esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Visible Light Communication Systems
Therefore, the channel response of the system could be written as:  
\[Hlos_{(i,p)}=\frac{T_{s}(\Psi)g(\Psi)A_{t}(m_{1}+1)(h_{i}-h_{p})^{m_{1}+1}}{2 \pi[\left(h_{i}-h_{p}\right)^{2}+\left(x_{i}-x_{p}\right)^{2}+\left(y_{i}-y_{p }\right)^{2}]^{\frac{m_{1}+3}{2}}}. \tag{6}\]  
Finally, the received power by the photodetector is given by:  
\[Pr_{(i,p)}=\frac{Pt_{i}T_{s}(\Psi)g(\Psi)A_{t}(m_{1}+1)(h_{i}-h_{p})^{m_{1}+1 }}{2\pi[\left(h_{i}-h_{p}\right)^{2}+\left(x_{i}-x_{p}\right)^{2}+\left(y_{i}- y_{p}\right)^{2}]^{\frac{m_{1}+3}{2}}}. \tag{7}\]  
For the particular application case at the receiver side (underground mining tunnel), it is assumed that the photo-detector is only exposed to the optical signals generated by the LED transmitters, and not to other natural or artificial lighting sources. The latter assumption is only an initial approach toward the analysis of VLC in underground mining. To the best of the authors' knowledge, the channel impulse response of a VLC system inside an underground mining facility has not yet been documented in the literature. Therefore, the received signal is modeled as:  
\[Y_{(i,p)}=rx*Hlos_{(i,p)}+n, \tag{8}\]  
where, \(Y_{(i,p)}\) represents the electrical signal received from LED \(i\) to receiver \(p\), \(r\) is the sensitivity in the photo-detector (A/W), \(x\) represents the transmitted optical pulse, \(*\) denotes the convolution operator, and \(n\) is modeled as additive white Gaussian noise (AWGN) with mean zero and variance \(\sigma^{2}\). The noise model used in this manuscript complies with the thermal and shot noise used in [41].
###### Abstract  
This paper studies the network performance of collaboration between the Internet of public safety things (IoPST) and drones. Drones play a vital role in delivering timely and essential wireless communication services for the recovery of services right after a disaster by increasing surge capacity for the purposes of public safety, exploring areas that are difficult to reach, and providing an area of rapid coverage and connectivity. To provide such critical facilities in the case of disasters and for the purposes of public safety, collaboration between drones and IoPST is able to support public safety requirements such as real-time analytics, real-time monitoring, and enhanced decision-making to help smart cities meet their public safety requirements. Therefore, the deployment of drone-based wireless communication can save people and ecosystems by helping public safety organizations face threats and manage crises in an efficient manner. The contribution of this work lies in improving the level of public safety in smart cities through collaborating between smart wearable devices and drone technology. Thus, the collaboration between drones and IoPST devices establishes a public safety network that shows satisfying results in terms of enhancing efficiency and information accuracy.  
IoPST; public safety network; drone; emergency communication; IoPST; SAR; smart cities +
Footnote †: journal:  
0000-0001-4522-2300][PERSON]  
1 School of Aerospace Engineering, Tsinghua University, Beijing 100084, China 12 Department of Electronics Engineering, IBB University, Ibb, Yemen 100084, China 2
## 2 Materials and Methods
### Daily Travel Mileage Distribution Estimation  
Driving range requirement is an essential indicator of travel behavior for ET drivers. We can obtain each taxi's daily travel mileage by mining the GPS dataset of taxi trajectories. The multi-day travel mileage for a vehicle is sorted in ascending order, and the median is taken as the driving range requirement for the driver. A modular battery swapping service allows ET drivers to choose the number of battery blocks to rent to cater to their driving range requirements and habits; thus, we can divide ET drivers into different groups according to the number of battery blocks they rent.  
In our study, one battery block can provide a 150 km driving range for the ETs, and an ET driver with a specific driving range requirement can install one to three battery blocks into an ET. For economy, they will rent the minimum number of battery blocks that can meet their driving range requirement. Hence, we classify the ET drivers into three groups according to the capacity of the battery block:  
* Short-distance travel (driving range requirement is less than 150 km);  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Taxi ID** & **Longitude** & **Latitude** & **Speed** & **Load State 1** & **Timestamp** \\ \hline
488115 & 116.357784 & 40.034022 & 32 & 1 & 10 October 2018 06:00:01; \\
214157 & 116.483694 & 39.942724 & 68 & 1 & 10 October 2018 06:00:01; \\
164927 & 116.233147 & 39.76826 & 76 & 1 & 10 October 2018 06:00:01; \\
470325 & 116.2453 & 39.861894 & 57 & 0 & 10 October 2018 06:00:01; \\
191485 & 116.484017 & 39.874658 & 20 & 0 & 10 October 2018 06:00:01; \\
21184 & 116.44534 & 40.002848 & 108 & 1 & 10 October 2018 06:00:01; \\ \hline \hline \end{tabular}  
* The passenger load state equals 1 when the ET is carrying passengers and 0 when the ET is empty.  
