esa-sceva/satcom-chunk-collection huggingface dataset:
# Coverage and Rate Analysis for Location-Aware Cross-Tier Cooperation in Two-Tier HetNets
## 2 System Model
### The Signal-To-Interference-Plus-Noise Ratio for a Typical User  
In the setup in Equation (1), given that the serving BS is located at \(x_{i}\in\Phi_{i}\), the received signal power for a typical user located at the origin, \(u\in U_{I}\), can be expressed as:  
\[\sum_{\begin{subarray}{c}k\in\mathcal{K}(l)\\ \text{\emph{desired signal}}\end{subarray}}\frac{\sqrt{P_{k}}h_{x}}{\left\|x _{k}\right\|^{\alpha_{k}/2}}X+\sum_{\begin{subarray}{c}i\\ y_{i}\in\Phi_{i}\backslash\{x_{k}\in\mathcal{K}(l)\}\end{subarray}}^{2}\sum_{ \begin{subarray}{c}y_{i}\in\Phi_{i}\backslash\{x_{k}\in\mathcal{K}(l)\}\\ \text{\emph{inter-cell interference}}\end{subarray}}\frac{\sqrt{P_{i}}h_{y}}{ \left\|y_{i}\right\|^{\alpha_{i}/2}}Y+Z \tag{9}\]  
where \(l\in\{M,in;\ M,out;\ F;\ C\}\), \(h_{x}\) and \(h_{y}\) are Rayleigh-distributed random variables with average unit power, \(X\) and \(Y\) are the data sequences jointly transmitted by the serving and interfering BSs, respectively, and \(Z\sim\mathcal{CN}\left(0,\,\sigma_{2}^{2}\right)\) is a circular-symmetric zero-mean complex Gaussian random variable with variance \(\sigma_{z}^{2}\) to model the additive white Gaussian noise (AWGN) at the receiver. It is also assumed that no CSI (channel state information) is at the BSs. Hence, the received signal-to-interference-plus-noise ratio (SINR) of a typical user located at the origin, \(u\in U_{I}\), is given by:  
\[SINR=1\left(l\in\{M,in;\ M,out;\ F;\ C\}\right)\frac{\left|\sum_{k\in\mathcal{ K}(l)}\sqrt{P_{k}}h_{x}\|x_{k}\|^{-\alpha_{k}/2}\right|^{2}}{\sum_{i=1}^{2}I_{i}+ \sigma_{z}^{2}} \tag{10}\]  
where \(1\left(A\right)\) is the indicator function that takes the value of \(1\) if the event \(A\) is true, and \(I_{i}=P_{i}\sum_{y_{i}\in\Phi_{i}\backslash\{x_{k}\in\mathcal{K}(l)\}}\left|h _{y}\right|^{2}\left\|y_{i}\right\|^{-\alpha_{i}}\) is the cumulative interference from the \(i\)th tier.
## 3 Results and Discussion
### Aging of Samples Due to Storage  
Ageing and hydrophobic recovery of PLA-activated samples were analyzed by evaluation of CA (Table 2) and SFE changes (Figures 9 and 10). The course of changes in the water contact angle of the tested films depends on the type of plasma activation. For argon plasma activation, the changes are close to linear, with WCA increasing with storage time. At the same time, WCA values for BCP and TCL films are close to each other, while for NTSS films they are lower (Table 2). However, for oxygen plasma-activated films, changes are non-monotonic in nature; as a result of storage  
Figure 8: Changes in film gloss due to plasma activation. for 14 days, after an initial slow increase in WCA, suddenly the WCA value increases very significantly, then decreases again. Such a course of changes is less frequently observed, but is consistent with observations made by other researchers [24; 68; 69; 70]. The aging of the surface and the disappearance of hydrophilic properties of films modified with argon plasma are probably caused by the reorientation of the polar groups into the bulk polymer. By comparison, for oxygen-modified materials, it can be expected that, in addition to the aforementioned process of the reorientation of the polar groups, the mobility of small polymer chain segments into the matrix also occurs. Intense oxidation leads to the formation of small fragments loosely bound to the surface, and such a surface is more susceptible to aging precisely because of the migration of small fragments into the bulk. In addition to post-plasma rearrangement processes, storage can lead to migration and diffusion of low molecular weight additives that were introduced into the polymer, from the bulk towards the surface, creating a weak boundary layer [20]. It can be speculated that such processes are responsible for the changes in the form of a significant increase and subsequent decrease in the water contact angle between the 14 th and 30 th days of sample storage. Moreover, it can be speculated that the non-polar environment in which the samples were stored and the average ambient humidity (RH 50%) further induced rather than inhibited the aging processes taking place [71]. Analyzing the obtained data, it can be concluded that the type of film has a significant effect on the course of hydrophobic recovery. Moreover, for NTSS and TCL films, the value of WCA after storage for 60 days was almost the same for samples activated with different types of plasma, despite previous significant changes in these values. Analyzing CA with diiodomethane, it can be seen that as the storage time increases (for periods of 30 and 60 days), the values, regardless of the type of film and gas used for plasma activation, begin to become increasingly similar to each other (Table 2). In addition, the smallest changes in CA with diiodomethane during storage are observed for BCP film, while the largest changes are observed for TCL film.
