esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Analysis of Numerical Results
### Influence of the Water Level on the Riverbed Side  
Five working conditions of the water level on the riverbed side (23 m, 26 m, 29 m, 32 m and 35 m) were selected for the simulation of stepwise excavation, as shown in Table 2. In  
Figure 14: Variation curve of displacement at different monitoring points with the tunnel spacing.  
Figure 13: Lateral variation curve of ground settlement for different tunnel spacing at 10 m depth in excavation direction.  
the annual flood season, the water level of the Liuyang River will rise significantly. In order to study the influence of the change in riverbed water level on the surface displacement after excavation, different water level values are set in the working condition, and the settlement changes of each monitoring point under different water level conditions are recorded; the results are shown in Figure 15 below.  
From Figure 15, it can be seen that the higher the water level is, the larger the settlement value of the strata is, and the settlement at the centerline of the two tunnels is the largest. As the water level on the riverbed side rises, the lateral and vertical pressures in each part of the tunnel increase almost linearly with the water level, and the difference between the two increases is small. However, the increase in both is smaller than the increase in river pressure, which is because the river pressure added to the surrounding rock changes the lateral pressure coefficient of each part. With the increase in water level on the riverbed side, the ground settlement increases, but its settlement difference is smaller than the difference under the influence of the other three factors, which indicates that the ground settlement is less affected by the change in water level. This is due to the fact that the river water weight is smaller than the unit weight of soil, so the effect of tunnel settlement is less affected by the change in water level. In conclusion, the tunnel construction period should be chosen during the river dry period as much as possible when building the tunnel through the river.
# A Novel Methodology for Planning Urban Road Safety Interventions
## 4 Validation of the Proposed Methodology via Case Study Application
### Proactive Analysis of Black Spots and Intervention Proposals
#### 4.3.3 Black Spot with Motorized Traffic  
Two critical locations (D and E) for motorized traffic incidents were identified, as demonstrated in Figure 18.  
The first one is critical point D, which is the roundabout is notable for high accident density involving motorcycles and automobiles. This complex roundabout consists of five exits, four entries, and three circulating lanes. With peak hourly traffic flows of 4500 vehicles in the morning and 4000 in the evening, its multi-lane configuration encourages risky lane changes and high-speed driving.  
Proximity between entries and exits reduces maneuvering space, often resulting in collisions during entry and exit maneuvers. The accident distribution across the roundabout was not localized, highlighting a systemic issue rather than a single entry or exit causing the incidents (see Figure 19).  
The second one is critical point E, which is a signalized intersection, characterized by frequent vehicle collisions due to red-light violations. This signalized intersection reported 11 vehicle collisions from 2017 to 2023, predominantly caused by vehicles running red lights, conflicting with traffic from the northern side (see Figure 20).  
The iRAP methodology has notable shortcomings in evaluating intersections, particularly in complex or signalized configurations due to the following:  
1. Simplistic modeling: Intersections are treated as extensions of road segments rather than standalone entities, limiting detail on entry and exit flows;  
Figure 19: Concentration map outputted by GIS of accidents at the square, (**a**) between motor vehicles, and (**b**) involving motorcyclist.  
Figure 18: Black spots D and E associated with accidents involving motor vehicles only, outputted by GIS.  
2. Traffic aggregation: iRAP aggregates traffic volumes without accounting for direction-specific flows, reducing risk analysis precision;
3. Signal timing ignored: Signal cycle durations, critical to traffic flow and conflict prevention, are not considered;
4. Uniform parameters: Roundabouts are evaluated using standardized attributes that fail to reflect detailed factors like lane config., entry angles, or geometric design.  
Due to these limitations, critical points D and E were excluded from the proactive cost-benefit analysis.
# Efficient and Secure EMR Storage and Sharing Scheme Based on Hyperledger Fabric and IPFS
## 5 Scheme Implementation
### Data Storage Phase
#### 5.3.5 IPFS Stores Medical Data  
The encrypted medical data of patients' EMR are stored in the IPFS, while only the medical data index is saved on the blockchain. This design not only alleviates the burden on the blockchain network but also reduces the risks associated with single points of failure and privacy vulnerabilities caused by centralized storage methods.  
