esa-sceva/satcom-chunk-collection huggingface dataset:
# Evaluation of Spaceborne GNSS-R Retrieved Ocean Surface Wind Speed with Multiple Datasets
## Theory and Methods
### Wind Speed Retrieval Algorithm
When the retrieved wind speed between the two types of observables is greater than 3 m/s, the inversion results are considered unreliable. Finally, the MV estimation is used to dynamically adjust the DDM SNR variation caused by GNSS-R geometry changes. The optimal wind speed estimator is obtained by weighting the wind speeds from DDMA and LES [22].
_applied_  
_sciences_  
_Article_  
Study on Deformation Control of Road-Deep Foundation Pit  
Passing under Elevated Subway Bridge  
[PERSON] 1\({}^{\copyright}\), [PERSON] 1, [PERSON] 2,3,4,*, [PERSON] 1\({}^{\copyright}\) and [PERSON] 1  
1 School of Civil Engineering, Beijing Jiaotong University, Beijing 100044, China  
2 National Engineering Research Center of High-Speed Railway Construction Technology,  
Changsha 410075, China  
3 China Railway Group Limited, Beijing 100039, China  
4 School of Civil Engineering, Central South University, Changsha 410075, China  
* Correspondence: [EMAIL_ADDRESS]  
This paper focuses on the application of pile foundation underpinning technology in a deep foundation pit of a subway Viaduct Project in Beijing. The study aims to address the engineering characteristics of the project, including a large number of new piles, a wide span of underpinning abutment, a long length of deep foundation pit, and a wide range of influences. This research utilizes field monitoring and numerical simulation methods to investigate the pile foundation underpinnings. The impact and management of road-deep foundation pit construction are considered, as well as their combined effect on subway viaducts and track structures. The primary accomplishments are as follows: (1) By analyzing the data from on-site deformation monitoring, it is evident that the pier exhibits maximum vertical deformation and maximum transverse deformation at the same location. The measuring locations are specifically situated on Pier 7# at the pile foundation underpinning. The maximum vertical and transverse deformations of the track are directly proportional to the maximum deformation of the pier. (2) By comparing the numerical simulation results with the field monitoring data, it is observed that although there is some discrepancy between the two, the deformation trend is largely consistent. This suggests that the numerical simulation analysis method is effective in reflecting the deformation of the bridge and track. (3) Through the numerical model and changing the values of the retaining structure parameters, the sensitivity of the pier deformation near the road foundation pit to the retaining structure parameters is systematically analyzed. The sensitivity of the pier deformation to the foundation pit parameters is as follows: the embedded depth insertion ratio of the retaining pile > the diameter of the retaining pile > the pile spacing.  
road-deep foundation pit; pile underpinning; foundation pit construction; viaduct; monitoring data; numerical simulation; deformation control
## 5 Conclusions  
The literature shows that the LPO-catalyzed oxidation of I\({}^{-}\) and SCN\({}^{-}\) mixtures can result in contradictory antimicrobial efficiency. The present article shows that certain mixtures of lactoperoxidase-oxidized I\({}^{-}\) and SCN\({}^{-}\) have a very good antimicrobial potential. Practical applications should use an optimal iodide/thiocyanate ratio of 4.5 to favor antimicrobial efficiency and a strongly mineralized medium if high doses of substrates are used. Although the oxidant is relatively stable, its long-term storage is clearly improved at 4 \({}^{\circ}\)C. The use of an environment that enhances the oxidoreduction reaction catalyzed by the enzyme can dramatically increase its efficiency; as a consequence, more oxidants are generated and antimicrobial activity is better.  
Conceptualization, F.B., M.H.J., and J.-P.P.; methodology, F.B., M.H.J., and J.-P.P.; software, F.B. and C.D.; data validation, F.B., C.D., G.C.L., and J.-P.B.; formal analysis, F.B., C.D., G.C.L., and J.-P.B.; writing--original draft preparation, F.B.; writing--review and editing, F.B., M.H.J., C.D., G.C.L., J.-P.B., and J.-P.P.; supervision, M.H.J.; project administration, F.B. and M.H.J.  
This research was funded by the Walloon Region (Service Public de Wallonie-DGO6) and by Taradon Laboratory.  
