esa-sceva/satcom-chunk-collection huggingface dataset:
# EpiInfer: A Non-Markovian Method and System to Forecast Infection Rates in Epidemics
## 8 Using Average Number of Meetings Instead of Meeting Distribution
### EpiPolicy Data Gamma Meeting Distribution Experiment  
The final series of experiments consists of three different meeting distributions, where each one follows a discretized version of the gamma distribution with the same mean (12), but with differing variances. The parameters \(\alpha\) and \(\theta\) are (12, 1), (2, 6), and (1, 12) respectively.  
The positive effect of using EpiInfer with full meeting distribution data can best be seen when comparing the two approaches for 20-day predictions across all three meeting distributions.  
For the meeting distribution with \(\alpha=12\) and \(\theta=1\), the difference between the means is 0.12, with a \(p\)-value of 0.207. For \(\alpha=2\) and \(\theta=6\), the difference between the means is 0.15, with a \(p\)-value of 0.1332. For \(\alpha=1\) and \(\theta=12\), the difference between the means is 0.36, with a \(p\)-value of 0.024. Figure 9 shows the comparison of these approaches for 20-day predictions across all three \(\alpha\), \(\theta\) pairs.  
Figure 8: Second EpiPolicy data experiment predictions of EpiInfer and EpiInfer with average number of meeting only. Every parameter except \(\beta\) is the same as described in Section 4.2. The values of \(\beta\) for the three groups are 0, 1.5, and 0. EpiInfer with the full data distribution performs better than the average only in most cases. (**a**) One-day predictions with 10–50 training days. (**b**) Five-day predictions with 10–50 training days. (**c**) Ten-day predictions with 10–50 training days. (**d**) Twenty-day predictions with 10–50 training days.  
Figure 9: Gamma meeting distributions experiment 20-day predictions of EpiInfer with full meeting distribution data compared with EpiInfer using the mean number of meetings only. Every parameter except \(\beta\) is the same as described in Section 4.2. The values of \(\beta\) are (0.4, 0.55, 0.75), (0.2, 0.5, 1.05), and (0.05, 0.35, 1.25) respectively. As the variance of the number of meetings increases, EpiInfer with full  
meeting distribution data performs increasingly better compared to EpiInfer using the mean number of meetings only. (**a**) Twenty-day predictions with 10-50 training days for \(\alpha=12\) and \(\theta=1\). (**b**) Twenty-day predictions with 10-50 training days for \(\alpha=2\) and \(\theta=6\). (**c**) Twenty-day predictions with 10-50 training days for \(\alpha=1\) and \(\theta=12\).  
The last two experiments show that using EpiInfer with full meeting distribution data is most beneficial when the variance of the number of meetings per person is high. That is, using the mean number of meetings is significantly worse when the number of meetings differs a lot between population subgroups.  
The conclusion we can draw from these experiments is that we should use the meeting distribution when available, but that the mean of the meeting distribution (i.e., the average number of people each person meets) is often nearly as good unless the meeting distribution is highly bimodal or strongly fractal.
# Decolorization of Orange-G Aqueous Solutions over C\({}_{60}\)/Mcm-41 Photocatalysts
## 4 Conclusions  
A series of C\({}_{60}\)/MCM-41 photocatalysts was studied for the first time in azo-dye removal from water. All these photocatalysts were proven to be active in the decolorization of orange G aqueous solutions.  
The decolorization is achieved partly in the dark via adsorption of orange G on the bare MCM-41 surface following pseudo-second order kinetics. The adsorption in this stage is not accompanied by decomposition. The specific adsorption of the dye decreases as the fullerene content increases because  
Figure 7: Degradation (%) of Orange G aqueous solution using the same 3C\({}_{60}\)/MCM-41 powder (1–5 cycles). The initial concentrations of methyl orange and ascorbic acid were 25 \(\upmu\)M and 0.50 mM, respectively.  
photocatalyst specific surface area decreases and the surface of MCM-41 is covered by an increasing amount of the sensitizer.  
The extent of decolorization is increased by irradiation in the presence of ascorbic acid and it is due to the photocatalytic degradation of the azo dye which is following first order kinetics.  
The photocatalytic activity increases initially with C\({}_{60}\) loading. It takes its maximum value over the sample containing 3 wt % C\({}_{60}\) and then it significantly decreases as the C\({}_{60}\) loading increases to 6 wt %. Further increase of C\({}_{60}\) loading (up to 12 wt %) is accompanied by a slight decrease of photocatalytic activity being the result of a compromise between the increase of active phase loading and the lowering of its dispersion and thus intrinsic activity. The high photocatalytic activity exhibited by the sample 3C\({}_{60}\)/MCM-41 is attributed to the very small C\({}_{60}\) clusters supported on MCM-41, which exhibit very high intrinsic activity.  
