esa-sceva/satcom-chunk-collection huggingface dataset:
# Non-Contact High Voltage Measurement in the Online Partial Discharge Monitoring System
## 3 System Architecture for Non-Contact High Voltage Measurement  
### Capacitive Probe  
When designing the probe for field applications, the possibility of using both a monopole and disk probe was analyzed. The technical and environmental conditions were primarily taken into account. The arguments in favor of choosing a monopole probe were as follows. Firstly, the monopole probe capacitively interfaces with the test HV object to a much lesser extent than the disk probe, thanks to which it can be installed relatively close to the live device and there is no risk of exceeding the limit value for the digital equipment connected to its output. Secondly, the monopole probe has a more compact structure, thanks to which it is easier to ensure the tightness of its housing, which is important from the point of view of the operation in changing weather conditions (the influence of moisture). In addition, laboratory tests have shown that this type of probe, the active part of which is surrounded mainly by air, is less exposed to changes in the properties (probe capacitance \(C_{p}\)) due to moisture than a disk probe. As shown in [32], the dielectric constant of air in the range of relative humidity from 25% to 75% changes only by about 0.012%. Due to the fact that its active part is filled with a solid dielectric, the disk probe  
Figure 4: Equivalent circuit of the measuring system: (**a**) simplified, (**b**) detailed, where: \(C_{1}\)—coupling capacitance between the probe and the tested object, \(C_{p}\)—probe capacitance, \(C_{c}\)—coaxial cable capacitance, \(C_{s}\)—voltmeter input capacitance, and \(R_{s}\)—voltmeter resistance.  
significantly changes its parameters in contact with moisture. This, in turn, will result in significant errors during the measurements as the voltage ratio of the measuring system changes. This type of probe is also more difficult to protect against the ingress of moisture, due to the larger dimensions and specificity of the structure. Therefore, it was decided to use a monopole probe, the structure of which is presented below.  
The probe consists of a receiving element made of copper wire, 20 cm long and 2 mm in diameter. It is equipped with a Bayonet Neill-Concelman (BNC) coaxial connector and a waterproof casing made of polyethylene. The probe capacitance \(C_{p}\) as measured by the LCR meter is 2.2 pF. Figure 5 shows a 3D schematic diagram and a technical drawing with the dimensions of the developed probe for contactless high voltage measurement.
# Enhancing Street-Crossing Safety for Visually Impaired Pedestrians with Haptic and Visual Feedback
## 3 Study 1: Haptic and Visual Feedback for Visually Impaired Pedestrians Crossing at Traffic Signals
### Experimental Design
#### 3.1.5 Participants and Procedure  
We recruited 16 participants (9 males; 7 females) from a university campus, with an average age of 23.7 years (\(sd=1.06\)). Among the participants, 11 had prior experience with haptic or visual assistive devices, while 5 had no previous exposure to such technologies. During the experiment, the participants closed their eyes to simulate visual impairment [6]. [PERSON] et al. demonstrated that both sighted individuals with closed eyes and visually impaired pedestrians exhibit similar levels of decision consistency in their street-crossing decisions when relying on non-visual senses [6]. While this simulation cannot perfectly replicate the experience of those with long-term visual impairments, it provides a valu  
Figure 3: Configurations of haptic and visual feedback size. (**a**) Haptic stimulus size; (**b**) visual stimulus size.  
Figure 2: Frequency patterns for haptic and visual feedback. 1 represents 100% intensity vibration or light on, while 0 indicates no vibration or light off. (**a**) 0.5 Hz, (**b**) 1.0 Hz, (**c**) 2.0 Hz, and (**d**) 4.0 Hz.  
able preliminary approach to studying the challenges faced by individuals with visual impairments and evaluating potential assistive technologies in controlled settings.  
Using a Pico controller, participants pushed the joystick forward to indicate \"cross\" or pulled it backward to indicate \"wait\" and then pressed the trigger to proceed to the next trial. After completion, the participants filled out two questionnaires. The first measured urgency using a five-point scale [86]: 0 (not perceived), 1 (insignificant), 2 (low priority), 3 (high priority), and 4 (urgent). This choice aligns with research showing that users can distinguish at least four levels of urgency in vibration cues [86; 87]. The second captured decision confidence, from 0% to 100%, following methods in prior human-machine interaction studies [88]. Together, these metrics offered a comprehensive view of how different feedback modes impacted user decision-making.