###### Abstract  
The interference of a two-cell two-hop multi-input-multi-output (MIMO) heterogeneous network where the cell-center user (CCU) coexists with the cell-edge user (CEU) is complex to characterize and costly to suppress. In downlink, the CEU is assumed to be served by a half-duplex relay with amplify-and-forward mode. To suppress the intra-cell and inter-cell interference, a cross time slot partial interference alignment (TPIA) scheme, which aligns the interference terms generated in different sub-time slots to the same subspace, is proposed in this paper. Furthermore, the feasibility condition of antenna configuration is analyzed. Simulation results indicate that the TPIA scheme outperforms other existing conventional techniques in achievable sum degrees of freedom and sum-rate performance.  
interference alignment; cross time slot; relay; two-cell; MIMO 1  
A cross time slot; frequency division multiplexing; multiple access
## 3 Simulation Setup  
Figure 2 describes in block diagrams (a) OFDM Tx, (b) OFDM Rx, and (c) a complete simulated setup of a converged 5G mm-wave A-RoF system at 60 GHz designed in the VPI Photonics design suite [47] and used to test the developed algorithms. The OFDM Tx is depicted in Figure 2a, where the data stream is converted from serial to parallel form, creating multiple parallel data streams. This procedure allows the data to be transmitted simultaneously on various subcarriers. Next, the inverse fast Fourier transform (IFFT) is performed, transforming a complex frequency domain signal into a time domain signal, which is then used to modulate the signal onto orthogonal subcarriers in the digital domain. A cyclic prefix (CP), introducing a guard time interval between symbols, is used to minimize  
intersymbol interference (ISI). The parallel data streams are converted back to serial, and the output signal through a digital-to-analog converter (DAC) is transformed into an analog signal.  
Using a Mach-Zehnder modulator (MZM), the signal is modulated, while an optical bandpass filter can be used to suppress the amplified spontaneous emission (ASE) noise (Figure 2c). The produced 60 GHz mm-wave analog signal [31; 32] is transmitted through an SSMF of different lengths with a 16 ps/nm/km dispersion, while a photodiode is utilized to capture the optical signal, which is then converted into electrical and fed into an OFDM receiver for subcarrier recovery, as shown in Figure 2c. The electrical signal undergoes down-conversion to a baseband signal, followed by an OFDM decoder, as shown in Figure 2b. The distorted electrical symbols from the OFDM constellations are captured and subsequently equalized in MATLAB using the different algorithms. Table 3 provides a summary of the simulation parameters used in this work.  
\begin{table}
\begin{tabular}{l l} \hline \hline
**Link Design Components** & **Values** \\ \hline Carrier Frequency & 7.5 GHz \\ \hline Laser CW & 10 dBm \\ \hline Wavelength & 1553 nm \\ \hline RIN & \(-\)130 dB/Hz \\ \hline Radio Frequency & 60 GHz mm-wave \\ \hline Bit Rate Default & 40 Gbit/s \\ \hline \hline \end{tabular}
\end{table}
Table 3: Simulation parameters.  
Figure 2: Block diagrams (**a**) OFDM Tx, (**b**) OFDM Rx, and (**c**) a converged OFDM-based 5G mm-wave A-RoF system at 60 GHz.
## 3 Implementation of the Soft Sensor in the Time Domain
### Test Cases  
The following test cases are investigated to obtain a range of validity for the derived method. The volumetric flow rate computed by the soft sensor is validated against the results provided by the software DSHplus, which solves the partial differential equations for the conservation of momentum and mass with a finite difference scheme [48]. Furthermore, a soft sensor only utilizing the law of HP, representing a commonly used approach for pressure-based soft sensors, is investigated to underline the benefit of incorporating the unsteady flow rate behavior. The simulation model in DSHplus consists of a pipe with varying pressure inlet boundary conditions. Four different types of pressure signals are investigated: sine, sum of sines, sawtooth, and step signals. In Table 1, the overall simulation parameters are displayed.  
