esa-sceva/satcom-chunk-collection huggingface dataset:
# A Comparative Analysis of Wi-Fi Offloading and Cooperation in Small-Cell Network
## 2 Related Work
### Contribution  
SBS cooperation is a vital technology being considered for 5G and B5G in the context of cell-free communication. Wi-Fi offloading is also being actively explored for 5G and B5G to complement cellular network throughput and coverage. Our study simultaneously considers both technologies for average data rate enhancement while considering different network conditions, which has not been considered in the previous studies. The specific contributions of this paper are as follows.  
* We formulate a resource allocation problem for Wi-Fi offloading and SBS cooperation for co-located Wi-Fi access points (APs) and SBSs. In the case of Wi-Fi offloading, allocation of leftover capacity from the Wi-Fi network to the LTE UEs is considered to be an optimization variable, whereas for SBS cooperation the association with multiple SBSs is considered along with OFDM resource block allocation and power allocation problem.
* We propose heuristic algorithms based on sequential allocation of resources for both offloading and cooperation scenarios. The heuristic algorithms are called sequential cooperative rate enhancement (SCRE) and sequential offloading rate enhancement (SORE) for small-cell cooperation and Wi-Fi offloading, respectively.
* We present a comparative analysis between SCRE and SORE for maximizing the average user data rate depending on the network conditions. We conclude from the results that cooperation (SCRE) is more beneficial in less dense network where several users are at cell edge and the average data rate requirement is high. However, Wi-Fi offloading (SORE) is more advantageous when the density of cellular UEs is higher and more UEs are present within Wi-Fi range and there is also sufficient Wi-Fi leftover capacity available.
## 4 Discussion
fNIRS primarily measures hemodynamic responses in the cortical surface of the brain, as near-infrared light cannot penetrate deeply into brain tissue. This means that limited sensitivity to activity occurring in deeper brain structures is evident, such as the hippocampus or thalamus. fNIRS also relies on hemodynamic responses, which are slower than the actual neuronal activity they reflect. Thus, a delay between the neuronal event and its detection is expected, limiting its temporal resolution. Variations in skull thickness can also affect the absorption and scattering of near-infrared light, potentially leading to differences in signal quality and reliability. Nevertheless, the acquired data followed the same protocol for all participants, which minimizes the effect of all the above-mentioned limitations. Caution must be taken when extrapolating the present findings to clinical implications. The immediate effects only allow physiological inferences, and longer prospective studies would be more feasible to assess the symptoms outcomes. Finally, conventional tDCS was chosen for this study due to its wider availability in clinical settings. Other devices and montages, such as HD-tDCS or individualized HD-tDCS, may produce different results.
## 10 Properties of Foamed Lightweight High-Performance Phosphogypsum-Based Ternary System Binder  
The potential of phosphogypsum (PG) as secondary raw material in construction industry is high if compared to other raw materials from the point of view of availability, total energy consumption, and CO\({}_{2}\) emissions created during material processing. This work [9] investigates a green hydraulic ternary system binder based on waste phosphogypsum (PG) for the development of sustainable high-performance construction materials. Moreover, a simple, reproducible, and low-cost manufacture is followed by reaching PG utilization up to 50 wt.% of the binder. Commercial gypsum plaster was used for comparison. High-performance binder was obtained, and on a basis of it, foamed lightweight material was developed. Low water-binder ratio mixture compositions were prepared. Binder paste, mortar, and foamed binder were used for sample preparation. Chemical, mineralogical composition, and performance of the binder were evaluated. Results indicate that the used waste may be successfully employed to produce high-performance binder pastes and even mortars with a compression strength up to 90 MPa. With the use of foaming agent, lightweight (370-700 kg/m\({}^{3}\)) foam concrete was produced with a thermal conductivity from 0.086 to 0.153 W/mK. Water tightness (softening coefficient) of such foamed material was 0.5-0.64. The proposed approach represents a viable solution to reduce the environmental footprint associated with waste disposal.  