## 6 Conclusions and Policy Implications  
### Conclusions  
Using panel data from 285 Chinese prefecture-level cities (2015-2023), this study examines the impact of green public procurement (GPP) on urban carbon emissions intensity with a particular focus on spatial spillover effects. The key findings are as follows.  
First, the results confirm that GPP significantly reduces urban carbon emissions intensity. Panel fixed-effects models reveal that a 1% increase in GPP expenditures leads to a 1.548% decrease in carbon emissions intensity. This finding confirming that GPP practices can effectively drive reductions in carbon emissions at the city level.  
Second, the study identifies three key mechanisms through which GPP lowers urban carbon emissions intensity. Urban green innovation mediates 9.65% of the total effect, corporate sustainability performance exhibits a mediation effect of 13.32%. Additionally, public ecological awareness mediates 5.31% of the effect, as GPP initiatives raise environmental consciousness, thus influencing consumer behavior and societal oversight to further curb emissions. These mechanisms collectively explain the multidimensional impact of GPP policies on urban carbon emissions intensity.  
Third, our analysis reveals a significant spatial spillover effect. The SDM establishes that a 1% increase in local GPP leads to a 1.360% reduction in local carbon emissions intensity and a 14.510% decrease in that of neighboring cities. This creates a remarkable cross-regional multiplier effect with a ratio of 1:10.7. These findings highlight the potential of GPP to foster inter-city collaboration in emissions reduction efforts.  
Finally, several control variables demonstrate complex spatial interaction effects that policymakers should consider. Population agglomeration and consumption upgrade directly reduce local carbon emissions intensity but may inadvertently increase intensity in adjacent regions through demand-driven production relocation and \"carbon leakage\"--whereby high-emission activities shift to areas with laxer regulations. Government intervention has a dual effect: moderate regulation facilitates emission reduction, but excessive intervention may distort market functions. Notably, stricter environmental policies in neighboring cities can trigger a \"competitive abatement\" effect that benefits the entire region.
## 4 Analysis of Research Variables
### Average CQI  
In an LTE network, the value of the _Channel Quality Indicator_ (CQI) is sent by the mobile device via the UL connection to the eNodeB, which provides the _User Equipment_ (UE) connection to the rest of the mobile network, and which, based on that value for data transmission in the DL direction, chooses the appropriate _Modulation and Coding Scheme_ (MCS) (Table 2).  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**CQI Index** & **Modulation** & **Approximate Code Rate** &
\begin{tabular}{c} **Efficiency (Information** \\ **Bits per Symbol**) \\ \end{tabular} \\ \hline
0 & No transmission & - & - \\
1 & QPSK & 0.076 & 0.1523 \\
2 & QPSK & 0.12 & 0.2344 \\
3 & QPSK & 0.19 & 0.3770 \\
4 & QPSK & 0.30 & 0.6016 \\
5 & QPSK & 0.44 & 0.8770 \\
6 & QPSK & 0.59 & 1.1758 \\
7 & QPSK & 0.37 & 1.4766 \\
8 & 16 QAM & 0.48 & 1.9141 \\
9 & 16 QAM & 0.60 & 2.4063 \\
10 & 16 QAM & 0.45 & 2.7305 \\
11 & 64 QAM & 0.55 & 3.3223 \\
12 & 64 QAM & 0.65 & 3.9023 \\
13 & 64 QAM & 0.75 & 4.5234 \\
14 & 64 QAM & 0.85 & 5.1152 \\
15 & 64 QAM & 0.93 & 5.5547 \\ \hline \hline \end{tabular}
\end{table}
Table 2: CQI values [39].  
Figure 3: Structure of physical block of resource elements (adapted from [36]).  