The comparison is performed for a pipe with standard hydraulic oil HLP46 and a set diameter and length. Based on these values, the hydraulic resistance can be computed. The change between the different presented simulations lies in the investigated pressure boundary conditions. Table 2 displays the various types of investigated pressure boundary conditions. The pressure outlet is fixed; thus, only the pressure inlet varies.  
The first investigated pressure signals are sine waves at different frequencies (1, 100, and 1000 Hz) to validate the analytical model for low and high frequencies. When a pump delivers oil into a system, it inevitably generates pressure pulsations. These pulsations occur at a fundamental frequency determined by the number of chambers in the pump and its rotational speed. In addition, integer multiples of this fundamental frequency are also excited. To replicate this behavior, the pressure boundary condition for the simulations is defined as a sum of sine waves oscillating at 1 Hz, 10 Hz, 20 Hz, and 40 Hz, as well as 10 Hz, 100 Hz, 200 Hz, and 400 Hz. Therefore, the second test case consists of two signals composed of sums of sines. Thirdly, a sawtooth function was examined as an example of a highly instationary boundary condition. Lastly, a step function was analyzed because this work focuses on the equation's ability to calculate transient flow rates in a pipe. To validate its performance under such conditions, a step function increase in the pressure boundary condition will be examined. A step function represents the most unsteady case possible, theoretically involving a Fourier approximation as a sum of frequencies up to infinity.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Name** & **Variable** & **Unit** & **Value** \\ \hline Kinematic Viscosity & \(\
u\) & m\({}^{2}\)/s & \(46\times 10^{-6}\) \\ Fluid Density & \(\rho\) & kg/m\({}^{3}\) & 860 \\ Bulk Modulus & \(K\) & Pa & \(14\times 10^{9}\) \\ \hline Diameter of the Pipe & \(D\) & m & \(14\times 10^{-3}\) \\ Length of the Pipe & \(L\) & m & 1.5 \\ Hydraulic Resistance & \(R_{\rm H}\) & Pa/(m\({}^{3}\)/s) & \(6.294\times 10^{7}\) \\ \hline \hline \end{tabular}
\end{table}
Table 1: Parameter set in the simulation for each test case.
# Personalized Prevention in Mercury-Induced Amyotrophic Lateral Sclerosis: A Case Report
## 1 Introduction  
Mercury (Hg) is a naturally occurring toxic heavy metal [1, 2] and a global pollutant [3]. Occupational exposure to elemental inorganic mercury may cause neurological and other adverse effects in exposed workers [4, 5, 6]. Even if its neurotoxic effects have been known for more than 300 years [7], occupational exposure may still be relevant in certain activities such as mining and metal working [8, 9, 10], production and waste of fluorescent lamps [11, 12] and incinerators [13, 14], recycling [15, 16], concrete processing [17], battery production [18], thermometer and precision instrument manufacturing [19], dental care [20], and other industrial activities. Chlor-alkali plantshave been extensively studied over the past 60 years for being at the origin of the ecological disaster of Minamata [21] and for neurological pathologies in exposed workers [22; 23; 24; 25; 26; 27; 28; 29; 30; 31].  
Trends in production and sales of Hg are rapidly increasing according to high global Hg demands (Global Chemicals Outlook II, 2019) [32]; consequently, the number of exposed workers is increasing. Occupational risk prevention is based on the adoption of environmental prevention measures, good work practices [33], and biological monitoring of workers. Mercury in urine (U-Hg) is commonly used to indicate exposure in occupational cohorts [34]. The reference values for U-Hg have been progressively reduced over years; for example, the American Conference of Governmental Industrial Hygienists (ACGIH(r)) has reduced the Biological Exposure Index (BEI(r)) for U-Hg from 35 (2007) to 20 ug/g (2017) [35].  
A systematic review of neurotoxicity studies in Hg-exposed workers confirmed dose-relatedness of objective neurological effects, including tremor, impaired coordination, abnormal reflexes, and reduced performance on neurobehavioral tests of manual dexterity and motor speed [36]. The metal mainly affects the central nervous system and is expressed in typical motor neuron diseases (MNDs). It has been long known that MNDs have a polyfactorial pathogenesis, and environmental influence has been associated with sporadic forms of amyotrophic lateral sclerosis (ALS), which is the most common MND in adults [37]. Moreover, huge differences in the onset and severity of neurological symptoms in individuals with a comparable level of exposure to Hg have been reported. This points up the role of the underlying genetic factors that may modify Hg uptake, biotransformation, distribution, and elimination, and, as a result, the effective dose, i.e., the dose that produces a biological response [38]. Furthermore, through the years, several epigenetic and genetic characteristics have been associated with Hg neurotoxicity [39].  
