esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Conclusions  
This article presents the results of experimental determinations of the properties of C12/15 concrete mixes and hardened concretes containing either fly ash or glass powder. Based on the performed research and analyses, the following can be concluded:  
* Concrete mixes with glass powder are characterized by a greater liquidity and a greater total air content.
* Irrespective of the type and quantity of the added material, the concretes have comparable compressive strength classes falling in the range between 24.7 MPa and 28.7 MPa. All the tested mixes met the compressive strength requirements for C12/15 class concrete and can be used for casting footings to support road kerbs and gutters along national roads in Poland.
* The greatest differences between the mixes concerned durability. As a result of exposure to freezing temperatures, the control mixes with fly ash suffered considerable damage. Replacement of fly ash with waste-glass powder in C12/15 strength concrete result in concretes satisfying the freeze-thaw resistance criteria for classes F25 and F100.  
In light of the test results obtained for the reference concretes (with fly ash addition), glass powder was shown to have no adverse effect on the compressive strength of concrete, did not significantly increase its water absorption, and significantly improved the resistance to frost attack. The above conclusions should be deemed preliminary and can be used as a basis for deriving a plan for further research. To begin with, the authors plan to verify ground waste glass added to concrete in terms of reactivity. Furthermore, for a more accurate picture, we also plan to carry out studies concerning the particle size and shape distribution of both fly ash and ground waste glass. Taking into consideration current efforts aimed at curbing CO2 emissions and material consumption, the results obtained in this study justify the need for further research on the use of recycled glass powder as a concrete admixture.  
Conceptualization, R.J. and F.S.; preparation of samples for testing, R.J. and F.S.; testing of samples concrete F.S.; formal analysis, R.J.; writing--original draft preparation, R.J.; writing--review and editing, R.J. and F.S. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The authors declare no conflict of interest.
## 2 Materials and Methods  
### Study Area  
Lake Alboraj is located in SE Spain, a karstic-tectonic sinkhole formed about 700,000 years ago [14], which sustains a permanent waterbody. The region is influenced by a semiarid meso-Mediterranean climate, with an historic average annual precipitation below 380 mm, with a fresh autumn (average autumn temperature of 6.7 \({}^{\circ}\)C) and a hot summer (average summer temperature of 24.3 \({}^{\circ}\)C). As freshwater habitat, this lake has been classified as type 3190 \"Lakes of gypsum karst\" within Natural Habitat Types of Community Interest [4; 15]. According to the lithology characteristics, the lake is hyposaline, calcium-sulphated, with a historic conductivity ranging from 2240-2496 mg/L (Regional Decree 182/2000; Declaration of the Micro-reserve Lake Alboraj) and Natural Resources Management Plan of Lake Alboraj). The small endorheic lake basin (120 ha) is in an agricultural landscape, where eutrophication, salinisation and lowering of the water level are the main anthropic impacts. Groundwater and surface water withdrawals have caused the shrinkage of the lake from a flooded area of 16,000 m\({}^{2}\), in the early 80's of the past century, to 5500 m\({}^{2}\), in 2017 [16]. The -like shrinking in turn has caused a salinity increase up to 5760-7680 mg/L [9]. Nowadays, the lake water table reaches 100 m in diameter, 5000 m\({}^{2}\) of surface and settle three deep dolines (5 m depth in its deepest doline) with shallow interdoline areas less than 2 m deep [10]. This geomorphological feature promotes the formation of a marked seasonal oxygen stratification pattern of the water column.  
The water level fluctuates and very much depends on the precipitation regime, although groundwater inputs from a local shallow Pliocene aquifer formed in the surroundings prevent drying. From a bathymetry model, the maximum volume of stored water has been estimated in 0.018 hm\({}^{3}\), corresponding to a laminar water area of 9500 m\({}^{2}\) and a maximum depth of 6.5 m (unpublished data). No water withdrawal or surface sewage discharges occur in the lake.  
Typically, when the oxygen stratification occurs, the lake shows three different layers: the epilimnion, which comprises the upper aerobic layer; the metalimion, the next layer in the depth profile that comprises from the depth at which oxygen starts to decrease to the depth at which anoxia is reached, i.e., the oxycline; and the hypolimnion, extends from the end of metalimnion to the lake bottom, i.e., the anaerobic layer. The oxygen depletion coupled with a strong gradient in physico-chemical parameters in the metalimion.