After diagnosis and treatment at hospital \(H\), the medical data plaintext \(M_{EMR}\), which does not contain patient privacy, is encrypted by \(H\) to generate the corresponding medical data ciphertext \(C_{EMR}\). This ciphertext is then uploaded to an IPFS node for storage. The IPFS calculates a unique data CID identifier from this medical data ciphertext. This CID is subsequently returned to hospital \(H\), which utilizes this identifier to construct the \(TreatmentData\) object and uploads it to the data channel for persistent storage. When DUs wish to access the stored data in the IPFS, they must provide the corresponding CID. The IPFS locates and accesses the corresponding medical data based on the CID. If the data are tampered with, the original CID will not match, thereby preventing access to the altered data.
# Effective Privacy-Preserving Collection of Health Data from a User's Wearable Device
## 4 Proposed Method
### Wearable Device Processing
Then, based on the sequential composition property of LDP, the privacy budget, \(\epsilon\), is equally partitioned into \(m\) privacy budges, each of which is used to perturb each salient data in \(FS_{i}\). Formally, given \(FS_{i}\), let \(PFS_{i}=\{(t_{f_{1}},px_{f_{1}}),(t_{f_{2}},px_{f_{2}})\cdots(t_{f_{m}},px_{f_{ m}})\}\) be the corresponding perturbed salient data set. Here, \(px_{f_{h}}\) is obtained by adding random noise sampled from a Laplace distribution with mean \(\mu=0\) and scale \(sf=\frac{\Delta s}{\epsilon/m}\):  
\[px_{f_{h}}=x_{f_{h}}+Lap(\frac{\Delta s}{\epsilon/m}).\]  
This satisfies the \(\epsilon\)-differential privacy because \(\epsilon=\sum_{t=1}^{m}\epsilon/m\). The last step of wearable device processing is to send the perturbed salient data set, \(PFS_{i}\), to the data aggregation server. Note that, unlike the naive solution in Section 3.3, the proposed method is able to reduce the error caused by the perturbation mechanism of LDP by using the privacy budget \(\epsilon\) to perturb and report the small number of salient data instead of reporting the entire health data (i.e., \(m<n\)).
# Dimensional Errors Due to Overhanging Features in Laser Powder Bed Fusion Parts Made of Ti-6 Al-4V
## 3 Results and Discussion
### Data Processing and Analysis
Therefore, it can be concluded that the choice of scanning strategy plays a minimal role within the down-facing area;
* Looking at the trends in Figure 5a-c, it can be seen that the dimensional error for all scan patterns decreases with an increase in the scan speed and increases with an increase in the laser power, which is consistent with the trends that were seen in Figure 4;
* While looking at the effect of layer thickness in Figure 5d, it is clear that the dimensional error % increased with an increase in laser power, while it decreased while increasing the scan speed. However, with regards to the scan spacing in Figure 5f, the dimensional error % decreases at first, but at a level of around 80 \(\upmu\)m, it increases once again. Figure 5e shows that at both layer thicknesses, the dimensional error % decreases while increasing the scan speed. These observations can help us understand the effect of individual process parameters on the dimensional error and indicate the trend that is produced while varying the process parameters. ANOVA analysis was also conducted in order to get a deeper understanding of the significance of the process parameters on the dimensional accuracy, as it also considers the interaction effects. The results indicate that the laser power (P-Value = 0.00088723) is the most significant process parameter,  
Figure 4: Plots depicting the interaction effects of the laser power, scan speed, and scan spacing. Figure 5: Plots depicting the interaction effects of the scan strategy and layer thickness with the laser power, scan speed, and scan spacing. followed by the layer thickness (P-Value = 0.0032135) and scan speed (P-Value = 0.0048101). The next highest significance is given to the interaction effect of the laser power and scan speed (P-Value = 0.30819). These were the four most significant effects. It is also important to note that the scan strategy was determined to be one of the most insignificant parameters, with a P-Value of 0.94519. The information obtained from the ANOVA analysis and the effect plots seen in Figures 4 and 5 can help to determine the best process parameters that must be chosen for conducting further validation experiments and for actual optimization of the process itself. The regression equation was then used to generate the empirical prediction slice plots, as shown in Figure 6. The prediction slice plot shows the main effect of each process parameter and displays the estimated dimensional error percentage. The prediction slice plot can be used to determine the predicted dimensional error in a part at various process parameters, as well as scanning strategies and layer thicknesses. The plot was tested against the initial experimental results and its predictions were found to be a maximum of 5% away from the measured value. In the case of Figure 4, the equation predicted an error percentage of 4.8%, while the actual measured error percentage for this parameter combination was 2.02%.
