esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### TEM and Size Distribution  
Transmission electron microscopy (TEM) image of the AuNPs is presented in Figure 2a. The TEM analysis was performed by placing one drop of the sonicated sample on the carbon-coated copper TEM grid and dried in air for 30 min. The core diameter of the AuNPs was 18.5 nm and semi-spherical [50] and almost uniformly-sized, as shown in Figure 2c. The addition of sodium citrate has made it possible to achieve the homogeneity in size and shape of AuNPs [51; 52]. In addition, the uniformity of nanoparticles may also be related to the high energy and intense power flow generated by ultrasound irradiation during the formation and breakdown of bubbles, which increases the temperature and pressure of the solution. Morphological characterization of AuNPs reveals that the NPs are semi-spherically shaped with smooth geometry. The ultrasonic power is responsible for the formation and collapse of the bubbles, these bubbles produce hot spots, which have intense local temperatures (~5000 K) and pressures (~1000 atm), sometimes identified as a micro-reactors [53]. Moreover, the collapse of the bubble leads to an intense flow of power within the solution. The size of the nanoparticles is therefore formed under crucial conditions through ultrasonic power via the cavitation process.  
Figure 1: XRD pattern of face-centered cubic (fcc) structure gold nanoparticles (AuNPs).  
Figure 2: (**a,b**) (TEM) image with a scale of 50 nm and (**c**) size distribution of AuNPs synthesized at ultrasound output power 17.9 W\(\cdot\)cm\({}^{2}\).
## 3 Proposed Method
### Stability Analysis of Fitted CNR  
Although the original CNR exhibits stability on adjacent days, it is still affected by random noise, especially at the low satellite elevation angle. Thus, the fitted CNR was extracted by adopting a third-order polynomial fitting method to improve the stability of CNR. In addition, in order to evaluate the stability of the fitted CNR with a direct signal, the data sets presented in the above section were still used.  
In Figure 7, the results of fitted CNRs at different stations and satellites on DOY 200 (blue dots) and DOY 201 (red dots), 2021 are demonstrated. From Figure 7, it is obvious that the fitted CNR with a direct signal performs much more consistently than the original CNR. The blue and red lines are almost exactly overlapping each other. The correlation coefficient of the CNRs between them is presented by R. It is obvious that all of the coefficients can reach approximately 0.99, which is a slightly better performance than the original CNR. However, it is worth noting that the bias between them can also be observed, especially for the CNRs for which amplitude was lower than 40
## 1 Introduction
Moreover, deterministic indexes to calculate dispatchability capability were proposed, so as to realize the optimum combination of dispatchable resources, which can improve the dispatchability of EGCS. The major contributions of this paper are as follows. 1. The power flow model of the EGCS is established in this paper. 2. Through analyzing the factors influencing the uncertain performance capability of the system, two kinds of dispatchability evaluation indicators are proposed eventually, and their applicability is testified by simulation. 3. To address the uncertainties in the source and load of EGCS, this paper analyzes the uncertainties of wind farms and photovoltaic plants output through actual data analysis in a certain area. Then, an economic dispatching model of EGCS considering DG output prediction errors is established, and the dispatchability under-expectation penalties is introduced into the objective function. On these foundations, this paper formulates the operation strategy of EGCS to improve the margin of the system. The rest of this paper is organized as follows. In Section 2, an overview of EGCS is first provided. Then, an evaluation index of dispatchability on EGCS is presented in Section 3. This is followed by Section 4, in which the model of operation strategy for EGCS is presented. Eventually, Section 5 provides the case studies and the results from the case studies.
# Pseudorange Measurement Method Based on AIS Signals
## 3 Detective Feature of Timestamp
### Amplitude Characteristics of Timestamp  
When the bit period \(T\) tends to be infinite, the output result that a rising edge of the digital message sequence passes through the Gaussian filter is equivalent to the unit step response of the Gaussian filter.  