Effect of Fly Ash as Cement Replacement on Chloride Diffusion, Chloride Binding Capacity, and Micro-Properties of Concrete in a Water soaking Environment  
This paper [10] experimentally studies the effects of fly ash on the diffusion, bonding, and micro-properties of chloride penetration in concrete in a water soaking environment based on the natural diffusion law. Different fly ash replacement ratio of cement in normal concrete was investigated. The effect of fly ash on chloride transportation, diffusion, coefficient, free chloride content, and binding chloride content were quantified, and the concrete porosity and microstructure were reported through mercury intrusion perimetry and scanning electron microscopy, respectively. It was concluded from the test results that fly ash particles and hydration products (filling and pozzolanic effects) led to the densification of microstructures in concrete. The addition of fly ash greatly reduced the deposition of chloride ions. The chloride ion diffusion coefficient considerably decreased with increasing fly ash replacement, and fly ash benefits the binding of chloride in concrete. Additionally, a new equation is proposed to predict chloride-binding capacity based on the test results.
# Floor Heave Mechanism and Anti-Slide Piles Control Technology in Deep and Large-Span Chamber
## 2 Discussion on the Floor Heave Mechanism in Deep Chambers
### Ultimate Bearing Capacity of the Floor in Deep and Large-Span Chambers  
From Figure 1, the normal stress of the floor \(\sigma_{n}\) is equal to supporting resistance \(p_{s}\) and shear stress \(\tau_{n}\) is always zero on the BE boundary, for \(\Delta\)BDE is a uniform stress zone. Therefore, mean stress and its included angle with the x-axis of any point within \(\Delta\)BDE are shown as Equation (1):  
\[p_{\rm D}=\frac{p_{s}+c\cot\varphi}{1-\sin\varphi},\theta_{D}=\frac{\pi}{4}- \frac{\varphi}{2} \tag{1}\]  
where \(c\) and \(\varphi\) are the cohesion and internal friction angle of floor rock, respectively.  
Similarly, according to assumptions, we derive \(\sigma_{n}=q_{0}\) and \(\tau_{n}=0\) on the AB boundary, so the following equations in \(\Delta\)ACB can be obtained:  
\[p_{\rm C}=\frac{q_{0}+c\cot\varphi}{1+\sin\varphi},\theta_{\rm C}=\frac{3\pi} {4}-\frac{\varphi}{2} \tag{2}\]  
The stress distribution in \(\Delta\)BCD is a kind of degenerate Riemann problem [27]. According to geotechnical plastic mechanics and the properties of the slip line, the equation between mean stress and its included angle on \(\beta\) lines can be simplified as:  
\[\ln p_{\rm C}+2\theta_{\rm C}\tan\varphi=\ln p_{\rm D}+2\theta_{\rm D}\tan\varphi \tag{3}\]  
\(q_{0}\) is the ultimate bearing capacity of the deep and large-span chamber and can be expressed by Equations (1) and (2):  
\[q_{0}=(p_{s}+c\cot\varphi)\exp(\pi qg\varphi)tg^{2}(\frac{\pi}{4}+\frac{ \varphi}{2})-c\cot\varphi \tag{4}\]  
The contribution of support resistance \(p_{s}\) to the bearing capacity of the floor can be derived from Equation (4):  
\[q_{s}=p_{s}\exp(\pi qg\varphi)tg^{2}(\frac{\pi}{4}+\frac{\varphi}{2}) \tag{5}\]  
When the stress from the roof and sides reaches or exceeds \(q_{0}\), the floor rock enters into plastic flow state, which results in continuous deformation.
## 3 DC-Side Capacitance Analysis  
### Effect of DC-Side Capacitance on Phase between Phases  
Simulation software was used to simulate the split-capacitor three-phase four-wire inverter. An analysis of the experimental results shows that the three-closed-loop control keeps the amplitude of the three-phase output voltage stable, and the variation in the capacitance on the DC-side causes deviations between phases. Through the Cftool toolbox in MATLAB 2019B, the capacitance of the DC-side capacitor and the phase of the output voltage are fitted as a function, and thus, the DC-side capacitance is obtained as a function of the phase between each phase, using the parameters in Table 1 for simulation.  