In this way, it defines the data transfer rate in the channel. The CQI value is determined based on the signal-to-interference plus noise (SINR) ratio and based on the characteristics of the mobile device. Most often, the mobile device selects the CQI value, and thus the MCS, so that the error rate (BLER) does not exceed 10%. Therefore, each CQI value is mapped to the corresponding modulation scheme (Quadrature Phase Shift Keying--QPSK, Quadrature Amplitude Modulation--QAM: 16 QAM and 64 QAM) which corresponds to a certain coding rate (Code Rate), and the number of bits per symbol. Table 2 shows CQI values according to 3 GPP LTE standards [39].
## 2 Related Work
### Discussion  
The discussed solutions for IoT and UAV networks for data communication have suffered from different routing issues. The topology-based protocols are especially designed for cellular networks where these protocols are exchanging routing tables for routing updates in the network as mobility is fast in UAV networks where the routing tables update does not suit due to delay and time factors. Topology-based routing creates overhead whenever there is a topology change [20]. For data communication, the UAVs' network has suffered with a limited payload or structure-free, unpredictable, or dynamic network topologies. Connectivity is one of the major challenges observed in existing solutions due to the limited communication or radio range of UAVs' nodes. The coverage area of UUVs nodes is limited and in some scenarios, it is not able to cover the ground, network such as in a forest, disaster areas, or large-scale areas. Some recent studies have utilized machine learning method to predict network topologies although the prediction is not realistic for such networks. The movement of nodes in these networks is very fast, where prediction is not possible. The UAV networks still suffer from various routing challenges where data delay, network overhead, and a lack of connectivity are observed [21]. Most of the routing protocols are dependent on a connected network status, which is again a weakness because frequent disconnection has been observed in networks where routing has failed. There is a need to design a more preferred routing protocol for data gathering from IoT networks for smooth and feasible data routing as existing routing protocols are designed for ground networks such as IoT, WSN, and cellular networks. However, the nature of UAV networks is unpredictable due to nodes' movements and their coverage. In this context, the proposed solution addresses the discussed issues by using more preferable and feasible routing parameters for UAV networks. The proposed protocol detects the network density from the ground network and calculates the distance and the UAV nodes call for congested traffic zones by sending one short message. The proposed solution also checks the battery power level to participate in data collection in the network and gives priority to those drones which have enough battery power.
## 1 Introduction  
The propagation analysis of a surface crack is a critical capability for structural integrity prediction of cylindrical metallic components (bolts, screws, shafts, etc.) Part-through flaws appear on the free surface of a smooth round bar and the front of a growing crack can be considered as a so-called 'almond' shape by extensive experimental works [1; 2; 3; 4; 5; 6].  
Attempts to predict fatigue growth of a surface crack in a round bar have been reported. Some investigators have employed a circular arc to describe the crack front [5; 7; 8], then the hypothesis that an actual part-through crack can be replaced by an equivalent elliptical arc edge flaw has been widely applied. [PERSON] [9; 10; 11; 12; 13], as one of the most representative researchers on this topic, conducted extensive studies related to this configuration. However, regardless of whether they used a circular arc or elliptical arc, most researchers employed a certain shape with a fixed center, which reduced the fatigue calculations to one-or two-dimensional problems. Few efforts have been made utilizing a three-parameter model. Although [PERSON] [14] mentioned the three-parameter model previously, the fatigue crack propagation was simply examined by applying the Paris-Erdogan law with the least square method as in almost all previous studies [15; 16; 17]. In addition to experimental backtracking technique [18; 19] and normalized area-compliance method [20], there is no further research regarding the method of surface crack prediction.  
The objective of this paper was to predict the shape change of a fatigue crack in a round bar subjected to tension by employing fatigue crack growth circles, based on a three-parameter model using finite element analysis. In this paper, a fewer shape restraints model with part-elliptical cracks whose center was allowed to move along the vertical axis was built, which could be more precise for expressing the actual crack shape front. The nominal aspect ratio of an ellipse, which is more meaningful, is proposed for the three-parameter model. Meanwhile, the fatigue crack growth circles, which are on a tangent to both current and new crack fronts, were developed to predict the crack path. The equivalent stress intensity factor \(\Delta K_{e}\) based on both stress intensity factors along the current and new crack fronts was proposed to reduce the number of modeling computations with only a few iterations. The validity of the present method will be shown by comparing its results with a simulation solution and experimental results.