It is well known that in a linear system, the unit step response is the integral of the unit impulse response. In addition, since the unit impulse response function of the Gaussian filter is an even function regardless of the value of the parameter \(k\), the following \(\infty\) conclusions can be obtained.  
\[\int_{-\infty}^{+\infty}h(x)dx=1 \tag{7}\]  
Therefore, the unit step response function of the Gaussian filter \(a(t)\) can be expressed as  
\[\begin{array}{ll}a(t)&=\int_{-\infty}^{t}h(x)dx=\int_{-\infty}^{0}h(x)dx+ \int_{0}^{t}h(x)dx\\ &=\frac{1}{2}+\int_{0}^{t}\left(\frac{k}{\sqrt{\pi}}e^{-k^{2}x^{2}}\right)dx= \frac{1}{2}+\frac{1}{\sqrt{\pi}}\int_{0}^{kt}e^{-u^{2}}du\\ &=\frac{1}{2}[1+erf(kt)]\end{array} \tag{8}\]  
On the condition that the parameter \(k\) (defined in Equation (6)) is introduced to Equation (8), we can obtain the relational expression between the unit step response of the Gaussian filter and the parameter \(BT\). When parameter \(BT\) takes different values, we get the corresponding unit step response curve shown in Figure 3a. As seen in the figure, for the Gaussian baseband waveform recovered by the receiver, the median point is the output result of the digital message sequence bit-0-phase that can be treated as the timestamp.
## 6 Typical Application Cases and Empirical Research
### Implementation Effect Assessment  
Before examining specific implementation cases, it is essential to establish a quantitative foundation for understanding the performance benefits achieved by different non-conventional lane types in practice. Table 3 synthesizes the documented performance improvements reported across the reviewed literature, providing empirical evidence of capacity enhancements, delay reductions, and emission benefits observed in field studies and controlled implementations. This comparative analysis demonstrates the practical effectiveness of non-conventional lanes and establishes benchmarks for evaluating implementation success. Scientific effect assessment is an important link in validating theoretical results and guiding engineering practice. Through field data collection and analysis, multiple studies have verified the positive effects of non-conventional lanes. Implementation effect assessment research has verified the positive role of non-conventional lanes in improving traffic efficiency and environmental quality through a large amount of empirical data. Existing assessments mainly focus on short-term effects and local indicators, with relatively insufficient evaluation of long-term benefits and systemic impacts. Future effect assessments should establish a more comprehensive indicator system that not only focuses on traffic operation indicators but also considers multi-dimensional factors such as socioeconomic benefits, user satisfaction, and system reliability. Simultaneously, long-term tracking assessments should be conducted to study the continuity and stability of non-conventional lane effects. Additionally, the standardization of assessment methods should be strengthened by establishing unified assessment frameworks and data collection specifications to make assessment results from different projects and regions comparable.
# Image-Based Dedicated Methods of Night Traffic Visibility Estimation
## 3 Proposed Visibility Estimation Methodology
### Visibility Estimation Based on Laser Atmospheric Transmission Theory  
The theory of laser atmospheric transmission mentioned in Section 2.1 is to obtain the current atmosphere transmissivity by the ratio of the received optical power to the optical power emitted by the laser, and then to obtain the visibility according to Lambert's law. Our laser transmission system uses a multi-point measurement method to obtain the optical power received at different points and obtains multiple sets of atmospheric transmissivity [15], as shown in Figure 2.  
Figure 2: Schematic diagram of multi-point measurement.  
To test the attenuation of the system, the distance between the transmitter and the receiver is set to zero, at which point the laser transmission does not need to pass through the atmosphere. \(T_{0}\) indicates the attenuation of light energy generated by the system (without atmospheric attenuation):  
\[T_{0}=P_{0}-P_{r}(0) \tag{15}\]  
\(P_{0}\) is the emitted power of the laser in the initial state; \(P_{r}(0)\) represents the power received by the receiver at the zero position. At this time, the atmospheric length is zero.  
When the distance between the transmitter and the receiver is 1 cm, the measured value of the receiver is \(T(1)\):  
\[T(1)=P_{0}-P_{r}(1) \tag{16}\]  
\(T(1)\) is the total amount of light attenuation generated by the optical measurement system, including the light attenuation \(T^{\prime}(1)\) caused by the atmosphere and the light attenuation \(T_{0}\) generated by the system:  
\[T(1)=T^{\prime}(1)+T_{0} \tag{17}\]  
Therefore, the actual power emitted by the laser emitter can be considered as \(P_{0}-T_{0}\), at which time the atmospheric transmissivity is the following:  
\[\tau=\frac{P_{r}(1)}{P_{0}-T_{0}}=\frac{P_{r}(1)}{P_{r}(0)} \tag{18}\]  
Suppose that the transmittance of the gas to be tested is uniform and static during the measurement. When the distance between the receiver and the transmitter is \(n\) cm, by analogy, the measured transmittance at the point \(n\) is the following:  
\[\tau=\frac{P_{r}(n)}{P_{r}(0)} \tag{19}\]  
\(P_{r}(n)\) is the power received by the laser receiver at the point \(n\). By moving the laser receiver, \(n\) groups transmitances can be obtained.