After fitting, it can be obtained that the DC-side capacitance is related to the phase of phase AB, as shown in Equation (5), and its function curve is shown in Figure 8.  
\[f_{AB}(x)=\frac{114.2\text{x}^{3}+119000\text{x}^{2}+850.3\text{x}+48.95}{ \text{x}^{3}+793\text{x}^{2}+21150\text{x}-5232} \tag{5}\]  
\begin{table}
\begin{tabular}{l l} \hline \hline
**Parameters** & **Value** \\ \hline DC-side voltage \(U_{\text{dc}}\) & 300 V \\ Load phase voltage \(U_{\text{an}}\), \(U_{\text{bn}}\) and \(U_{\text{cn}}\) & (85) 120 V \\ Filter inductance \(L\) & 2 mH \\ Filter capacitor \(C\) & 10 \(\mu\)F \\ Three-phase load \(R_{\text{a}}\), \(R_{\text{b}}\) and \(R_{\text{c}}\) & 10 \(\Omega\), 20 \(\Omega\), 10 \(\Omega\) \\ Load voltage frequency \(f\) & 50 Hz \\ \hline \hline \end{tabular}
\end{table}
Table 1: Simulation model parameters.  
Figure 8: Phase function curve between the DC-side capacitance and AB phase.  
Figure 7: Voltage RMS outer loop control block diagram.  
The DC-side capacitance is related to the phase between the BC phases as a function of Equation (6), and its function curve is shown in Figure 9.  
\[f_{\rm BC}(x)=\frac{125.2\rm x^{3}+5005\rm x^{2}+167.6\rm x+2.393}{\rm x^{3}+214.5 \rm x^{2}-12550\rm x-129.5} \tag{6}\]  
The DC-side capacitance is related to the phase between the CA phases as a function of Equation (7), and its function curve is shown in Figure 10.  
\[f_{CA}(x)=\frac{117.8\rm x^{3}-12810\rm x^{2}-11.21\rm x-2.238}{\rm x^{3}-153.7 \rm x^{2}+4672\rm x+474.9} \tag{7}\]  
The DC-side capacitance can be designed according to the fitted function curve, and the DC-side capacitance can be selected to meet the system requirements. The calculated capacitance values on the DC-side obtained by this method do not differ significantly from those obtained using the method mentioned below. However, this design method is tedious, computationally intensive and has limitations. In order to obtain the size of the DC-side capacitance more easily, the following DC-side capacitance design method is proposed.
# Analysis of LTE-M Adjacent Channel Interference in Rail Transit
### Article Structure  
The rest of this paper is organized as follows. In Section 2, the interference principle of a LTE-M at adjacent frequency bands is introduced in detail. Section 3 analyzes the interference of a LTE-M underground system and provides critical analysis. In Section 4, the interference of a LTE-M ground system is analyzed and simulation results are given. Finally, Section 5 provides the conclusion of this paper.
# A Novel Fractional Sine Chaotic Map and Its Application to Image Encryption and Watermarking
## 5 Analysis of Image Encryption and Decryption
### Statistical Analysis
#### 5.1.1 \(\chi^{2}\) Test  
The uniformity of the histogram obtained for the encrypted images is justified with a \(\chi^{2}\) test. If \(\
u_{\ell}\) denotes the frequency of the observed occurrence and the expected frequency of occurrence is \(\omega_{\ell}\) then the \(\chi^{2}\) value can be obtained from  
\[\chi^{2}=\sum_{\ell=1}^{256}\frac{\
u_{\ell}-\omega_{\ell}}{\omega_{\ell}}, \tag{13}\]  
Figure 10: Binary form of the recovered secret images embedded in the sub-band of level 2 ((**a**) Lena) and sub-band of level 1 ((**b**) Fingerprint) in an objective image of size \(256\times 256\).  