_Appl. Sci._**2014**, \(4\), 240-254; doi:10.3390/app4020240  
_applied sciences_  
**ISSN 2076-3417**  
www.mdpi.com/journal/applsci  
**Mobilization of Toxic Elements from an Abandoned Manganese Mine in the Arid Metropolitan Las Vegas (NV, USA) Area**  
**[PERSON] 1, [PERSON] 1,*, [PERSON] 2 and [PERSON] 3**  
1 Department of Chemistry, University of Nevada, Las Vegas, NV 89154, USA;  
E-Mail: [EMAIL_ADDRESS]  
2 School of Community Health Sciences, University of Nevada, Las Vegas, NV 89154, USA;  
E-Mail: [EMAIL_ADDRESS]  
3 School of Environmental and Public Affairs, University of Nevada, Las Vegas, NV 89154, USA;  
E-Mail: [EMAIL_ADDRESS]  
* Authors to whom correspondence should be addressed; E-Mail: [EMAIL_ADDRESS];  
Tel.: +1-702-895-3845; Fax: +1-702-895-4072.  
_Received: 2 January 2014; in revised form: 21 April 2014 / Accepted: 23 April 2014 / Published: 12 May 2014_  
**Abstract:** Active and abandoned mines may present health risks, especially to children, from environmental exposure to airborne chemical elements, such as Pb, As, and Mn. X-ray fluorescence analysis of tailings at the Three Kids Mine show they contain high levels of: Pb (15,300 mg/kg), As (3690 mg/kg), and Mn (153,000 mg/kg). Soil was sampled along eight transects, radiating from the dried tailings ponds. Concentrations of Mn and Pb to the NE are at background concentrations at 4.8 km, and, As and Sr at 3.2 km from the mine. Going SW to the City of Henderson, all elements are at background at 1.6 cm, with the closest houses at 1.8 km. The United States Environmental Protection Agency (USEPA) Regional Screening Levels (RSLs) are exceeded for Pb, As and Mn at 0.8 km on all transects except one. The RSLs are exceeded for Pb, As and Mn on the NE transects at 1.6 km. Future home sites are on a NE transect between 0.4 km and 2.3 km downwind from the tailings ponds, in an area highly impacted by tailings which exceed the USEPA RSLs. This research demonstrates that there has been the farthest transport of tailings offsite by the prevailing winds to the NE; the closest currently-built homes have not received measurable tailings dust because they are upwind; and that precautions must be taken during the proposed remediation of the mine to restrict dust-transport of Pb, As, and Mn to avoid human exposure and ecological damage.  
keywords:abandoned manganese mine; tailings; X-ray fluorescence; lead; arsenic; manganese; strontium; EPA-RSL; transport +
Footnote †: journal: Journal of the American Chemical Society
## 4 Conclusions  
In this paper, a physical model was designed based on the real tectonic distribution and target reservoirs in the Tarim Basin, and the seismic profile response characteristics of short axis, low frequency, and strong amplitude in fractured carbonate reservoirs with different parameters were investigated. Although the signal-to-noise ratio of the physically modeled data was typically higher than that of real data, it could also provide a reference for recognizing seismic response characteristics. After the acquisition of the real data obtained from the physical model and seismic data processing, the reflected events of the designed strata and fractured reservoirs could be identified and were in the same position as the designed ones on the seismic stacking and migration profiles, which proved the validity and correctness of the construction of the physical model and the acquisition and processing of the seismic data. The effect of fracture reservoir groups with different parameters on the seismic response characteristics has been analyzed. For fractured reservoirs with different dipping angles, the difficulty of identification gradually increased with an increasing dipping angle, while the morphology of reflected events varied greatly. For fractured reservoirs with different numbers of fracture layers, the more layers there were, the lower the frequency was, while when the number of layers exceeded 15, the reflected event was slightly separated. In terms of planar attributes, the slope of reflection strength and maximum absolute amplitude attributes had a clear advantage for the identification of fractured reservoirs. It is worth mentioning that the maximum absolute amplitude attribute enabled the identification of fracture reservoirs located below the overlying strong reflections. For more complex conditions, more detailed and larger-size physical model design and fabrication can achieve a higher resolution of seismic data to investigate the seismic response characteristics of fractured carbonate reservoirs more precisely. These  
Figure 12: Attribute slices at the top of the Yingshan Formation. The attribute name is below the attribute.  
aspects represent the future needs of the petroleum industry and the direction of our further research.  