## 4 Discussion
### Future Research
#### 4.4.1 Database Creation for Existing Directional Speakers (for Impulse Response Measurements)  
Our results are encouraging and should be validated for a larger size of existing directional speakers. The current study found differences in the results for different speakers. One possible direction for future research could be the creation of a database for different directional speakers concerning their results for acoustic measurements compared with a dodecahedron speaker. The database will be useful for estimating the expected results when using a conventional speaker for acoustic measurements. The database could also include high gain one-way speaker designs, which because of the similar directivity characteristics with the dodecahedron speaker, could also possibly provide excellent results.
# Quantum Leap from Gold and Silver to Aluminum Nanoplasmonics for Enhanced Biomedical Applications
###### Abstract  
Nanotechnology has been used in many biosensing and medical applications, in the form of noble metal (gold and silver) nanoparticles and nanostructured substrates. However, the translational clinical and industrial applications still need improvements of the efficiency, selectivity, cost, toxicity, reproducibility, and morphological control at the nanoscale level. In this review, we highlight the recent progress that has been made in the replacement of expensive gold and silver metals with the less expensive aluminum. In addition to low cost, other advantages of the aluminum plasmonic nanostructures include a broad spectral range from deep UV to near IR, providing additional signal enhancement and treatment mechanisms. New synergistic treatments of bacterial infections, cancer, and coronaviruses are envisioned. Coupling with gain media and quantum optical effects improve the performance of the aluminum nanostructures beyond gold and silver.  
aluminum plasmonics; UV; photothermal therapy; hot electron; cancer; bacteria +
Footnote †: journal: Medical Engineering, University of South Florida, Tampa, FL 33620, USA; [EMAIL_ADDRESS] 1
# Forecasting Taxi Demands Using Generative Adversarial Networks with Multi-Source Data
## 4 Methodology
### Raw Data  
#### 4.1.1 Taxi GPS Data  
The dataset used in this paper contains temporally ordered location records collected from 9124 GPS-enabled taxis during 91 days (historical GPS dataset of September, October, and November in 2013) of the city of Wuhan, China.  
The temporal resolution of the dataset is 25 s; therefore, approximately 3500 GPS records for a taxi per a day (24 h) would be collected, and the total volume of the dataset approached 320 million records. The GPS meter triggered information to the taxi data center and contains seven taxi attributes, i.e., taxi (driver) ID, timestamp, longitude, latitude, speed, direction, and taxi status. The detailed description of the taxi attributes is shown in Table 1.
## 3 Analysis of Results
### Elasticity Modulus  
Figure 8 shows the mean values of the elasticity modulus for the different mixes as a function of the percentage of substitution and the type of waste (GCW-D or GCW-GS). The results for the GCW-GS show a slight decrease in the modulus of elasticity with respect to the control concrete. For concrete with GCW-D, the variations are negligible, i.e., 3% for a substitution of 100% GCW-D. In the case of GCW-GS, a greater reduction in the modulus of elasticity was observed, i.e., between 3.5% and 8.5%, depending on the percentage of substitution.  
Overall, the modulus of elasticity tends to decrease with most of the substitute materials used in the studies discussed below. [PERSON] and [PERSON] [36] did not observe significant variations in the modulus of elasticity of concrete when incorporating different types of ash as an alternative to silica powder. For a ratio of 25% fly ash, the variation was less than 6.5%. [PERSON] et al. [13] also observed a slight variation when incorporating waste mining sand (WMS) as an alternative to finest silica sand. For a replacement of 100% WMS, the loss was less than 6%. However, in other studies, the results showed more significant  
Figure 8: Elasticity modulus of UHPFRC for both wastes (GCW-D [14] and GCW-GS).  
Figure 7: Compressive strength of UHPFRC for both wastes (GCW-D [14] and GCW-GS).  
variations. [PERSON] et al. [37] analyzed the influence of using blast furnace slag and fly ash on the properties of reactive powder concrete. A decrease in the modulus of elasticity of 10% and 18% were observed when 30% and 40% of blast furnace slag, respectively, was incorporated. However, [PERSON] et al. [38] observed an increase of between 2% and 3% in the modulus of elasticity of high-performance concrete when using industrial by-products. This was related to a reduction in its porosity.