Figure 9: Simulations for peppers image of size \(256\times 256\): (**a**) Watermarked image; (**b**) partially encrypted image; (**c**) inter-block shuffled image; (**d**) encrypted image; (**e**) decrypted image.  
where \(\ell\) is the count of grey levels (256). For a significant level of 0.05, the value of \(\chi^{2}\) is 293. From Tables 2 and 3, the \(\chi^{2}\) value for all the images is clearly less than 293 and ensures the uniform distribution of the histogram.  
Analysis of \(\chi^{2}\) test results illustrates the impact of watermarking images at different levels. From Tables 2 and 3, it is clear that the higher the image watermarking level (Level-3) the smaller the \(\chi^{2}\) value, while watermarking images at a smaller level (Level-2) results in a \(\chi^{2}\) value close to the ideal value. Histogram uniformity is supported with images watermarked deep into the objective image.
## 6 Parasitic Element Analysis
### Parasitic Effects on VM Inverse Filter Realization
By taking into account the VCII parasitic effect on the second-order VM inverse filter realization of Figure 2b, the non-ideal transfer functions of ILP, IHP, and IBP filters are as follows:  
\[2\text{nd}-\text{order ILP}:\qquad G_{v2}(s)\ =\ \frac{G_{0}N(s)}{(sR_{1}C_{x1}+1)(sR_{2}C_{x2}+1) \big{(}sR_{y1}C_{A}+1\big{)}\big{(}sR_{y2}C_{B}+1\big{)}}, \tag{11}\]  
\[2\text{nd}-\text{order IHP}:\qquad G_{v2}(s)\ =\ \frac{G_{0}N(s)}{(s^{2}R_{1}R_{2}C_{1}C_{x 1}+1)(sR_{2}C_{x2}+1)}, \tag{12}\]  
\[2\text{nd}-\text{order IBP}:\qquad G_{v2}(s)\ =\ \frac{G_{0}N(s)}{s(R_{1}C_{1}+R_{2}C_{2})(sR_{1}C_{x1}+1)(sR_{2}C_{x2}+1) \big{(}sR_{y1}C_{A}+1\big{)}}, \tag{13}\]  
where \(C_{xk}\) and \(R_{yk}\) are the parasitic elements \(C_{x}\) and \(R_{y}\) of the \(k\)-th VCII-. Suppose that \(f^{\prime}_{v1}=\frac{1}{2\pi R_{1}C_{x1}}\), \(f^{\prime}_{v1}=\frac{1}{2\pi R_{2}C_{x2}}\), \(f^{\prime}_{v2}=\frac{1}{2\pi R_{y1}C_{x}}\), and \(f^{\prime\prime}_{v1}=\frac{1}{2\pi R_{2}C_{x2}}\), then the operating frequency ranges of the proposed second-order VM ILP, IHP, and IBP filters can be defined as follows:  
\[2\text{nd-order ILP:}\qquad\qquad f<<\min\big{[}f_{v1},f^{\prime\prime}_{v1},f_{v2},f^{\prime\prime}_{v2}\big{]}, \tag{14}\]  
\[2\text{nd-order IHP:}\qquad\qquad f<<\min\big{[}f_{v1},f^{\prime\prime}_{v1} \big{]}, \tag{15}\]  
\[2\text{nd-order IBP:}\qquad\qquad f<<\min\big{[}f^{\prime\prime}_{v1},f^{ \prime\prime}_{v1},f_{v2}\big{]}. \tag{16}\]  
These effects on the realized filter performance can be considerably minimized if the operating frequencies are chosen sufficiently lower than the parasitic pole frequencies of VCII-.
## 2 Background and Related Work  
### Smart Environment  
Smart environments represent the combination of computational technologies, advanced sensing, and communication paradigms, facilitating real-time monitoring, control, and enhancement of diverse environmental parameters. Typically supported by IoT technologies, these environments are generally defined by the widespread presence of interconnected devices and sensors that gather data, allowing smart systems to react automatically to the evolving conditions within the space [9]. The notion of smart environments spans multiple domains including smart buildings, homes, workspace, hospitals, museums, and many others that emphasize improving occupants' comfort, system efficiency, safety, and sustainability.  