# Exploitation of Antimicrobial Nanoparticles and Their Applications in Biomedical Engineering
## 3 Mechanisms of Action of Antibiotics and Nanoparticles Against Bacteria
### The Mechanisms of Actions of Antimicrobial Nanoparticles  
In general, four proposed theories were considered to trigger the bactericidal deactivations, depending on the chemistry (i.e., constituents/ionic states) and the physical properties (i.e., particle shapes/sizes) of the nanoparticles. Figure 4 shows a representative diagram of the four possible mechanisms, and their details can be explained as follow:  
1. Reactive oxygen species (ROS): ROS include superoxide anion (\(O_{2}^{-}\)), hydroxyl radicals (\(\bullet OH\)) singlet oxygen (\(O_{2}\)) and hydrogen peroxide (\(H_{2}O_{2}\)) (by-products of cellular oxidative metabolism) [115]. Typically, redox-active essential metals present in biomolecules act as catalytic cofactors when ROS are either generated or catalysed by cell enzymes. The presence of external metals intensifies reactions producing an excess of ROS that trigger oxidative stress and subsequently lead to cellular programmed death [116; 117]. With specific metals, an occurrence of Fenton reactions both increases the formation of ROS and stimulates the electron transport chain to eventually promote bacteria death through the catabolism of the carbon source and the generation of nicotinamide adenine dinucleotide [13].
2. Dissolved metal ions: external metal ions are absorbed through the cell membrane and inhibit cellular function or enzyme activity by interacting with the functional groups of proteins and nucleic acids, which eventually affect the normal physiological processes [14].
3. Physical interaction: unlike antibiotics, Gram-negative bacteria are more vulnerable to nanoparticle mechanisms of action since their wall structure may assist released ions from the nanoparticle into the cell. In addition, although both bacteria cell walls  
Figure 3: Structure difference of Gram-negative and -positive bacteria. Reproduced with modification from [PERSON] et al., _Journal of Nanobiotechnology_; published by Spring Nature, 2017. [15].  
are dominated by negative charges, Gram-negative bacteria have a higher affinity for the positive ions due to electrostatic attraction [15].
4. Internalisation into the cell: smaller sizes of particles are likely to enter the cells via endocytosis. Subsequent, released nanoparticle ions are then up-taken in high intracellular concentration, which leads to oxidative stress [16].  
It is known that smaller-sized nanoparticles enhance antimicrobial properties due to the increase in surface area to volume ratio. Conversely, smaller-sized particles have shown an increase in toxicity towards mammalian cells; thus, concentration and leaching of nanoparticles from products are also to be considered [19; 118]. Moreover, common physico-chemical behaviour, such as particle agglomerations that were found in nanoparticles when suspended in a biological medium, appeared to reduce antimicrobial effectiveness [119].
## 3 Results and Discussion
### Tests with Sigma-Delta Converters with Four Chassis  
In the first stage of this phase, the tests focused on the analysis of the Sigma-Delta converters with the distribution shown in Figure 4. The study was carried out to observe the behaviour of the distributed capture system under the same conditions as the tests with the NI-9215 modules. As mentioned above, these tests served as a reference to determine whether this conversion technology could be replaced by SAR converters.  
The box plot in Figure 17 shows that the results were below 50 ns for a 95% distribution of the samples with two chassis and with both 50 m and 75 m cabling. These are undoubtedly the highest quality results, guaranteeing an uncertainty of 5%. Conversely, this quality was progressively reduced when three and four chassis were used. In no case did 95% of the samples exceed 110 ns. Figure 18 shows a response with an almost Gaussian distribution for the four tests, with a dispersion level of less than 40 ns for the first three tests and less than 190 ns when using four chassis.  
Figure 16: The four cDAQs connected in-line with 50 m, 75 m, and 10 m cables.  
Figure 17: Box diagram for Sigma-Delta converters.  
The results in Table 6 show a median that increases progressively from values of 21.5 ns to 80 ns. This is a very high-quality response that facilitates the comparative study with lower resolution 16-bit converters with a lower time response.
## 3 Results and Discussion
### Analysis of VOCs in Base Wines  
The volatile components of the five lots of base wine were analysed by SPME-GC-MS. As can be seen in Table 2, 59 volatile components were detected and they were grouped in acetates, methyl and branched esters, ethyl esters, fused alcohols, C6-alcohols, acids, terpenes, phenols, aldehydes and ketones. According to their number, the ethyl ester group was the most numerous (17 compounds), followed by 13 alcohols, 7 acids, 5 acetates and 5 phenols.