The 3C\({}_{60}\)/MCM-41 catalyst proved to be quite stable upon five subsequent photocatalytic cycles, losing less than 5% of its initial activity.  
The crucial role of ascorbic acid for photocatalytic degradation of azo-dyes over supported C\({}_{60}\) catalysts has been demonstrated once again and a reaction network has been proposed.  
The following are available online at [[http://www.mdpi.com/2076-3417/9/1958/s1](http://www.mdpi.com/2076-3417/9/1958/s1)]([http://www.mdpi.com/2076-3417/9/1958/s1](http://www.mdpi.com/2076-3417/9/1958/s1)), Figure S1: Photocatalytic reactor (Heraeus) with the TO 150 lamp situated in a glass cooling jacket filled with re-circulated deionized water and immersed in the reaction mixture, Figure S2: Relative spectral radiant flux of low pressure Hg lamp (TQ 150) being in a glass cooling jacket filled with re-circulated de-ionized water.  
All authors have contributed equally  
This research received no external funding  
The authors declare no conflict of interest
# A Novel Fused Multi-Class Deep Learning Approach for Chronic Wounds Classification
## 4 Experimental Setup and Results
### Datasets
#### 4.1.2 Extended Medetec Dataset  
The Extended Medetec dataset is the extended version of the original Medetec dataset. To reduce the class imbalance problem of the Medetec dataset, we have added more images in the Diabetic wound class. In the extended version, there are 174 images in the Diabetic wound class, while in the other two classes (i.e., Pressure and Venous), the number of images is the same as in the original Medetec dataset.
## 4 Results and Discussion
### Results and Discussion of Geo-Environment Indicator Distribution
#### 4.1.8 Enrichment of Deep Groundwater and Geothermal Resource  
Based on the available data, groundwater and geothermal resources were relatively abundant in Rongcheng, and showed certain zonation characteristics (Figures 9 and 10).  
The enrichment of deep groundwater for suitability for urban construction, making 1000 m\({}^{3}\)/d, 3000 m\({}^{3}\)/d, and 5000 m\({}^{3}\)/d as grading standards [47], could be divided into four grades, corresponding to very high (>5000 m\({}^{3}\)/d), high (3000-5000 m\({}^{3}\)/d), moderate (1000-3000 m\({}^{3}\)/d), and low (<1000 m\({}^{3}\)/d) (Figure 9) (Table 3). Meanwhile, geothermal resources, according to the difference of geothermal gradient, could be divided into four grades, corresponding to very high (\(\geq\)6 \({}^{\circ}\)C/100 m), high (\(\geq\)5 \({}^{\circ}\)C/100 m), moderate (\(\geq\)3 \({}^{\circ}\)C/100 m), and low (<3 \({}^{\circ}\)C/100 m) (Figure 10) (Table 3).  
Figure 8: Zonal distributions of chemical corrosion of steel by groundwater.
## 4 Application of Moisture Identification and Algorithm Comparison  
In order to verify the advantage of the two-step method, the AE feature parameters were selected through the two-step method. The Pearson coefficients method and and principal component analysis (PCA) were taken as input vectors for the SVM classifier to realize moisture identification. Algorithm comparisons were conducted. The AE parameter data that were used in this experiment were taken from Section 3. The experimental setup and boundary conditions, including the sandstone sample source, data acquisition equipment, and the system-computing environment, were identical to those in the experiment in Section 3.
# MQC-MB: Multiphoton Quantum Communication Using Multiple-Beam Concept in Free Space Optical Channel
## 4 The Implementation of MQC-MB  
MQC-MB aims to improve SKR by reducing the geometrical loss between the sender and receiver while maximizing the light beam to reach the receiver's telescope. This section presents the proposed MQC-MB with secret polarization, which means the information is encoded to non-orthogonal quantum states so that the state cannot be duplicated by an  
Figure 2: Multiple-beam technique in FSO link [32].  
eavesdropper. If any eavesdropping attempt occurs, error will be introduced during the transmission process. Besides, the multiple parallel multiphotons are sent separately into the FSO to ensure that an eavesdropper cannot tap the transmitted photons that are in the quantum channel. There are two phases involved in the MQC-MB to send the photons, which are the initial phase and the quantum communication phase. The system model of MQC-MB is depicted in Figure 3, where [PERSON] transmits the quantum states parallel to Bob [15; 22].  