For example, in smart homes and workplaces, the environment can automatically adjust lighting, temperature, and security settings to suit the occupants' needs, thereby creating a more comfortable and safe atmosphere. In smart museums, interactive displays and augmented reality initiatives can captivate visitors in innovative manners, tailoring tours to align with individual interests and offering profound insights into the exhibited collections. These technologically enriched environments significantly improve the visitor experience. In smart cities, integrated transportation frameworks can optimize vehicular flow and lessen traffic congestion by leveraging real-time data to manage public transport systems and traffic signals. This approach fosters a more sustainable urban ecosystem that prioritizes the welfare of its inhabitants. Moreover, the recent advancements in machine learning algorithms have enabled smart environments to adapt these changing conditions dynamically. This predictive capability enhances the overall responsiveness and efficiency of energy consumption by optimizing heating ventilation and air conditioning (HVAC) systems.
# Nonthermal Plasma Multi-Reactor Scale-Up Using Pulse Capacitive Power Supplies
## 2 Experimental
### Capacitive Current Limitation Plasma Generator (CCL)  
The main problem faced in the process of developing NTP systems on an industrial scale is the parallel evolution of electric discharges powered by a single main power supply. The parallel connection of several NTP reactors implies their simultaneous operation in the same conditions. This cannot be achieved by directly connecting the reactors in parallel due to the fact that, once an electric discharge is initiated, the voltage at the electrodes decreases and may not be high enough to ensure the initiation of the discharge in the adjacent reactor. This can be achieved by discharge current limitation through passive elements (R, L, and C) other than electrical resistors, which consume electrical power and reduce the efficiency of the multi-reactor system. However, the limitation of the current of discharge using inductive coils requires the same number of inductive coils of relatively high inductance values L, equal to the number of NTP reactors; as a result, they have a considerably large volume and are expensive.  
Figure 3 presents the second schematic for the NTP reactors suitable to scale up the NTP reactors to a multi-reactor array. The second type of power supply uses a capacitive current limitation. The capacitive current limitation, as shown in Figure 3, could be an effective solution to upscale the NTP multi-reactor systems supplied by a regular HV AC transformer, where Tr is an AC transformer with secondary voltage U5 = 10 kV/AC, Rsh = 63 \(\Omega\) is the shunt for current measurement, and the capacitor C = 2 nF. In Figure 3, the NTP in the I-NTP type reactor is generated by an AC electrical discharge. The current is limited to an optimal value by a C capacitor.  
Figure 3: The schematic of capacitive current limitation plasma generator (CCL).  
In Figure 4, the current and voltage waveforms for the CCL plasma generator are presented. The current pulses occur when the voltage of the AC power supply overpasses the NTP reactor voltage breakdown threshold. The voltage of the AC transformer drops and the current pulse discharge stops. After increasing the voltage, another current pulse occurs. In our conditions, a train of pulses per voltage half-period is generated.
## 3 Results
### Biomarker Concentrations
#### 3.3.3 H-FABP  
In patients with severe AS and an sPAP < 40 mmHg, H-FABP was almost undetectable in close temporal relation before and after TAVR (sPAP < 40 mmHg: baseline--0.00 \(\pm\) 0.51 ng/mL, 24 h--0.00 \(\pm\) 1.48 ng/mL, 96 h--0.09 \(\pm\) 1.05 ng/mL). Only at the 3-month follow-up was there a relevant increase (sPAP < 40 mmHg: 3 months--0.34 \(\pm\) 1.41 ng/mL) in the plasma concentration of H-FABP, which increased further at 12 months (sPAP < 40 mmHg: 12 months--0.99 \(\pm\) 1.62 ng/mL). Patients with an sPAP \(\geq\) 40 mmHg in the setting of severe AS recorded a decrease in the plasma concentration of H-FABP 96 h after TAVR (sPAP \(\geq\) 40 mmHg: baseline--1.50 \(\pm\) 2.86 ng/mL, 24 h--1.48 \(\pm\) 2.77 ng/mL, 96 h--0.87 \(\pm\) 3.40 ng/mL; not significant) and then steadily increased after 3 months (sPAP \(\geq\) 40 mmHg: 3 months--1.28 \(\pm\) 2.07 ng/mL) and 12 months (PAP \(\geq\) 40 mmHg: 12 months--2.09 \(\pm\) 1.95 ng/mL).  