Methodology, L.W.; Investigation, L.W., B.D. and J.W.; Writing--original draft, L.W.; Writing--review & editing, B.D.; Supervision B.D. and J.W. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the National Natural Science Foundation of China (41804105) and the National Science & Technology Major Project (2017 ZX05005004).  
Data Availability Statement: Data is contained within the article.  
The authors declare no conflict of interest.
## 3 Case Study
### Data Pre-Processing
#### 3.2.2 Resampling  
According to the prediction target, this paper resamples the rainfall data and water depth data into a time series with 5 min as the time interval. The rainfall data is an hourly time series, so the interpolation method for its high frequency upsampling lacks practical significance, so this paper chooses to use the fill method to process the rainfall data. The short time interval of ponding depth data is suitable for downsampling the ponding time series by interpolation method. The commonly used interpolation methods are linear interpolation and cubic spline interpolation, etc. In order to avoid negative values in the interpolated time series, this paper chooses to use the linear method to process the ponding depth data.
# Numerical and Experimental Studies of the LK Type Shaped Charge
## 3 Experimental Method and Results
### Experimental Results  
Six shooting tests were performed, three for each type of charge, as shown in Figure 5.  
The shooting resulted in perforations of the steel plates loaded with a cumulative jet (see Figure 7a). Preliminary visual inspection showed that charges with axially (1A, 2A and 3A) induced explosive wave propagation were less effective, which was indicated by the lack of plate puncture--1A and 2A (see Figure 7b).  
Visual inspection of the armored plate was limited to the evaluation of entry and exit holes from the impact of the cumulative jet on the material of the armored plate being assessed. Such an example is shown in Figure 6, and values are summarized in Table 2. These results indicate that the jet was more regular with the peripheral charge. The diameter of the entrance hole was almost identical to the exit hole (see Figure 6c,d). However, for the axial charge, the jet formation was more disturbed. The entrance hole was significantly larger than the exit hole (see Figure 6a,b).  
This was confirmed by the measured diameters of the entry and exit holes (see Table 2) for the two types of shaped charge in 80 mm and 100 mm thick armor plates.  
Figure 4: Liner geometry.  
Figure 5: A way of loading the armor plate with a cumulative charge.  
Figure 6: Examples of results of the entry and the exit openings after a shot with a LK type shaped charge: (**a**) hole of axial charge entrance; (**b**) hole of axial charge exit; (**c**) hole of peripheral charge entrance; (**d**) hole of peripheral charge exit.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Specimens**} & \multicolumn{3}{c}{**Axial Charges**} & \multicolumn{3}{c}{**Peripheral Charges**} \\ \cline{2-9}  & **[mm]** & **1A** & **2A** & **3A** & **1P** & **2P** & **3P** \\ \hline \multirow{2}{*}{plate 100} & front & 21.2 & 22.7 & 23.0 & 12.9 & 14.1 & 13.2 \\  & back & None & None & 14.8 & 12.0 & 13.4 & 12.9 \\ \hline \multirow{2}{*}{plate 80} & front & 22.0 & 23.0 & 24.0 & 12.0 & 12.5 & 13.0 \\  & back & 15.3 & 16.0 & 15.0 & 11.7 & 12.3 & 12.8 \\ \hline \hline \end{tabular} Note--no perforation.  
\end{table}
Table 2: A list of the diameters of the entrance and exit holes from a shaped charge.