The general input and output model of the multiphoton can be represented as:  
\[\left[\begin{array}{cccc}R(\theta_{1})|\Psi 1_{i}\rangle&R(\theta_{1})|\Psi 1_{i+1}\rangle&\ldots&R(\theta_{1})|\Psi 1_{n}\rangle\\ R(\theta_{2})|\Psi 2_{i}\rangle&R(\theta_{2})|\Psi 2_{i+1}\rangle&\ldots&R( \theta_{2})|\Psi 2_{n}\rangle\\ \vdots&\vdots&\ddots&\vdots\\ R(\theta_{4})|\Psi 4_{i}\rangle&R(\theta_{4})|\Psi 4_{i+1}\rangle&\ldots&R( \theta_{4})|\Psi 4_{n}\rangle\\ \end{array}\right]= \tag{14}\] \[\left[\begin{array}{cccc}\left|\Psi 1^{\prime}_{i}\rangle,\left|\Psi 1^{\prime}_{i+1}\right\rangle&\ldots&\left|\Psi 1^{\prime}_{n}\right\rangle\\ \left|\Psi 2^{\prime}_{i}\right\rangle,\left|\Psi 2^{\prime}_{i+1}\right\rangle&\ldots& \left|\Psi 2^{\prime}_{n}\right\rangle\\ \vdots&\\ \left|\Psi 4^{\prime}_{i}\right\rangle,\left|\Psi 4^{\prime}_{i+1}\right\rangle&\ldots& \left|\Psi 4\right\rangle\\ \end{array}\right]\right]\]  
where \(R(\theta_{i})\) is the secret rotation angle of HWP for each number of the beam, \(i=1,2,\ldots 4\) based on Equation (14), \(|\Psi\rangle\) is the input photon states of \(|0\rangle\) or \(|1\rangle\), and \(|\Psi\prime\rangle\) is the output states. The arbitrary value of \(\theta\) is set to \(0^{\circ}<\theta<180^{\circ}\):  
\[M_{HWP}=\left[\begin{array}{cccc}1&0&0&0\\ 0&\cos(4\theta)&\sin(4\theta)&0\\ 0&\sin(4\theta)&-\cos(4\theta)&0\\ 0&0&0&-1\\ \end{array}\right] \tag{15}\]
## 2 Materials and Methods
### Monitoring the Saturated Zone  
The equipment installed to monitor the saturated zone during the helium injection test was as follows:  
* Two physicochemical sensors for measuring temperature, pH, electrical conductivity, oxidation-reduction potential, and dissolved oxygen; one was permanently installed (for the duration of the test) in the PZ2 BIS piezometer located 5 m downstream of the injection borehole while the other one was mobile to take measurements in all other piezometers;
* A GGUN-FL30 field fluorimeter which provides live analysis of the fluorescence of the water extracted from the piezometers; it is a multichannel device that can successively analyze the three fluorescent tracers used;
* A GRUNDFOS-MP1 submersible pump which was first used to fill the tanks from the PZ2 and moved to the PZ2 BIS shortly before the start of the injection; it made it possible to regularly sample the groundwater to carry out laboratory analyses of the tracers, dissolved gases (helium) and major elements (calcium, magnesium, sodium, potassium, bicarbonate, chlorides, sulfates, nitrates);
* A Raman and Infrared (IR) spectrometer, installed in the PZ2 TER piezometer located 7.5 m downstream of the injection well [16; 17]; it makes possible to analyze the concentration of mononuclear diatomic molecules (H\({}_{2}\), O\({}_{2}\), N\({}_{2}\)) as well as polar molecules (CO\({}_{2}\) and CH\({}_{4}\)) in the water; since the detection of a monoatomic gas such as He is not possible with this type of sensor, only the indirect effect on the concentration of other dissolved gases can be detected;
* A device for water pumping from the aquifer and degassing by mechanical agitation; it is combined with an ALCATEL ASM 122D transportable mass spectrometer to measure the helium concentration in the degassed gas mixture.
## 3 Energy Harvesting Techniques
### Kinetic Energy Harvesting  
Kinetic energy harvesting captures mechanical motion, such as vibrations or movements, and converts it into electrical energy using piezoelectric materials or electromagnetic generators [65; 66; 67]. This technique is particularly useful in environments with constant vibrations or movement. The power generated from vibrations can be expressed as follows:  
\[P=\frac{1}{2}m\cdot A^{2}\cdot\omega^{3}\cdot Q \tag{3}\]  
where \(P\) is the electrical power output (in watts), \(m\) is the mass of the vibrating object (in kilograms), \(A\) is the amplitude of the vibration (in meters), \(\omega\) is the angular frequency of the vibration (in radians per second), and \(Q\) is the quality factor of the system. The **advantages** of kinetic energy harvesting are as follows:  
* Versatility: Can be used in various settings, including wearable devices and industrial equipment.