The plasma level of H-FABP in severe AS patients with echocardiography proven PH was already at a significantly higher baseline level (baseline: \(p\) = 0.022). Additionally, H-FABP remained at a constant, significantly higher level in contrast to the sPAP < 40 mmHg group (24 h: \(p\) = 0.012; 96 h: \(p\) = 0.037; 3 months: \(p\) = 0.006; 12 months: \(p\) = 0.030).
## 3 Results and Discussion
### Development of the Multistatic UWB IR  
During the study, there was an upgrade applied to the existing UWB IR radar:  
* Designing the optimized antennas for frequencies above 2 GHz (Figures 2 and 3);
* Designing the antenna switch that ensures good isolation between channels (for signals up to 3 GHz in frequency, \(S21>-1.5\) dB when the channel is on, and \(S21<-43\) dB when the channel is off);  
Figure 1: Initial architecture of the model trained using synthetic data.  
* Redesigning the firmware of the existing radar in order to support multistatic radar data flow;
* Designing the human-machine interface software of the upgraded radar.  
The parameters of the upgraded radar are listed in Table 1.  
All the previously listed hardware components were assembled to create the measurement setup (Figure 3). The radar and antenna switch boards were placed below the broadband EM wave absorber foam block in order to reduce interference from the electronics; the foam block also reduced the reflections of the whole measurement setup. The antenna holder base circle is composed from 10 modular, con  
Figure 3: Multistatic UWB IR experimental measurements setup: Tx-transmitting antenna, from Rx0- to Rx3-receiving antennas.  
Figure 2: Measured S11 of the developed wideband antenna.  
plastic sections with locations for antenna insert stands on each section. Such segmented construction allows flexibility in antenna placement so that different radar configurations can be tested easily:  
* Pseudo-monostatic radar, in the case when the receiving antenna is placed next to the transmitting antenna;
* Bistatic radar, in the case when the receiving antenna is not placed next to the transmitting antenna;
* Multistatic radar, in the case when multiple receiving antennas are used.  
The 3D-printed stand for objects under analysis is placed in the center of the circle. Inner diameter of the antenna holders circle is 60 cm; stand with an object is at closest about 25 cm from the antennas. Antenna fixtures along with object stand are raised about 40 cm from the base in order to reduce reflections from it.
###### Abstract  
In this work, a record of 16 channels, with future channel spacing in the telecommunication standardization sector of the International Telecommunications Union G.694.1 (ITU-T G.694.1) for Dense Wavelength Division Multiplexing (DWDM) (i.e., 12.5 GHz), is simulated and tested. This work is done to realize a proposed high capacity DWDM-Passive Optical Network (DWDM-PON) system. These specifications are associated with enhancing the upstream (US) capacity to 2.5 Gb/s over a 25 km Single-Mode Fiber (SMF) transmission and producing a noteworthy average Bit Error Rate (BER) of \(10^{-12}\) during the system's evaluation process. These performance indicators are achieved through design optimization of the cross-seeding Rayleigh Backscattering (RB) elimination technique. This optimization has successfully reduced (compared to the cross-seeding related literature) the simulated DWDM-PON components and maintained an effective Rayleigh Backscattering elimination with the aforementioned system's performance enhancement and capacity enlargement.  
cross seeding; Rayleigh backscattering elimination; dense wavelength division multiplexing; passive optical network +
Footnote †: journal: Applied  
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