In this short paper, we reported the case of a worker exposed to Hg in a chlor-alkali plant, who presented several episodes of work-related neurotoxicity and, finally, developed ALS. Genetic tests showed that he had a TANK-binding kinase 1 (TBK1) mutation.
# A Novel Resource Allocation Scheme in NOMA-Based Cellular Network with D2D Communications
## 4 Numerical Results and Discussions
### Convergence of the Proposed Algorithm  
The cumulative distribution function (CDF) versus the number of searching in JUPLA is shown in Figure 7. The results in Figure 7 are averaged over 10,000 independent adaptation processes which involve different numbers of users from 20 to 80 on 10 SCs. It can be observed that with \(\Delta=0.15\) the proposed joint resource allocation algorithm has a fast converge rate in 1000 iterations for all considered numbers of users. As the number of users decreases, the convergence rate slows down.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline Cellular radius & 450 m \\ Maximum distance between D2D pairs & 75 m \\ Total bandwidth & 2.0 MHz \\ Carrier frequency & 2.6 GHz \\ Maximum Transmission power of CU & 21 dBm \\ Maximum transmission power of D2D & 21 dBm \\ Maximum transmission power of BS & 26 dBm \\ Number of CU & 10 \\ Number of D2D pairs & 10 \\ Number of users on each subchannel & 3 \\ SINR threshold of D2D & 1.8 dB \\ SINR threshold of CU & 1.3 dB \\ Noise Spectral density & \(-173\) dBm \\ Path loss constant & 0.01 \\ Path-loss exponent & 3.76 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Propose the simulation parameters of the study.  
Figure 7: CDF of the number of branches in each search process, with \(\Delta=0.15\), which depicts the probability of finding out the solution increases with the growing of the search number.
# Spatial and Temporal Sampling Properties of a Large GNSS-R Satellite Constellation
## 1 Introduction  
The proliferation of smallsats and the small but highly capable scientific sensors on them have ushered in a new era of Earth remote sensing from space. Technology development lifecycles have been shortened, new and improved sensors can reach space more quickly, both launch vehicle and satellite costs have been reduced dramatically, and it is now both possible and affordable to consider flying large constellations of remote sensing instruments [1]. Notably, large constellations of smallsats in low Earth orbit have the potential to significantly improve upon the spatial and temporal sampling densities provided by a single traditional large satellite [2]. The improvement in sampling density with number of spacecraft is generally intuitive--more of them spread out around the globe will tend to sample more places at the same time and to sample the same place more frequently. We consider here the optimization problems of:  
1. Achieving a particular sampling density with the minimum number of satellites;
2. Maximizing the sampling density for a given number of satellites; and
3. Spreading out the samples at each location in time to better resolve diurnal variability and support the initialization of numerical weather prediction models.  
The optimization is performed with respect to specific orbit parameters of the constellation, namely the number and orientation of orbit planes and the number of satellites in each plane. When quantifying the notion of sampling density, it is helpful to consider a specific type and design of remote sensing instrument. Our optimization study is performed with respect to a Global Navigation Satellite System Reflectometry (GNSS-R) sensor. These sensors are the receiver half of a bistatic radar system in which the transmitters are theexisting constellation of navigation satellites, such as GPS and Galileo. Measurements of GNSS signals scattered back into space from the Earth surface contain information about a wide variety of scientifically valuable geophysical surface conditions [3; 4; 5; 6; 7]. The relevant instrument design parameters to be considered are the number of simultaneous GNSS surface reflections observed and the gain and field of view of the antenna through which the observations are made. The former design parameter affects the signal processing complexity and power requirement of the instrument, and the latter parameter affects the size and mass of the antenna. GNSS-R sensors are compatible with smallsats [8; 9] and have been demonstrated to provide improved sampling density in small constellations [10], so are a natural type of measurement to consider for this study.  
The satellite constellation design space being considered here is an extension of the point design used by the NASA CYGNSS mission [11]. Its constellation consists of 8 identical spacecraft spaced roughly equally around a single orbit plane at an altitude of \(\sim\)525 km and an inclination angle of 35\({}^{\circ}\). Each CYGNSS spacecraft carries a GNSS-R sensor capable of measuring 4 simultaneous surface reflections.