## 2 Proposed Approach
### Model Architecture
#### 2.3.2 Decoder
\(d_{k}\) is the common number of columns of these learnable matrices. Figure 1: The schematic diagram of the decoder. Q, K, and V indicate the query, key, and value in the attention, respectively. Experiments were conducted by changing the number of decoder layers from one to six, and the best results were obtained when set to two. In addition to the soft parameter sharing in the encoder part, the DCMA process will play a major role in obtaining the association between SED and DOAE feature information prior to the prediction.
## 3 Results  
### Characterization of the 5G NR Signal  
The spectrum overview measurements performed once at each site showed similar RF environments. RF signals were detected in the following telecommunications bands: 800 MHz (Long Term Evolution, LTE), 900 MHz (Global System for Mobile Communications (GSM) and LTE), 1800 MHz (LTE), 2100 MHz (Universal Mobile Telecommunications System, UMTS), 2400 MHz (Wireless Fidelity, Wi-Fi), 2600 MHz (LTE), and 3500 MHz (NR), the latter of which contained the 5G NR signals to be evaluated. The other bands were accurately characterized using the SRM-3006 analyzer (Table 1).  
A closer look at the 100 MHz-wide signal around 3.6 GHz (Figure 2) revealed [13] the position of the SSB at the start of the channel bandwidth (Figure 3), namely at \(SS_{REF}\) = 3604.8 MHz (with corresponding global synchronization channel number (GSCN) of 7919). Furthermore, its width of \(\sim\)7 MHz indicated an SCS of 30 kHz (Figure 3). This was checked and observed at each of the investigated sites.  
Figure 1: Tri-axial Satimo INSITE Free electric-field probe (at a height of 1.5 m) in line-of-sight of a fifth generation new radio base station in Bern, Switzerland.  
\begin{table}
\begin{tabular}{l c c c} \hline \hline
**Band** & \(\mathbf{E_{arg,min}}\) & \(\mathbf{E_{arg,max}}\) & **Average Relative** \\  & [**V/m**] & [**V/m**] & **Contribution [\%]** \\ \hline
800 MHz & 0.2 & 0.9 & 44 \\
900 MHz & 0.1 & 0.7 & 24 \\
1800 MHz & 0.09 & 0.6 & 15 \\
2100 MHz & 0.09 & 0.5 & 12 \\
2400 MHz & \textless{}0.01 & 0.02 & \textless{}1 \\
2600 MHz & 0.04 & 0.2 & 4 \\
3500 MHz & & & \\ (without traffic) & \textless{}0.01 & 0.04 & \textless{}1 \\ (with traffic) & 0.02 & 0.4 & 2 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Minimum and maximum average electric-field levels (\(E_{agg}\)) measured for various frequency bands used for wireless telecommunications, as well as the average contribution of these bands to the total environmental RF-EMF exposure.  
Figure 3: Samples (black dots, with the envelope indicated by a red dotted line) measured with the FSV spectrum analyzer along one electric-field component that are a part of a four-symbol long signal, i.e., the length of a synchronization signal block (SSB). This way, the frequency position and subcarrier spacing (SCS) of the SSB can be deduced: in this case, the SSB has a center frequency \(SS_{REF}\) 3604.8 MHz and has an apparent width of 7 MHz (delineated by the two blue dashed lines), indicating an SCS of 30 kHz.  
Figure 2: Spectrum overview between 700 MHz and 6 GHz at one of the investigated sites with a fifth generation (5G) new radio (NR) base station. Here, the total electric-field level (i.e., the vector sum of the three orthogonal components) was normalized to the maximum. Besides the NR signal around 3.6 GHz, other radiofrequency (RF) signals were observed in the telecommunications bands at 800, 900, 1800, 2100, 2400, and 2600 MHz. Similar results were obtained at the three other sites.
## 4 Conclusions  
In this research, high-precision CT scanning equipment was used to study the erosion process of saturated magnesium sulfate, sodium sulfate solution, and freeze-thaw cycles on twff. We quantitatively examined the pore changes in twff under frost and salt weathering.  
1. [label=(0)]
2. Saturated magnesium sulfate is more corrosive to twff than sodium sulfate when erosion days reach 60; the quality loss rate of twff immersed in a saturated magnesium sulfate solution is 1.56%. Sodium sulfate solution increases the mass of twff by 0.33%.
3. Freeze-thaw cycles have a significant influence on twff's weathering. After 60 freeze thaw cycles, the mass loss rates of twff in solutions of distilled water, sodium sulfate, and magnesium sulfate were 3.82%, 3.52%, and 3.58%, respectively.