The authors declare no conflict of interest.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & & \multicolumn{4}{c}{**T\({}_{\text{1/2}}\) (Days)**} \\ \cline{2-6}  & **25 \({}^{\circ}\)C** & **4 \({}^{\circ}\)C** & **25 \({}^{\circ}\)C** & **4 \({}^{\circ}\)C** & **25 \({}^{\circ}\)C** & **4 \({}^{\circ}\)C** \\ \hline
**Water Mineralization** & **Double-Dose** & \multicolumn{4}{c}{**Full-Dose**} & \multicolumn{4}{c}{**Half-Dose**} \\ \hline
**Low** & 11 & 34 & 49 & 309 & 109 & 494 \\
**Medium Low** & 15 & 119 & 36 & 248 & 100 & 464 \\
**Medium High** & 20 & 165 & 98 & 504 & 73 & 433 \\
**High** & 33 & 229 & 121 & 491 & 94 & 529 \\ \hline \hline \end{tabular}
\end{table}
Table 8: Half-lives (T\({}_{1/2}\)) expressed in days of the double-, full and half-doses of substrates after lactoperoxidase oxidoreductase in various mineralized waters (low; medium low; medium high; high) in function of the storage temperature (25 \({}^{\circ}\)C or 4 \({}^{\circ}\)C).
## 3 Experiments and Discussion
### Experiments on VRM  
#### 3.1.1 Analysis of Grid Convergence  
The grid resolution should be first studied to improve the computing efficiency on the premise of ensuring the accuracy. Further experiments are based on the optimized grid level. Here a test  
Figure 6: Computation flow.  
was done using geometric and experimental data from NACA Technical Note 1270, in which several NACA-44 series airfoils were tested [33]. The test was to verify the influence of grid resolution on the convergence of aerodynamic coefficients. Based on the NACA-4412 airfoil, four wing geometries were studied, covering low aspect ratio-low sweep angle, low aspect ratio-high sweep angle, high aspect ratio-low sweep angle and high aspect ratio-high sweep angle. Details on the geometries of four test wings are presented in Table 1. Further airfoil parameters are shown in ref [33].  
VRM requires a sufficiently refined grid to achieve results that are grid-independent. Ten different surface grids of increasing mesh density were generated for each of the geometries. Each grid had a constant spacing in both chord-wise and span-wise directions. The lattice number of chord-wise \(N_{RW}\) and span-wise \(N_{CW}\) are presented in Table 2.  
Vortex rings were all assigned on the mean camber surface. In Figure 7, the changes of the lift coefficient \(c_{L}\), drag coefficient \(c_{D}\) and pitching moment coefficient \(c_{m}\) about the 1/4 chord point of the root chord are presented, for the four test wings, as a function of the grid refinement level. All the coefficient values were normalized using the value obtained for the finest grid, Grid 10. When it comes to the eighth refinement level, the results for all three aerodynamic coefficients and for all four wing geometries were within 1% of the values obtained with the most refined grid. Thus, satisfactory accuracy can be obtained by adopting Grid 8 configuration.  
\begin{table}
\begin{tabular}{c c c c c} \hline
**Geometry** & **Wing 1** & **Wing 2** & **Wing 3** & **Wing 4** \\ \hline Aspect ratio & 11.3 & 11.3 & 6.7 & 2.4 \\ Sweep angle & 0 & 45 & 0 & 60 \\ Span & 34 & 34 & 10 & 12 \\ Root chord length & 5 & 5 & 2 & 6 \\ Tip chord length & 1 & 1 & 1 & 4 \\ Taper ratio & 5 & 5 & 2 & 1.5 \\ \hline \end{tabular}
\end{table}
Table 1: Details of test wings used for grid convergence study.  
\begin{table}
\begin{tabular}{c c c c} \hline
**No.** & \(N_{CW}\) & \(N_{RW}\) & **Total** \\ \hline Grid 1 & 6 & 3 & 18 \\ Grid 2 & 12 & 6 & 72 \\ Grid 3 & 18 & 8 & 144 \\ Grid 4 & 20 & 10 & 200 \\ Grid 5 & 25 & 10 & 250 \\ Grid 6 & 30 & 12 & 360 \\ Grid 7 & 40 & 15 & 600 \\ Grid 8 & 40 & 20 & 800 \\ Grid 9 & 60 & 20 & 1200 \\ Grid 10 & 80 & 20 & 1600 \\ \hline \end{tabular}
\end{table}
Table 2: Number of cells included at each grid level used for convergence study.