## 3 Experimental Results and Discussion  
### Distribution of the EMPs in the Time and Frequency Domains  
The time-domain signals of EMPs generated from the laser filaments in air and the laser filaments followed by solid targets were measured (as shown in Figure 2a) using the biconical antenna and 1 GHz oscilloscope. Both these measurements were performed under the same following conditions: laser energy \(E\) = 850 mJ, laser pulse width \(t\) = 30 fs, detection distance \(d\) = 50 cm, and detection angle \(\theta\) = 0 deg. Figure 2b shows the Fourier transform of the corresponding time-domain signals in Figure 2a. It can be seen that: (1) under the experimental parameters, the amplitude of EMPs generated from the laser filament, followed by a 3 mm-thick alloy target, was approximately 5 times larger than  
Figure 1: Schematic diagram of the femtosecond laser filament interacting with a solid target.  
the peak of the EMPs generated from the laser filament only; (2) the EMPs generated from the laser filament in air were weak and mainly located at 0.19 GHz, whereas those generated from the laser filament-Al alloy target interaction were not only boosted nearby 0.19 GHz, but also had several distinct frequency ranges centered at 0.31 GHz and 0.45 GHz; (3) the amplitude of EMPs from laser filamentation-Al target interaction was approximately 6 times stronger than that of EMPs from laser filamentation in the air. The results showed that the EMPs generated from the laser filaments interacting with the aluminum alloy target were significantly stronger than those generated from the laser filaments only; hence, it is necessary to focus on the EMP generation mechanism from the interactions between femtosecond laser filament and solid targets. It should be noted that this experiment was limited by the oscilloscope bandwidth. In future experiments, we will use an oscilloscope with a higher acquisition frequency to detect EMP signals above 1 GHz. In our experiments, the spectral and waveform amplitude measurements were averaged from 10 laser shots at each condition. In addition, we also calculated the statistical fluctuation of the EMP intensity, the statistical fluctuations of spectral amplitude from shot to shot were about 19.4% with laser energy of 850 mJ, detection distance of 50 cm, and frequency at 0.2 GHz.
# Research on Key Technologies of Elastic Satellite Optical Network Based on Optical Service Unit
## 2 Methods  
### OISL-MPLS Packet Switching  
As depicted in Figure 0(a), OISL multi-protocol label switching (OISL-MPLS)-based packet switching splits a block from the transmission frame insertion field of an advanced orbiting system (AOS) standard frame as an extended control field to accomplish AOS frame forwarding based on labels and support multiple types of services [19; 20]. The extended control field comprises a label field and a data communication network (DCN) field. Using the label domain, AOS frame forwarding is developed on label switching routers (LSRs) to replace IP address-based routing forwarding. Multiple types of services are supported, with different types inserted into the _Transfer frame data field_ of the AOS frame for transmission, as illustrated in Figure 0(b).
# Narrowband Internet of Things (NB-IoT):
## 2 Narrowband-IoT Standard and Releases
### Release 14 Enhancements
#### 2.2.1 Improved Positioning Technique  
3 GPP Release 14 introduces an indoor advanced positioning method of observed time difference of arrival (OTDOA) for NB-IoT to enhance UE position measurement of cell identity (CID). In OTDOA method, the UE measures the times of arrival (ToAs) of positioning reference signals (PRSs) received from different transmitters with respect to a reference node's PRS transmission to form the reference signal time difference (RSTD) measurements. In enhanced CID, the measurement requirements include the base station receive (Rx) and transmit (Tx) time difference, reference signal received power (RSRP), and reference signal received quality (RSRQ).
## 4 Results and Analysis
### Model Deployment on Embedded Systems  
We have deployed the optimal stacking ensemble model trained on a balanced dataset on an NVIDIA AGX Orin, a powerful embedded system chip with a maximum computational power of 275 TOPS. Using a socket connection, we established duplex communication between the UAHW and the NVIDIA AGX Orin. The specific computational process involves UAHW computing echo features and transmitting them to the NVIDIA AGX Orin through the socket connection. The NVIDIA AGX Orin computes the predicted results and transmits them back to UAHW. Through testing, the stacking ensemble model has demonstrated accurate predictions with a time of 15 ms, meeting the real-time requirements of UAHWs.