# A Novel System of Mixed RF/FSO UAV Communication Based on MRR and RIS by Adopting Hybrid Modulation
## 2 System and Theoretical Model
### CDF of End-to-End SNR  
In the dual-hop communication system using DF protocol, \(\gamma=\min(\gamma_{1},\gamma_{2})\)[36; 37], where \(\gamma\) is the instantaneous end-to-end SNR of the system, \(\gamma_{1}\) and \(\gamma_{2}\) are the instantaneous SNR of the RF and FSO links, respectively. Therefore, the CDF of end-to-end SNR is expressed as [38]:  
\[\begin{split} F_{\gamma}(\gamma)&=1-(1-F_{\gamma _{1}}(\gamma))(1-F_{\gamma_{2}}(\gamma))\\ &=F_{\gamma_{1}}(\gamma)+F_{\gamma_{2}}(\gamma)-F_{\gamma_{1}}( \gamma)F_{\gamma_{2}}(\gamma).\end{split} \tag{10}\]  
Substituting (2) and (7) into (10), the CDF of end-to-end SNR for the system uplink is obtained as:  
\[F_{\gamma}(\gamma)=1-e^{-\frac{\gamma}{\tilde{\gamma}_{1}}}\left(\sum_{m=0}^{ N-1}\frac{\gamma^{m}}{(B\overline{\gamma}_{1})^{m}m!}\right)\left(1+W\times G \begin{array}{c}5,1\\ 2,6\end{array}\left(\frac{\alpha_{1}\alpha_{2}\beta_{1}\beta_{2}}{A_{0}} \sqrt{\frac{\gamma}{\tilde{\gamma}_{2}}}\bigg{|}\begin{array}{c}\phi_{1}\\ \phi_{2}\end{array}\right)\right), \tag{11}\]  
where \(W=\frac{\xi^{2}}{\Gamma(\alpha_{1})\Gamma(\alpha_{2})\Gamma(\beta_{1})\Gamma( \beta_{2})}\); \(\phi_{1}=1,\xi^{2}+1\); \(\phi_{2}=\xi^{2},\alpha_{1}\), \(\alpha_{2},\beta_{1},\beta_{2},0\).  
Similarly, substituting (2) and (9) into (10), the CDF of end-to-end SNR for the system downlink can be given by:  
\[F_{\gamma}(\gamma)=1-e^{-\frac{\gamma}{\tilde{\gamma}_{1}}}\left(\sum_{m=0}^{ N-1}\frac{\gamma^{m}}{(B\overline{\gamma}_{1})^{m}m!}\right)\left(1+\frac{\xi^{2}}{ \Gamma(\alpha_{3})\Gamma(\beta_{3})}\times G\begin{array}{c}3,1\\ 2,4\end{array}\left(\alpha_{3}\beta_{3}\sqrt{\frac{\gamma}{\tilde{\gamma}_{2} }}\bigg{|}\begin{array}{c}1,\xi^{2}+1\\ \xi^{2},\alpha_{3},\beta_{3},0\end{array}\right)\right). \tag{12}\]
## 2 Materials and Methods  
Figure 1 shows schematic drawings of the 3D view of the eSRR device and the corresponding geometrical denotations of the unit cell. The eSRR device is composed of double symmetrical semicircles and two central metal bars on the SOI substrate. The thickness of the Au layer is kept constant at 300 nm. The corresponding geometrical denotations of the eSRR unit cell are represented in Figure 1b. They are lengths (\(L_{1}\), \(L_{2}\)) of the metal bars, the gap (\(g\)) between the two metal bars, gaps (\(g_{1}\)) between semicircles and bars, and outer and inner radiuses (\(R\), \(r\)) of semicircles. The metal line width is kept as a constant at 4 \(\mu\)m. The period of the eSRR is 80 \(\mu\)m \(\times\) 80 \(\mu\)m. The proposed eSRR device is designed based on finite difference time domain (FDTD) solutions. The periodic boundary conditions are applied along the \(x\)- and \(y\)-axis directions, while the boundary condition of the \(z\)-axis direction is a perfectly matched layer (PML). The monitor of resonant frequency is set under the eSRR device to calculate the transmission of the incident THz wave. The resonant frequency (\(f_{LC}\)) can be expressed by [36]:  
\[f_{LC}=\frac{1}{2\pi\sqrt{L_{eq}C_{eq}}}=\left(\frac{c_{0}}{l\sqrt{c_{c}}} \right)\sqrt{\frac{g_{eq}}{w}} \tag{1}\]  
where \(c_{0}\) is the light velocity in a vacuum, \(L_{eq}\) and \(C_{eq}\) are the equivalent inductance and capacitance of eSRR, \(\varepsilon_{c}\) is the relative permittivity of the materials within the eSRR, \(l\) is the size of models, \(w\) is the metallic line width, and \(g_{eq}\) is the equivalent gap width of the eSRR. The resonant frequency of the eSRR can be tuned by changing different parameters. According to Equation (1), the impact of metallic thickness is minor [37; 38; 39]. Here, the Au layer is designed to be 300 nm in thickness.