* Low Maintenance: Passive energy harvesting requires minimal maintenance compared to battery-powered systems. The **limitations** of kinetic energy harvesting are as follows:
* Variable Power Output: Power generation depends on the intensity and frequency of mechanical motion.
* Complex Integration: Integrating kinetic energy harvesters into existing systems can be challenging.  
Figure 4 shows a kinetic energy harvesting system, including the piezoelectric materials or electromagnetic generator and the sensor node.
# EUV-Induced Plasma: A Peculiar Phenomenon of a Modern Lithographic Technology
## 2 EUV-Induced Plasma  
### Observation of a Peculiar Phenomenon: EUV-Induced Plasma  
In 2006, researchers at the research department of world leader in photolithography systems ASML reported a peculiar phenomenon that would later be referred to as \"EUV-induced plasma\" [10]. A glow was created upon sending a pulsed beam of EUV photons through a low pressure (a few Pa) background gas (see Figure 1). Even by the naked eye, it could be observed that the created plasma--or more specifically the excited plasma species that radiate in the visible spectrum--was visually confined in space. Although the state of this matter (plasma) and its potential impact on the lithography tool was immediately recognized, the relevant mechanisms where far from understood and key parameters of this plasma where not known at all. As a reaction, several research groups around the world started to perform both experimental and numerical studies with the aim of unraveling this plasma's secrets. In this part, we elaborate first on the key parameters to be expected in EUV-induced plasmas in Section 2.2. With these parameters in mind, Sections 2.3 and 2.4, respectively, review the governing numerical and experimental research efforts that have been undertaken until today. Section 2.5 describes the principle mechanisms behind the plasma formation and subsequent plasma dynamics, while Section 2.6 summarizes the relevant scaling laws with respect to the plasma densities to be expected under scanner conditions. It should be noted that--although measurements have been conducted in other gases, such as argon as well [11]--only EUV-induced plasmas in H\({}_{2}\) background gas are discussed in detail in this work. The reason for this is that today's lithographic tools are operated while using low pressure H\({}_{2}\) gas [3].
## 3 P2Y12 and Thrombis
\begin{table}
\begin{tabular}{c c c} \hline \hline
**P2Y12 Inhibitors** & \multicolumn{2}{c}{**The Targets Functions of Drugs**} & **References** \\ \hline Clopidogrel & Clopidogrel is a P2Y12 receptor inhibitor which selectively inhibits the binding of ADP to platelet receptors, the activation of ADP-mediated glycoprotein & GPIIb/IIIa complex, and platelet aggregation. It is used to prevent and treat heart, brain and other arterial circulatory disorders caused by high platelet aggregation, such as recent strokes, myocardial infarctions and confirmed peripheral arterial diseases. & [50; 51] \\ Prasugrel & Prasugrel is a new orally effective thienopyridine drug. The P2Y12 adenosine diphosphate receptor on platelets can be irreversibly inhibited after the cytochrome P450 enzyme system is metabolized to the active metabolite. & [53; 54; 55] \\ Prasugrel & Prasugrel has a higher conversion rate of prodrug to active metabolites and higher bioavailability, so it takes effect faster and can reduce the difference in efficacy between individuals, and reduces major ischemic cardiovascular events to a greater extent Incidence rate. & \\ Ticagrelor is an oral P2Y12 receptor antagonist, which is a new type of cyclopentyl triazole pyrimidine oral antiplatelet drug. Ticagrelor promotes a greater inhibition of adenosine 5”-diphosphate (ADP)-induced Ca2+ release in shed platelets compared with other P2Y12R antagonists. Studies have also shown that ticagrelor is significantly better than clopidogrel. In clinical trial, 2 different dosages, 90 twice daily and 60 mg once a day of ticagrelor both showed reduced risk of cardiovascular death. & [56; 57; 58; 59; 60] \\ \hline \hline \end{tabular}
\end{table} 
Table 1: The treatment drugs of diseases based on P2Y12 receptors. Figure 1: The activation of P2Y12 receptor in platelet activation and other biological process. thrombosis [80]. Ticagrelor and clopidogrel can effectively reduce platelet reactivity by inhibiting the P2Y12 receptor, but they cannot inhibit the formation of early atherosclerosis. The role of P2Y12 inhibitors is mainly reflected in the development of atherosclerotic diseases [74].