## 4 Experiments and Results
### Baseline Systems  
In comparison with recent proposals [11; 12; 38], RNN-based models are significantly better than HMM-based and DNN-based models. Therefore, we used the RNN-based models as a baseline. In terms of the representation of \(F_{0}\), the DCT-based model was used as a baseline because of its advantages reported in [23]. Details of the implementation of the baselines are described below.
## 3 Irrigation Scheduling  
Irrigation scheduling is the process of determining how much water to apply and when to irrigate, and thus has a direct effect on WUE: the application of more water than that is necessary for optimal plant consumption reduces the irrigation WUE. Irrigation scheduling requires an understanding of the pattern of plant water use, which is affected by factors such as weather, growth stage and canopy wetness. The meteorologic component varies seasonally, daily and diurnally.  
Irrigation may be scheduled based on the plant water status, which may be measured directly using a pressure bomb, or indirectly by monitoring the flow of the stem sap. Other indirect methods include the measurement of soil moisture content using probes and estimation of crop evapotranspiration (ET). A summary of the main irrigation scheduling approaches is presented in [PERSON] [16]. In Australia, the most common tools used for irrigation scheduling are soil probes and tensiometers [17]. The major drawback of using these soil-moisture-based tools for scheduling is that they give point-based measurements, while the soil characteristics are known to vary spatially and temporally [18].  
Farmers who do not use any scheduling tool often rely on their experiences to schedule their irrigations. However, previous studies have shown that such farmers who rely on the \"rule-of-thumb\" may be losing water [19]. Emerging methods of measuring or estimating crop water status for irrigation scheduling purposes are discussed later in this paper.  
With the advancement in technology including the internet, a number of computer-based irrigation scheduling systems have been developed to help farmers in their decision-making process. Typical examples of these used in Australia include WaterSense, WaterTrack Rapid and IriSatSMS [20]. However, despite the proven benefits of improved WUE using these technologies, their adoption is still limited because of reasons ranging from complexity to cost [17]. In the recent years, cheaper and more versatile sensors have become available (for instance Figure 2).  
It is clear from the above discussion that scheduling of irrigation is easier if the irrigation system is automated, and with features such as accurate metering and sensors.
# Entity Relationship Extraction Based on a Multi-Neural Network Cooperation Model
## 4 Experiments and Results
### Evaluation Index  
For the evaluation of experimental results, this paper takes the F1 value as the main evaluation index based on current mainstream practices. P is the precision rate of experimental results, R is the recall rate of experimental results, FP is the number of times predicted to be the relationship but not the relationship, TP is the number of correct predictions of the relationship, FN is the number of times predicted to be the relationship but wrong, and the specific calculation formula of F1 value is as follows:  
\[\text{P}=\frac{\text{TP}}{\text{TP}+\text{FP}} \tag{13}\]  
\[\text{R}=\frac{\text{TP}}{\text{TP}+\text{FN}} \tag{14}\]  
\[\text{F1}=\frac{2\text{P}*\text{R}}{\text{P}+\text{R}} \tag{15}\]  
\begin{table}
\begin{tabular}{c c c c c} \hline
**Relationship** & **DuIE2.0 Train** & **Our Small Balanced** & **DuIE2.0 Test Set** & **Our Small Balanced** \\
**Number** & **Set** & **Train Set** & **Test Set** \\ \hline
1 & 1817 & 30 & 171 & 10 \\
2 & 4701 & 30 & 460 & 10 \\
3 & 2466 & 30 & 237 & 10 \\
4 & 16,553 & 30 & 1425 & 10 \\
5 & 10,342 & 30 & 889 & 10 \\
6 & 660 & 30 & 50 & 10 \\
7 & 1008 & 30 & 94 & 10 \\
8 & 3522 & 30 & 337 & 10 \\... &... &... &... &... \\
17 & 20 & 20 & 1 & 1 \\
50 & 633 & 30 & 57 & 10 \\ Total number & 172,983 & 1451 & 19,981 & 462 \\ \hline \end{tabular}
\end{table}
Table 1: Example of dataset sampling results.