4. From 10 to 60 erosion days, the maximal and average porosity changes in all cross-sections in the sodium sulfate and magnesium sulfate groups were 3.42% and 5.54%, 4.14%, and 6.59%, respectively. The largest and average values of porosity change in the sodium sulfate and magnesium sulfate groups were 3.77% and 3.35%, and 2.18% and 2.25%, respectively, as the number of freeze-thaw cycles rose from 10 to 60.  
Conceptualization, H.J. and A.L.; Software, Y.S.; Formal analysis, Y.S. and A.L.; Investigation, L.C. and C.W.; Data curation, L.C. and C.W.; Writing--original draft, L.C. and A.L.; Writing--review & editing, P.S. and M.L.; Funding acquisition, P.S. and M.L. All authors have read and agreed to the published version of the manuscript.  
This study has been partially funded by the Second Tibetan Plateau Scientific Expedition and Research Program (Grant No. 2019 QZKK0904), the Program of the State Key Laboratory of Frozen Soil Engineering (Grant No. SKLFSE-ZT-202110), and the Science and Technology Plan of Gansu Province (22)R5 RA059).  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Not applicable.  
**Acknowledgments:** The authors thank the anonymous reviewers and editors for their constructive comments on this manuscript.  
**Conflicts of Interest:** The authors declare no conflict of interest.
# Random Segmentation: New Traffic Obfuscation against Packet-Size-Based Side-Channel Attacks
## 5 Evaluation and Results
### Efficiency  
In this section, we evaluate the byte overhead \(B\) and the time taken \(T\) by our algorithm. We calculate \(B\) as:  
\[B=\frac{D_{b}-W_{b}}{W_{b}} \tag{1}\]  
where \(D_{b}\) is the total amount of bytes transferred when implementing our defense, and \(W_{b}\) is the total amount of bytes transferred without implementing our defense. As we utilize the covered bytes presented in Table 2 solely for concealing data rate features, we deduct them from this calculation in the context of packet-size obfuscation.  
For the second aspect (\(T\)), we set up a remote virtual server and let our local machine send a large file of 10 MB, with and without our defense. Thus, we calculate the added latency by our methodology compared with the standard/undefended transmission scenario. We define \(T\) as:  
\[T=\frac{D_{t}-W_{t}}{W_{t}} \tag{2}\]  
Figure 3: Average packet size before and after obfuscating the bidirectional traffic of two devices over time.  
where \(D_{t}\) is the time span to send the file when implementing our defense, and \(W_{t}\) is the time span to send the same file without implementing our defense.  
Furthermore, we implemented two randomization levels to analyze the impact of the obfuscation intensity (i.e., range of random values) on \(T\). The wider the range of random lengths, the more packets are required to carry the payload. Consequently, more packets might take a longer time to deliver. For instance, sending a large array of data using random-sized packets ranging from 100 to MTU will result in significantly more packets than using a range of larger lengths between 1200 and MTU. For this experiment, we define two randomization levels (\(Rand_{(low)}\) and \(Rand_{(high)}\)) with an upper bound of a common maximum length of 1400 bytes, whereas the lower bound of each level varies as follows: \(Rand_{(low)}=1200\) and \(Rand_{(high)}=100\). We run ten sets of experiments and report the average result in the following section.
## Time-Efficient High-Rate Data Flooding in One-Dimensional Acoustic Underwater Sensor Networks  
**[PERSON] 1, [PERSON] 2, [PERSON] 3 and [PERSON] 4,*  
* Department of Electronic Engineering, Yeungnam University, Gyeongsan 712-749, Korea; E-Mail: [EMAIL_ADDRESS]
* School of Electronics Engineering, Kyungpook National University, Daegu 702-701, Korea; E-Mail: [EMAIL_ADDRESS]
* Institute of Industrial Technology, Yeungnam University, Gyeongsan 712-749, Korea; E-Mail: [EMAIL_ADDRESS]
* College of IT Engineering, Kyungpook National University, Daegu 702-701, Korea
* Author to whom correspondence should be addressed; E-Mail: [EMAIL_ADDRESS], Tel.: +82-53-950-7577; Fax: +82-53-950-5505.  