# Strength Correlation and Prediction of Engineered Cementitious Composites with Microwave Properties
## 2 Methodologies
### Microwave Near-Field Detecting Technique
#### 2.2.3 Measurement Techniques  
In measurement, the authors used the near-field reflection wave approach [20; 21]. The complex reflection coefficient (\(\Gamma\)) was obtained and computed from the PNA using signal reflected from the ECC specimen under test. The PNA was capable of direct displaying a normalized admittance (unit-less) from the built-in inverse Smith chart with approximate loaded waveguide probe admittance (\(Y_{L}\)). The measured normalized admittance (\(y_{L}\)) has a complex form as  
\[y_{L}(\omega)=\frac{Z_{o}}{Z_{L(\omega)}}=\frac{Y_{L}(\omega)}{Y_{o}}=g( \omega)+jb(\omega) \tag{2}\]  
where \(Y_{o}=1/Z_{o}\) is the waveguide characteristics admittance in unit of Siemens; \(g(\omega)\) and \(b(\omega)\) are, respectively, the normalized conductance and normalized susceptance at frequency \(\omega\), and \(j\) is an imaginary number with a value of the square root of \(-1\).  
In this study, a direct measurement of normalized admittance (both the real and imaginary parts) in a single step was used. The reflection coefficient with respect to the RWG aperture and the normalized admittance have the following relationship:  
\[\Gamma(\omega)=\frac{Y_{o}-Y_{L}(\omega)}{Y_{o}+Y_{L}(\omega)}=\frac{1-y_{L} (\omega)}{1+y_{L}(\omega)} \tag{3}\]  
Effective electrical conductance was directly related to the dielectric properties of CBMs with high water/moisture content at early ages, and thus more suitable for measurement of early-age CBMs during hydration [21]. Daily near-field measurement was undertaken for PE2 and PE3 specimens from Day-1 to Day-8, whereas measurement of PE1 commenced on Day-2 due to its late casting and hydration. For each specimen, 10 measurements were performed on non-overlapping locations of each side surface excluding the top and bottom surface, to avoid high surface roughness. Therefore, a total of 40 readings of normalized electrical admittance for each specimen were recorded in such a way that the side-surfaces were rotated in turn for measurement. The average and standard deviation values of these 40 measurements would be used to represent the daily variations of microwave properties for each specimen. In order to obtain measurement results under consistent environmental conditions, surface temperature and humidity of specimens were monitored during the measurement.
# A Review of Industry 4.0 Manufacturing Process Security Risks
## 3 Identifying the Problem
### Case Studies of Cyber-Physical Attacks
#### 3.1.3 Duqu and Flamer--Followers of Stuxnet  
With Stuxnet paving the way for the development of extremely complex and powerful cyber-attacks, two new threats that are very similar to Stuxnet made their entry less than a year after the Stuxnet worm went viral. Although very similar to the Stuxnet codebase, the Duqu threat was developed primarily to steal information from industrial manufacturing entities, so as to facilitate the development of more specific and focused attacks on other third parties. Consisting mainly of a driver file, a dynamic link library (DLL) and configuration file that were installed by an executable file through a Microsoft Word document that contained a zero-day kernel exploit, the threat would search for detailed design information (among other proprietary information) and make use of HTTP and HTTPS to upload and download information between the infected devices and its C&C servers. One variant of the threat had a particularly novel way of hiding the DLL containing the primary functions of the threat. This DLL was hidden as encrypted data contained in a JPEG file which featured an image taken by the Hubble Space Telescope. Another novel feature of the Duqu threat in general was that it would remove itself from the infected device after approximately 30 days, thus minimizing the possibility of its detection [29].  
The first attack by the Duqu threat was recorded in early April 2011, with additional variants encountered in October 2011. By the time that a comprehensive analysis of the Duqu threat was published by Symantec in November 2011, more than eight countries had fallen victim to the 15 variants of the threat [29].  
Similar to the Duqu threat, the Flamer threat also has deep roots in the Stuxnet codebase, and has been in existence since 2010. Symantec considered the Flamer threat the most complex malware that had ever been written at the time of its detection and analysis, and it is anticipated that it will retain this reputation for many years to come. Its size is in excess of 20 megabytes, and the software architectural design is on a par with professionally developed software. The purpose of the Flamer threat was similar to that of the Duqu threat, i.e., industrial espionage, but on a much larger scale [30].