## 4 E-Waste Management in Serbia--Current Situation
### Obstacles and Potential Solutions in the E-Waste Management System in SERBIA
#### 4.1.2 Organizational Obstacles  
The infrastructure for e-waste management at the state level practically does not exist, and the motivation for e-waste recycling depends to a large extent on the will of a few private companies that deal with it for personal gain [43]. At the moment, communal services typically collect e-waste along with other bulky waste because there is neither a system in place for the separate collection of this waste from households nor locations for its collection at the local community level [44; 45]. There are only collection companies dealing with targeted collection of this waste, and there are 15 of them nationwide [35]. These companies are located in urban areas, while there are none in rural areas [36]. The return of waste electrical and electronic equipment from retail establishments is only partially carried out, while these same retail establishments do not offer the service of accepting this waste from citizens [41]. This is because those who collect this waste should have a storage permit according to the Law on Waste Management, and currently only companies dealing with the collection and recycling of e-waste in Serbia have it [46]. Practice has shown that even the companies involved in the recycling of e-waste in Serbia are not sufficiently motivated to collect waste directly from households, but do so through occasional environmental campaigns [47]. Currently, the most efficient collection of e-waste in Serbia is carried out through organized collection actions initiated by the recyclers themselves, which include bringing the waste to a specified location or the arrival of collectors at the home address. The biggest problem in the entire e-waste management system is illegal flows, which make monitoring the situation in Serbia and statistical analysis difficult [35; 48]. The lack of professional staff for e-waste management in the relevant institutions has been a problem for years. This begins with the Ministry of Environmental Protection, where additional staff are required to handle the implementation of legal and strategic acts. This extends to the inspection supervision sector, which overse the performance of activities within the framework of e-waste management, and the Serbian Environmental Protection Agency, which is responsible for reporting [41]. Due to the lack of specialized softwarefor monitoring waste flow, operators in Serbia improvise their e-waste reporting methods, primarily using various accounting programs or Microsoft Excel 2021 [49]. The root of these problems lies, to the greatest extent, in high investment costs and the absence of state support. Landfill fees are generally low, making e-waste treatment and recycling operations a priori expensive. Therefore, there has been minimal investment in the development of e-waste separation technologies thus far.
# Privacy and Security in Digital Health Contact-Tracing: A Narrative Review
## 3 Results
### Data Protection and Control
#### 3.2.3 Data Misuse and Abuse  
Data misuse refers to sharing data for purposes other than the main intention, while data abuse refers to a more severe misuse of data for different agendas, which impacts individuals. Concerns about the potential misuse of personal data have emerged as significant barriers to adopting contact-tracing apps. There was a concern among participants that the information collected could be used for purposes other than managing the pandemic [108]. This fear of data misuse has been prominent in the negative sentiments [64; 65]. According to a study conducted in the USA, 40% of the participants expressed concern about the purpose of data collection and storage, 28% were worried about the potential sale of data for profit, 24% mentioned security and confidentiality as their main concern, 8% concerned the type of data collected, and another 8% were worried about the possibility of the data being used against them [94].  
In Malaysia, respondents acknowledged the potential risk of abuse of their data [105]. In the USA, participants voiced concerns about contact-tracing apps potentially leaking information to third parties. Forty-six percent indicated that this concern would significantly or strongly influence their decision whether to install the contact-tracing app [109]. The public expressed concerns about data theft and the potential for law enforcement to use the information provided against them [110]. There was significant fear about governments using digital contact-tracing to further different agendas [110]. In the US, concerns mainly centred around the misuse of sensitive data [52].  
A study conducted in the UK with people from the Black, Asian, and Minority Ethnic (BAME) communities found that many individuals were worried about their privacy due to the possibility of the government or other organisations accessing their data and using it for other purposes as the nature and scope of data collection were not clear [50].  
People expressed concerns about sharing their data with other organisations without their consent, which could be used for marketing purposes and to identify the target audience for businesses [108]. In an Irish study, 41% of respondents mentioned that they worried technology companies would use this as an excuse for greater surveillance after the pandemic, 33% worried that the government would do the same, and 22% worried that phones would be more likely to get hacked [111].  
The perception of susceptibility to data misuse was negatively correlated with the adoption of contact-tracing apps to the same extent in Singapore and Switzerland. The severity of data misuse was not associated with contact-tracing app adoption in Singapore and was weakly positively correlated with app adoption in Switzerland [112].