\end{table}
Table 1: An example for the GPS trajectory data.  
* Medium-distance travel (driving range requirement is larger than 150 km and less than 300 km);
* Long-distance travel (driving range requirement is larger than 300 km). The minimum distance for our sample is 30 km. As shown in Figure 2, the multi-day travel mileage of ET drivers of short-distance travel satisfies the truncated log-normal distribution (Equation (1)). Moreover, the multi-day travel mileage of ET drivers of medium- and long-distance travel satisfies the truncated normal distribution in Equation (2). \[f_{short}(d)=\frac{1}{d\sigma_{short}\sqrt{2\pi}}\exp\left[-\frac{\left(\ln d- \mu_{short}\right)^{2}}{2\sigma_{short}^{2}}\right]\ \,\ d\geq 30\] (1) \[f_{medium/long}(d)=\frac{1}{\sigma_{medium/long}\sqrt{2\pi}}\exp\left[- \frac{\left(d-\mu_{medium/long}\right)^{2}}{2\sigma_{medium/long}^{2}} \right]\ \,\ d\geq 30\] (2)  
We estimate the parameters \(\mu\) and \(\sigma\) in Equations (1) and (2) by the multi-day daily travel mileage of taxis that have been grouped.
## 4 Research Case
### Independent Variable Data
#### 4.3.3 Building Environment Variables  
Land use type POI is a major component of the built environment. In this study, we used Python to obtain POI data in Shenzhen, China, through the AMAP open platform. AMAP divides POI data into 23 categories. According to the type of POI and the standard of urban land use [43], land use is divided into six categories: servicing businesses, scenic spots, public services, government and corporate offices, commercial housing, and transportation hub, corresponding to variables \(X_{3}\) to \(X_{8}\).  
The floor area ratio reflects the intensity of land use development. To some extent, it reflects the economic level and residential activities in the area, denoted as \(X_{9}\). The formula is shown in Equation (8):  
\[X_{9}=\frac{F}{S} \tag{8}\]  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Independent Variable** & **Variable Name** \\ \hline \hline \multicolumn{3}{c}{**Socio-economic variables**} \\ \hline \(X_{1}\) & Population \\ \(X_{2}\) & Average house price \\ \hline \hline \multicolumn{3}{c}{**Built environment variables**} \\ \hline \(X_{3}\) & Servicing businesses \\ \(X_{4}\) & Scenic spots \\ \(X_{5}\) & Public services \\ \(X_{6}\) & Government and corporate offices \\ \(X_{7}\) & Commercial housing \\ \(X_{8}\) & Transportation hub \\ \(X_{9}\) & Floor area ratio \\ \(X_{10}\) & Land use mix \\ \(X_{11}\) & Road network density \\ \hline \hline \multicolumn{3}{c}{**Station characteristics variables**} \\ \hline \(X_{12}\) & Number of entrances and exits of rail transit stations \\ \(X_{13}\) & Accessibility \\ \(X_{14}\) & Bus lines \\ \(X_{15}\) & Bus stops \\ \hline \hline \end{tabular}
\end{table}
Table 2: Description of statistics of independent variables.  
where \(F\) is the total area of all above-ground buildings within the rail site buffer zone area, m\({}^{2}\), and \(S\) is the area of the rail site buffer zone, m\({}^{2}\).  
Land use mix can explain land use, and land use will affect residents' travel [44]. According to the existing research [45; 46], the Shannon-Wiener index was used to characterize the land mixing degree as the independent variable \(X_{10}\). The formula is shown in Equation (9):  
\[X_{10}=\frac{-(\sum\limits_{j=1}^{n}p_{j}\times InP_{j})}{InA} \tag{9}\]  
where \(X_{10}\) is the land use mix within the buffer zone of the rail transit site; \(P_{j}\) is the proportion of POI type \(j\) within the buffer zone of the rail transit site; \(A\) is the total number of POI types, and according to the previously mentioned land use classification, \(A\) is denoted as 6 in this paper.  