# A Statistical Analysis of Industrial Penetration and Internet Intensity in Taiwan +
## 2 Firm's Internet Intensity and Geographical Concentration
Using sample survey data for 17,000 small and medium-sized firms covering the period from July 2001 to February 2002, and by focusing on the degree to which the manufacturers used information technology (IT), they categorized the manufacturers into those that: (1) did not use information technology; (2) had low use of information technology; (3) had medium use of information technology; and (4) had high use of information technology. They found that the factors that significantly affected the manufacturer's use of information technology included the scale of the manufacturer's operations, the geographical location of the plant, the training that was provided by the manufacturers for their employees, how much they engaged in R&D, the amount of outsourcing that occurred, and the degree of cooperation with other manufacturers. [21] [PERSON] et al. (2011) used survey data on French manufacturers for 2001 and 2002, and discovered that using the internet to co-ordinate and monitor the company's branch network within particular sectors was an important factor affecting the manufacturer's use of information and communications network technology. Therefore, the distance between the enterprise's head office and branch units, and the geographical dispersion of the enterprise's branch units, significantly affected the extent to which manufacturers used information and communications network technology. In addition, the more that enterprises within the same industry or geographical area used internet technology, the greater was the contagion effect resulting from the internet technology, with there being a significant positive impact on how much the enterprises used the internet. These empirical results provided support to the theories that were advanced by [22; 23] [PERSON] (1963a, b) and [24] [PERSON] and [PERSON] (1995). The literature shows that substantial research has focused on the problems that are associated with internet intensity related to urbanization. However, few if any studies have analysed the relationship between industrial penetration and the degree to which firms have used the internet. For this reason, this paper will focus on the important but as yet not thoroughly investigated issue of internet use and industrial penetration.
## 4 Results and Discussion
### Flight Routes Visualization
(**b**) When removing self-connections and focusing on external connections, we observe that _Europe_ and _Asia_ are the two most highly connected continents. this analysis at a higher level of abstraction, visualizing _South America_ collapsed. Highlighting the direct connections of _South America_, we observe that it has direct routes with only five African countries: _Morocco_, _South Africa_, _Togo_, _Cape Verde_, and _Angola_ (Figure 17b). Figure 16: (**a**) Focusing on _Europe_, the most highly connected countries are _Germany_ and _Spain_. (**b**) Uncollapsing, applying a magnification on _Spain_, and highlighting the connections from _Germany_ reveals that the majority of the routes between _Germany_ and _Spain_ are with the _Canary Islands_, followed by the _Balearic Islands_ and _Andalusia_ region. Figure 17: (**a**) _Brazil_ is the only South American country with air routes to _Africa_. (**b**) _Brazil_ connects with only 5 African countries: _Morocco_, _South Africa_, _Togo_, _Cape Verde_, and _Angola_. Figure 15: (**a**) Filtering out the rest of the continents except _Asia_ and _Europe_, we can analyze the connectivity between them. By uncollapsing _Europe_, we can see that European _Russia_ is the country with the most connections to _Asia_. (**b**) By painting the connections among sibling countries on the outward side of the sunburst, the external routes are more sharply observed. In this image it is easy to see that the European countries that are most connected to _Asia_ are _Russia_, _Great Britain_, and _Germany_. (**c**) Uncollapsing _Asia_, we observe that _Turkey_ is the Asian country most connected to _Europe_.