# A Context-Aware Edge-Based VANET Communication Scheme for ITS +
## 2 Related Work
### VANET Multi-Hop Unicast Communications  
Many protocols have been proposed to take into account the vehicle mobility, route length, and inter-vehicle wireless link quality for the route selection since the performance of a communication route is affected by these multiple factors. [PERSON] et al. [14] have proposed a traffic-aware position-based routing protocol for city environments. The protocol uses small control packets to sample traffic conditions and makes routing decisions based on congestion conditions. In [15], the regularity of vehicle moving behaviors has been used to improve the routing performance by predicting a vehicle's future locations based on the past traces and a hidden Markov model. [PERSON] et al. [16] have discussed the routing decision at the intersection, and proposed a protocol that makes routing decision based on road structure, vehicle position and received signal strength. There have been several studies considering some special types of vehicles to improve the routing. [PERSON] et al. [18] have proposed a bus-based street-centric routing approach that uses buses as the main relay nodes for the packet forwarding. Similarly, [PERSON] et al. [19] uses the bus systems as routing backbones of VANETs. In [20], drones are used for boosting VANET communications.  
However, these existing approaches do not adequately address the MAC layer contention issue in a high-density network. Since vehicles could be deployed in a high-density manner for some hours or some road segments, the number of concurrent sender nodes is expected to be large. IEEE 802.11p, the standard for wireless access in vehicular environments, has the performance degradation problem when the number of sender nodes increases due to the MAC layer contention scheme based on the exponential backoff [12; 13]. However, this problem is not sufficiently considered in the design of routing protocols.
## 3 Results and Discussion
### Hardened Properties of OMGPC
#### 3.2.5 Static Modulus of Elasticity of OMGPC Incorporating Recycled Aggregates  
Figure 13 presents [PERSON]'s modulus of elasticity of OMGPC with REISIN8 and FWG aggregates. Adding these aggregates resulted in a significant reduction in the elastic modulus compared to the control OMGPC. The control OMGPC exhibited an elastic modulus of 33 GPa. However, incorporating R5% leads to a substantial 60% reduction in the matrix stiffness against deformation. At the incorporation of R10% in OMGPC, the elastic modulus experienced an even more drastic reduction of 78.8%. These findings indicate that the inclusion of REISIN8 aggregates above 5% significantly weakens the overall stiffness and rigidity of the OMGPC matrix. This result is consistent with the previous studies on the use of recycled waste plastic in concrete production, ascertaining that the increase in the recycled aggregate content results in a decrease in the elastic modulus of the concrete [80; 81].  
Similarly, adding FWG aggregates also has a notable impact on the elastic modulus of OMGPC. With a G5% content, the elastic modulus decreased by 21.2%, while a G10% content resulted in a more significant reduction of 30.3%. [PERSON] et al. [57] reported a decrease in [PERSON]'s modulus of elasticity of OMGPC with the inclusion of FWG, which was attributed to the weak glass-geopolymer interfaces. The observed reductions in elastic modulus for both plastic and FWG aggregates are important considerations for structural applications that rely on the stiffness of the concrete and the ability to withstand deformation under loads. The lower elastic modulus may affect the overall behaviour and performance of OMGPC elements, especially in cases where stiffness and resistance to deformation are critical design factors.
## 4 Decomposing Multi-Controlled Rotation Gates  
The multi-controlled rotation gates from Section 3.6 can be decomposed into a combination of CNOTs and regular rotation gates. This can be done using the method from [13], which results in \(2^{k}\) CNOTs gates and \(2^{k}\) 1-qubit rotation gates for a controlled rotation gate with \(k\) control bits. To move from an \(F_{k}^{m}(R_{a})\)-gate to an \(F_{k-1}^{m}(R_{a})\)-gate, a circuit such as Figure 3 can be used.  
Figure 1: A quantum multiplexer.  
Figure 3: Partial decomposition of an \(F_{k}^{m}(R_{a})\)-gate.  
Figure 2: A multi-controlled \(U(2)\) gate.  
This can be extended until only CNOT gates and one-qubit rotation gates are left, which leads to an example decomposition of a rotation gate with three control bits as shown in Figure 4.  
To directly calculate which qubit is the control bit for each CNOT, this can be determined using Gray code. This is shown in the table below the circuit. The number of the bit that is changed in the Gray code is the number of the qubit that will be the control bit.  
For each control bit of the multi-controlled gate, a one-qubit rotation gate and a single CNOT is used, so the total decomposition of an \(F_{m}^{k}\)-gate requires \(2^{k}\) rotation gates and CNOTs [13]. This is the least-known number of gates for decomposing such a matrix and is therefore used in almost all decomposition methods for (block) diagonal matrices of this form.