# Reliable Positioning and mmWave Communication via Multi-Point Connectivity +
## 4 Simulation Results
### Position Accuracy  
Figures 4 and 5 show the average positioning accuracy with the exhaustive beam training, as a function of increasing uplink transmit power and link blockage probability, respectively. It can be concluded in Figure 4 that positioning accuracy improves with the increase in the uplink transmit power \(P_{t}\). Higher the \(P_{t}\), better the SNR and that will lead to lower PEB, which can seen from Equation (23). It should be noted that an increase in the number of sounded beams during the beam training phase provides more Fisher information and that leads to better positioning accuracy, and, hence, lower PEB. However, with the increase in link blockage probability \(P_{b}\), there will be less active or unblocked beams, resulting in lower Fisher information and higher PEB, as shown in Figure 5, for the increasing link blockage probability.  
Performance gap between multi-point reception and BS selection method decreases with the increase in \(P_{b}\). The behavior is expected, since, with the higher link blockage probability, there will only be a few active beams that are contributing to the Fisher information.  
Finally, coordinated multi-point reception performs significantly better for all the simulation parameters, i.e., link blockage probability and uplink transmit power. The performance improvement obtained with the joint reception can be clearly seen from the empirical CDF in Figure 6.  
Figure 4: Average positioning accuracy as a function of increasing uplink transmit power \(P_{t}\) with the link blocking probability \(P_{b}=0\).
## 2 Methods
### Undifferenced Mixed OSB Model Coupled with Satellite Clock Offsets
\[\delta_{M_{I\bar{F}_{ik}}}^{s}(t)=b_{I\bar{F}_{ik}}^{s}-b_{I\bar{F}_{ij}}^{s}+ B_{I\bar{F}_{ik}}^{s}(t)-B_{I\bar{F}_{ij}}^{s}(t)=\delta_{p_{I\bar{F}_{ik}}}^{s}+ \delta_{\bar{p}_{I\bar{F}_{ik}}}^{s}(t) \tag{18}\]  
The mixed IFCB \(\delta_{M_{I\bar{F}_{ik}}}^{s}(t)\) can be further converted into OSB type, which is expressed as follows. \[\left\{ \begin{array}{c}\delta_{M_{i}}^{s}(t)=0\\ \delta_{M_{j}}^{s}(t)=0\\ \delta_{M_{k}}^{s}(t)=\alpha_{ij}\cdot\left(1-\mu_{k}/\mu_{i}\right)\cdot b_{ i}^{s}-\beta_{ij}\cdot\left(\mu_{k}-1\right)\cdot b_{j}^{s}-b_{k}^{s}\\ +\alpha_{ij}\cdot\left(1-\mu_{k}/\mu_{i}\right)\cdot B_{i}^{s}(t)-\beta_{ij} \cdot\left(\mu_{k}-1\right)\cdot B_{j}^{s}(t)-B_{k}^{s}(t)\\ =\delta_{p_{k}}+\delta_{\phi_{k}}(t)=\beta_{ik}^{-1}\cdot\delta_{I\bar{F}_{ik} }^{s}(t)\end{array} \right. \tag{19}\]  
Equation (19) indicates that the OSB for the third frequency is composed of the time-invariant UCD and time-variant UPD, which differs from Equation (17) in including and excluding pseudorange OSB for basic frequency. In summary, the traditional IFCB model is based on three assumptions: (1) the PIFCB of the same satellite at different stations has good consistency and the receiver PIFCB can be combined into satellite PIFCB; (2) pseudorange and phase IFCB are determined by CCL and ED GFIF models, respectively; (3) the PIFCB is determined by averaging multiple GNSS tracking stations. These assumptions also reflect some defects. If the time-varying phase delays of different GNSS receivers are inconsistent, it will have a negative impact on the satellite PIFCB estimation. It is undeniable that traditional methods are more efficient than undifferenced models in terms of computational efficiency because they do not require the calculation of ambiguity. However, the new method only has one set of ambiguity parameters, so the computational efficiency is still very high. In addition, the pseudorange OSB is required for basic frequency observations, and both pseudorange OSB and phase time-variant OSB corrections are required for the third frequency observation in MFPPP. Obviously, this way is too complicated. In addition, the ACs such as CODE, DLR, CAS, WHU, and SHA basically use CCL to generate satellite pseudorange OSBproducts. This will lead to the poor self-consistency of those biases. The new method can avoid complex bias correction. We do not need to make pseudorange OSB corrections for the basic frequency observations. We only need to make the pseudorange and phase time-variant mixed OSB corrections for the third frequency observation, which significantly optimizes the terminal positioning algorithm. The method of (19) is used to obtain the mixed OSB.