# Long-Term and Seasonal Changes in Sources of Urban Atmospheric Particulates in the Western Pacific
###### Abstract  
To reduce atmospheric pollutants, the sources need to be identified. To this end, combustion-derived particulates (P\({}_{\rm c}\)) in atmospheric suspended particulate matter (TSP) in ten Western Pacific cities from 1997 to 2018 were analyzed using the NP method, which we have recently developed. The method separates P\({}_{\rm c}\) into particulates originating from high-temperature (P\({}_{\rm h}\)) and low-temperature (P\({}_{\rm l}\)) combustion sources. Using this method, ten cities in the Asia-Pacific region were separated into three classes. Class 1: commercial cities whose major contributor to P\({}_{\rm c}\) was from vehicles, and which showed lower [P\({}_{\rm c}\)] values with larger [P\({}_{\rm h}\)]/[P\({}_{\rm c}\)] ratios. Sapporo, Kanazawa, Tokyo, Sagamihara (Japan), Shanghai (China), and Busan (Korea) were contained in this class. Class 2: cities whose main source of P\({}_{\rm c}\) was from coal heating, and which showed much higher winter [P\({}_{\rm c}\)] with larger [P\({}_{\rm l}\)]/[P\({}_{\rm c}\)] ratios. Beijing, Shenyang (China), and Vladivostok (Russia) were contained in this class. Class 3: steel manufacturing city which showed lower [P\({}_{\rm c}\)] with larger [P\({}_{\rm l}\)]/[P\({}_{\rm c}\)] ratio. The low [P\({}_{\rm c}\)] appeared to be due to elimination of P\({}_{\rm l}\) from coke oven plants. Only Kitakyushu was contained in this class. This study has elucidated the contribution of sources to urban atmospheric TSP in the Western Pacific that was previously unknown. Overall [P\({}_{\rm c}\)] was decreasing in this region, mainly due to the decreasing contribution of vehicles to P\({}_{\rm c}\), but not due to a decrease in coal combustion.  
combustion-derived particulate; vehicle emission; coal combustion; Western Pacific; NP method +
Footnote †: journal: Medical Physics
## 2 DAB DC/DC Resonant Converter TPS Close Loop Control Scheme
### DAB LCC Resonant Converter Open Loop TPS Control Simulation Analysis
#### 2.6.2 DAB LCC Resonant Converter TPS Control for Unity Power Factor Operation  
Figure 14 shows the PLECS circuit simulation results of inverter/rectifier voltage/current and the receiver winding voltage/current waveforms obtained from TPS open loop control for the same inverter/rectifier phase shift angle \(\beta\)p and \(\beta\)s settings but different inverter-to-rectifier phase shift angle \(\delta\) settings.  
These simulation results show that the inverter-to-rectifier phase shift angle \(\delta\) has a negligible effect on the rectifier AC current waveform. However, it changes the inverter and rectifier power factor angle significantly. The inverter and rectifier operate at unity power factor when the inverter-to-rectifier phase shift angle is around \(\delta\) = 90\({}^{\circ}\).  
In TPS close loop control, the inverter-to-rectifier phase shift angle \(\delta\) should be automatically adjusted to minimize inverter and rectifier reactive power flow to/from LCC resonant circuit.
# GPR55 and GPR119 Receptors Contribute to the Processing of Neuropathic Pain in Rats
###### Abstract  
Orphan G-protein-coupled receptors (GPCR) comprise a large number of receptors which are widely distributed in the nervous system and represent an opportunity to identify new molecular targets in pain medicine. GPR55 and GPR119 are two orphan GPCR receptors whose physiological function is unclear. The aim was to explore the participation of spinal GPR55 and GPR119 in the processing of neuropathic pain in rats. Mechanical allodynia was evaluated using von Frey filaments. Protein localization and modulation were measured by immunohistochemistry and western blotting, respectively. Intrathecal administration of CID16020046 (selective GPR55 antagonist) or AS1269574 (selective GPR119 agonist) produced a dose-dependent antiallodync effect, whereas O1062 (GPR55 agonist) and G-protein antagonist peptide dose-dependently prevented the antiallodync effect of CID16020046 and AS1269574, respectively. Both GPR55 and GPR119 receptors were expressed in spinal cord, dorsal root ganglia and sciatic nerve, but only GPR119 was downregulated after 14 days of spinal nerve ligation. Data suggest that GPR55 and GPR119 participate in the processing of neuropathic pain and could be useful targets to manage neuropathic pain disorders.  
allodynia; GPR55; GPR119; neuropathic pain; spinal nerve ligation Article