The road network density reflects the external accessibility of the rail transit station, reflecting the convenience of the residents to travel; it also affects the passenger flow of the rail transit station. The road network density is recorded as \(X_{11}\), as shown in Equation (10).  
\[X_{11}=\frac{\sum L}{S} \tag{10}\]  
where \(S\) is the area of the buffer zone range of rail transit stations, km\({}^{2}\), and \(L\) is the length of each road section within the buffer zone range, km.
# Phytoplankton as CO\({}_{2}\) Sinks: Redirecting the Carbon Cycle
## 6 Conclusions  
* Since the Industrial Revolution, 292 GtC have accumulated in the atmosphere, equivalent to 1072 Gt of CO2, and this number continues to increase annually at a growing rate of 5.1 GtC per year (18.75 Gt of CO2). This phenomenon is altering several of the planet's physicochemical parameters and cycles, such as temperature and the pH of large bodies of water, whose balance is vital for the stability of the vast majority of global ecosystems.
* The measures proposed by our civilization through various policies and international treaties have been slow and ineffective, focusing only on reducing emissions without implementing technologies to neutralize the excess CO\({}_{2}\). The window for intervention with a guarantee of success is closing.
* The mass cultivation of phytoplankton is presumed to be a mature technology capable of utilising and accelerating the natural cycles of CO\({}_{2}\) capture. Based on the literature reviewed in this work, an average CO\({}_{2}\) capture value of 34 g/m\({}^{2}\cdot\)day, equivalent to a biomass production rate of 17 g/m\({}^{2}\cdot\)day, is proposed for cultivated areas.
* From this value, it can be theorised that to neutralise the 18.75 Gt/year of CO\({}_{2}\) that accumulates in the atmosphere, an area of 2.1 \(\times\) 10\({}^{6}\) km\({}^{2}\) would need to be cultivated, equivalent to 0.41% of the planet's total surface or 1.41% of the land surface. These figures would imply a 6.5% increase in the global NPP value.
* This work also analyses the challenges that civilization would face in implementing phytoplankton cultivation technology on a global scale. It suggests a horizontal PBR model with a water depth of 0.5 m placed in coastal areas, completely isolated from other natural environments and ecosystems. A low level of control is suggested for these partially natural areas, involving only recurrent inoculations with nitrogen-fixing species, aeration, and control of key nutrients (N, P, and Fe). Proper management of the generated biomass, whether through blocking or re-oxidation, would be crucial for maintaining the carbon cycle in a balanced state suitable for the stability of the biosphere.  
Conceptualization: B.Z. and G.Z. Visualization: B.Z. Formal analysis: B.Z. Writing--original draft: B.Z. Writing--review & editing: B.Z., L.M., M.-J.B. and J.E. All authors have read and agreed to the published version of the manuscript. This research received no external funding. We would like to thank Global BioTech S.L. (Spain) for their support and assistance in the preparation of this literature review. The authors declare no conflicts of interest.
# Recent Advances in the Growth and Characterizations of SILAR-Deposited Thin Films
## 5 Metal Oxide Thin Films
### Cadmium Oxide Films  
Cadmium acetate and hydrogen peroxide (H\({}_{2}\)O\({}_{2}\)) were used to produce adherent and dark yellowish color films [143]. The films deposited in higher molarity (0.06 M) showed bigger grain sizes, excellent crystallinity, high absorbance values, and compact distribution over the surface of the substrates compared to lower molarity (0.03 M). The cadmium chloride was used to prepare thin films on microscopic glass slides [144] at room temperature under various deposition cycles (40 cycles to 120 cycles); the thin film formations could be highlighted in Equations (48)-(51).  
\[\mathrm{CdCl_{2}+2 NaOH\to Cd(OH)}_{2}+2 NaCl \tag{48}\]  
\[\mathrm{Cd(OH)}_{2}+\mathrm{NaOH\to H_{2}O+H^{+}+NaCdO_{2}^{-}} \tag{49}\]  
\[\mathrm{H^{+}+NaCdO_{2}^{-}+H_{2}O\to NaOH+Cd(OH)}_{2} \tag{50}\]  
\[\mathrm{Cd(OH)}_{2}+\mathrm{heat\to CdO+H_{2}O} \tag{51}\]  
The XRD analysis showed that the highest intensities and biggest crystallize size (13.59 nm) could be observed when the deposition cycle was 80 cycles. The spongy cluster and band gap energy were reduced; however, absorbance increased, with the increasing number of deposition cycles. The annealing effect (623 K, 120 min, air atmosphere) on the properties of the thin films was studied by [PERSON] and co-workers [145]. A lower band gap (3.3 eV), smaller crystallite size (20-30 nm), lower electrical resistivity, and uniform coverage of the substrate surface could be seen in the as-deposited films when compared to annealed films. Cadmium acetate (0.1 M and 0.05 M) and ammonium hydroxide were used to synthesize thin films on glass slides [146]. The crystallize size (24.05 to 42.09 nm), thickness (410 to 424 nm), and band gap (2.17 to 2.21 eV) increased, but the strain (2.255 to 1.291 \(\times\) 10\({}^{-3}\)) and dislocation density (17.277 to 5.643 \(\times\) 10\({}^{14}\)) reduced with the increase in the solution concentration.