Academic Editor: [PERSON]  
_Received: 6 August 2015 / Accepted: 28 October 2015 / Published: 30 October 2015_  
**Abstract:** Because underwater communication environments have poor characteristics, such as severe attenuation, large propagation delays and narrow bandwidths, data is normally transmitted at low rates through acoustic waves. On the other hand, as high traffic has recently been required in diverse areas, high rate transmission has become necessary. In this paper, transmission/reception timing schemes that maximize the time axis use efficiency to improve the resource efficiency for high rate transmission are proposed. The excellence of the proposed scheme is identified by examining the power distributions by node, rate bounds, power levels depending on the rates and number of nodes, and network split gains through mathematical analysis and numerical results. In addition, the simulation results show that the proposed scheme outperforms the existing packet train method.  
**Keywords:** underwater sensor network; time efficiency; one-dimensional deployment; power consumption
## 4 ADRC-Based ABS Slip Ratio Tracking Control
### ABS Model
#### 4.1.2 Slip Rate Dynamic Model  
To find the second derivative of the wheel slip ratio described by Equation (4), the following expression is derived:  
\[\ddot{\lambda}=-\frac{\ddot{\omega}R}{v}+\frac{\omega\ddot{v}R}{v^{2}}+\frac{ 2\dot{\omega}vR}{v^{2}}-\frac{2\omega\dot{v}^{2}R}{v^{3}} \tag{18}\]  
By combining Equations (1)-(4) and Equations (6) and (7), and substituting them into the above equation, we can obtain the second-order nonlinear system expression for the slip ratio:  
\[\ddot{\lambda}=\frac{1}{mv}\left((\lambda-1)F\dot{\mu}(\lambda)+2F_{z}\mu( \lambda)\dot{\lambda}-\tau F_{z}R^{2}\dot{\mu}(\lambda)+\tau K_{b}K_{t}R\dot{I }_{a}\right) \tag{19}\]  
where \(\tau=m//j\); the dynamic model of the ABS slip rate of the EMB system can be described as a second-order nonlinear system with respect to slip rate.  
Figure 3: Electromechanical brake actuator structure.  
To improve vehicle braking performance, an active disturbance rejection control (ADRC) algorithm was used to design a controller for tracking the optimal slip ratio. Figure 4 shows the structure diagram of the ADRC-based ABS control strategy.
## 2 Results and Discussion
### Structural Analysis (X-ray Diffraction (XRD))  
Figure 4 shows characteristic XRD patterns of the samples before and after calcination. A broad spectrum exhibited by the sample before calcination indicates that the dried samples demonstrated an amorphous behavior. For the calcined samples at 500 \({}^{\circ}\)C and above, the spectrum shows sharp and narrow diffraction peaks, implying that the formation of crystalline TiO\({}_{2}\) nanoparticles was established. Moreover, higher values of calcination temperatures were observed to enhance the degree of crystallinity and the purity of the TiO\({}_{2}\) nanoparticles by increasing the intensity of the peaks and removing the undesired small peaks at lower calcination temperatures. This crystallinity enhancement is stemmed from the increment of the crystalline volume-to-surface ratio, as supported by transmission electron microscopy (TEM) images, which occurred due to particle size enlargement. The position of the Bragg's lines of the TiO\({}_{2}\) nanoparticles was used to determine the inter-planer spacing (d), which in turn was used to index the diffraction peaks. The existence of multiple diffraction peaks of (101), (103), (004), (112), (200), (105), (211), (204), (116), (220), and (215) in the diffraction patterns suggests that the TiO\({}_{2}\) samples have a typical tetragonal structures, referring to (JCPDS card no. 21-1272) [1; 3]. Similar XRD patterns were observed for commercial bicrystalline TiO\({}_{2}\)/P25, which was supplied by Degussa (80% anatase and 20% rutile) [33]. The co-presence of anatase and rutile crystallites induces a high level of photoactivity; the transfer of photoexcited electrons and the positive holes between interconnecting anatase and rutile particles can enhance charge separation and hence improve the efficiency of the utilization of electron-hole pairs [34].  
Figure 3: Energy dispersive X-ray spectroscopy (EDX) spectrum of TiO\({}_{2}\) nanoparticles calcined at temperature of 600 \({}^{\circ}\)C.  
The samples' crystallite sizes were found to be in the range of 8-42 nm (Table 1), which were calculated for the most intense peak (101) using the Scherrer's equation as given below:  
\[D=\frac{0.9\lambda}{\beta\text{cos}\theta}, \tag{1}\]  
where \(D\) is the crystallite size (nm), \(\beta\) is the full width of the direction line at half of the maximum (101) intensity measured in radians, \(\lambda\) is the X-ray wavelength of Cu K\(\alpha\) = 0.154 nm, and \(\theta\) is Bragg's angle.