# Protective Effects Induced by a Hydroalcoholic _Allium sativum_ Extract in Isolated Mouse Heart
## 3 Results and Discussion
### GC-MS Analysis of VOC Fraction
#### 3.1.2 Garlic Hydroalcoholic Extract  
The analysis of the hydroalcoholic extract basically revealed the exclusive presence of the following two classes of compounds: fatty acid esters (FAE: 22.16%) and long-chain n-alkanes (LA: 53.47%), besides a certain number of unknown compounds (Table 3). The most representative FAE are methyl and ethyl linoleic (6.87 and 4.76%, respectively).
# Secure Image Transmission Using Multilevel Chaotic Encryption and Video Steganography
## 5 Results and Testing
### Image Encryption Result
#### 5.2.5 Correlation Coefficient  
The measurement of the correlation coefficient r is computed for the range and trend of the linear set of two randomized variables. If two variables are correlated, the value of the correlation coefficient is close to 1. If the coefficient is near 0, the two variables are correlated. The value of the coefficient \(r\) can be calculated as follows [47]:  
\[\mathbf{r}=\frac{\Sigma_{i}(x_{i}-x_{m})(y_{i}-y_{m})}{\sqrt[c]{\Sigma_{i}(x_{i}-x_ {m})^{2}}\sqrt[]{\Sigma_{i}(y_{i}-y_{m})^{2}}}\]  
Our system uses a multilevel chaotic system and AES algorithm, which results in a greater correlation coefficient, as shown in Table 7.
# The Machine-to-Everything (M2X) Economy: Business Enactments, Collaborations, and e-Goverance
## 5 Discussion
### Trust  
Blockchains are trust engines in an inherently trustless M2X Economy collaboration context. Blockchain technology promises to secure the M2X ecosystem where the management of large and distributed datasets in a secure way is essential. Still, the expected performance and scalability of existing blockchains is currently not compatible for a M2X context [56]. Consequently, new types of blockchains with novel consensus and validation algorithms are required for the large number of securely connected smart autonomous devices that interact with other machines, humans, and infrastructure.  
Since M2X ecosystems are a source of large, unstructured data sets that must be combined and understood to extract intelligence with advanced analytic for actionable decision-making, it is our contention that trust management is only possible with novel blockchain technology of high scalability and performance. For example, the use of blockchains in a M2X ecosystem involves many devices that have low storage capacity and computing power. Since these devices cannot maintain a blockchain of many gigabytes, novel sharding management for blockchain parts to and from devices is required to overcome storage and computing-power limitations [1; 57].
## 3 Results and Discussion
### Estimation of the Fibre Orientation  
According to the procedure described in Section 2.4, the fibre orientation inside the specimen was calculated. For the electrode array with angular distances of 90\({}^{\circ}\), the orientation in two orthogonal horizontal directions and the vertical direction was possible, while for the setup with angular distances of 180\({}^{\circ}\), it was only possible to measure one horizontal direction and it was assumed that the other horizontal direction would show the same value.  
It was presumed that SFRC compacted by a vibrating table would show a higher number of fibres oriented in the horizontal direction than the vertical and, as Figure 12 shows, the calculations absolutely support this expectation for an alternating current frequency of 1 kHz, except for the specimen with 80 kg/m\({}^{3}\) of fibres and an electrode array with angular distances of 90\({}^{\circ}\). Changes in the frequency did not lead to any important changes in the results. For most of the specimens, at a specimen age of 9 days, the calculation orientation factor in the horizontal direction was lower than that in the vertical direction. For the specimens with an electrode array of electrodes with angular distances of 90\({}^{\circ}\) it was observed that one horizontal direction always provided the highest calculated orientation and the other horizontal direction provided the lowest, while the vertical direction had an orientation factor of about 30-35%. For the specimens with angular distances of 180\({}^{\circ}\), high orientation factors for the horizontal direction of more than 35% were calculated.  
Figure 11: Calculated fibre content of the concrete specimens with different electrode arrays depending on fibre content and frequency of the alternating current at a specimen age of 9 days.  
This could confirm the expectations but could also be a random result, because only one horizontal direction was investigated and, as the results of the investigations with more electrodes show, one horizontal direction could have very high orientation factors.  
Comparing the results of the same specimens investigated at a concrete age of only 38 days, there were only small differences (see Figure A7 in Appendix A). It was concluded that the ongoing hydration process and thus, the pore structure in different parts of the specimen, would differ slightly based on small variations in the local water and cement content and so, lead to small variations in the calculated orientations for different concrete ages. While for the calculation of the fibre content, there was almost no influence of aging since the whole specimen was considered in its entirety for the calculation of the fibre content.
# Study on the Wellbore Flow for Carbon Dioxide Fracturing
###### Abstract  
CO\({}_{2}\) fracturing has unparalleled advantages in the reservoir reform which can significantly improve oil and gas recovery in unconventional oil and gas resources. The wellbore flow behavior is one of the fundamental issues of CO\({}_{2}\) fracturing. A model of flow and heat transfer in the wellbore is developed in this paper, and wellbore temperature and pressure are coupled using an iterative method. The model is validated by measured data from the field. Wellbore pressure, temperature, CO\({}_{2}\) properties, and phase state along depth are observed and a sensitivity study is conducted to analyze the controlling factors for CO\({}_{2}\) fracturing. Results show that displacement is the key factor affecting CO\({}_{2}\) flow behavior in the wellbore and injection temperature has greater influence on CO\({}_{2}\) flow behavior than injection pressure and geothermal gradient; however, excess injection temperature brings enormous cost in wellbore pressure. CO\({}_{2}\) phase state is related to working parameters and it tends to stay in liquid state under higher displacement, which is matched with field tests. This study can help optimize the working parameters of CO\({}_{2}\) fracturing.  
Carbon dioxide fracturing; Wellbore flow model; Heat transfer; Phase state; Sensitivity analyses +
Footnote †: journal: Applied Physics Letters
## 4 Experiments
### Ablation Study
#### 4.4.1 Ablation of Network Structure  
Throughout the present investigation, we proposed a semi-supervised arrangement that utilizes both supervised and unsupervised branches to jointly train the model with synthetic and real training images. The network structure of the two branches is identical and combines the impairment of operations, both monitored and unattended to constrain the network training. To confirm the efficacy of the overseen and unattended branch structure, we removed the unsupervised branch and conducted an experiment using only the synthetic dataset for training. The network was optimized solely on the labeled synthetic data, without utilizing the information from real data. Table 1 displays the outcomes of the experiment. \"Input\" refers to the untreated real rainy images, \"MSWT-DN\" alludes to the trained model only on the synthetic Rain1200 dataset, and \"MSWT-SSIDA\" refers to the trained model using the proposed method on both Rain1200 and real data.  
Figure 11: Examples from the RealRain real dataset.  
Figure 9: Examples from the Rain1200 synthetic dataset.  
In Table 1, by comparing the NIQE and PIQE values, it can be observed that removing the unsupervised branch significantly degraded the deraining performance, particularly when handling actual data, where the generalization ability was poor. This illustrates the efficacy of the proposed semi-supervised approach.
## 3 Results and Discussion  
### Nanosecond Pulsed Corona Discharge Characteristics  
A typical voltage pulse is presented in Figure 2. It does not depend on the reactor geometry, condition of the dielectric barrier, presence of catalysts, or gas composition. Its half-measured width is 9 ns, which ensures fast energization of electrons and inhibits their thermalization. This way, energy delivered to the discharge is not wasted in gas heating but consumed by electrons and further the production of radicals via electron-induced dissociation of molecules.  
Current pulses are influenced strongly by the discharge environment. When the internal ceramic barrier is impregnated with catalytic material, the current pulse is much higher compared to clean ceramics (Figure 3). This difference was expected, since a catalyst is formed by metals conducting an electric current and inhibiting the effect of the ceramic barrier. It also strongly influences the discharge energy, resulting in higher values when treating the gas mixture in the reactor with the catalyst (Figure 4). As can be seen in Figure 4, the pulse energy also grows with the pulse repetition rate. This is the result of remaining charged species in gas space between two consecutive pulses. At high pulse repetition rate, they do not have sufficient time to diffuse and recombine. Moreover, each pulse increase concentration of long-living metastable species formed in the process of electron-impact excitation, which is beneficial for the multi-step ionization for the next pulse.  
Figure 2: Typical voltage pulse from NPG-15/2000 pulse generator.