# Worldwide Connectivity for the Internet of Things Through LoRaWAN
## 4 How an End Device Joins a LoRaWAN(tm) Network
### Keys in an End Device after Joining the Network  
On top of the aforementioned keys, after the end device successfully joins a LoRaWAN(tm) network, the following additional set of keys are stored in the end device in a secure way:  
* the NwkSEncKey. It is used to encrypt the signaling traffic;
* the AppSKey. It is used to encrypt the end device user traffic;
* the SNwkSIntKey and FNwkSIntKey. They are used to calculated the message integrity code (MIC) for the signaling traffic;
* the JSIntKey. It is used to calculate the MIC for rejoin-request type 1 messages and join-accept answers;
* the JSEncKey. It is used to encrypt the join-accept triggered by a rejoin-request;
* the end device DevAddr. It consists of 32 bits and identifies the end device within the current network. The DevAddr is allocated by the NS of the end device.
# Enhancement of Underwater Images with Retinex Transmission Map and Adaptive Color Correction
## 3 Proposed Underwater Image Enhancement Method  
The proposed method follows the recovery formula in Equation (4), which requires the transmission map and the backscattered light to be estimated before performing recovery calculation. In addition, adaptive color correction is carried out subsequently to deal with possible low contrast and color shifts remaining in the output of the preliminary recovery calculation of Equation (4). Thus, the proposed underwater image enhancement method consists of four steps: retinex transmission map estimation, local backscattered light estimation, preliminary recovery and adaptive color correction.
## 3 Influence of PM and stator Arcs on Torque Production
### PM Arcs  
Figure 4 shows the influence of \(\theta_{sp}\) and \(\theta_{yp}\) on torque production for the multi-tooth HE-DSDPM. Figure 4a can be observed that the average torque increases when increasing \(\theta_{sp}\) between 3 and 25 degrees and gradually decreases when \(\theta_{sp}\) of 26 degrees is too large because the magnetic flux density at the air gap is reduced with a decrease in magnetic permeance. Meanwhile, the small \(\theta_{yp}\) between 1 and 3 degrees provides high average torque at large \(\theta_{sp}\) due to the reduction of flux refutation at the stator teeth region. In addition, the ripple torque variation with varying \(\theta_{sp}\) and \(\theta_{yp}\) is indicated in Figure 4b. The large \(\theta_{sp}\) between 20 and 32 degrees results in a lower ripple torque, while the \(\theta_{yp}\) has little influence on the ripple torque. The results exhibit that the \(\theta_{sp}\) has a higher significant effect on torque production than the \(\theta_{yp}\). In order to achieve high average torque and low ripple torque, the \(\theta_{sp}\) of 23 degrees and \(\theta_{yp}\) of 1.75 degrees are chosen as the best PM arcs because it produces good MMF and magnetic permeance around stator teeth and air gap of the proposed structure.
## 5 Conclusions  
Under micro-spray irrigation, maize yield and WUE were the highest in the JG treatment with 16,178.40 kg \(\text{hm}^{-2}\), 3.25 kg \(\text{m}^{-3}\), respectively, in which Y\({}_{\text{c}}\) was significantly lower than that in the NF and WG treatments. The three treatments showed no significant differences in ET\({}_{\text{c}}\). The water saving potential (including P\({}_{\text{y}}\) and S\({}_{\text{p}}\)) of maize was positively affected by Y\({}_{\text{c}}\) and negatively affected by grain yield and WUE. Therefore, values of P\({}_{\text{y}}\) and S\({}_{\text{p}}\) were the lowest in the JG treatment, were just 0.16 \(\text{m}^{3}\) kg\({}^{-1}\) and 2572.31 \(\text{m}^{3}\)\(\text{hm}^{-2}\), respectively, but no significant differences were found, compared to NF and WG treatments. The net economic profit of maize was negatively correlated with the water saving potential in all treatments, which was primarily responsible for the negative relationship between water saving potential and yield, WUE, respectively. So, the maximum of net economic profit appeared in the JG treatment, was up to 17,610.09 yuan \(\text{hm}^{-2}\), and was higher than that in the NF and WG treatments (\(p<\)0.05).  
The yield, WUE, and water saving capacity of the JG treatment were significantly higher than that of the NF and WG treatments. This suggests that straw mulding with micro-spray irrigation should be applied in local appropriate farmland. Given the lower WUE and higher water saving potential of the NF and WG treatments, it is important to explore these planting patterns further.  
**Author Contributions:** [PERSON] designed, performed the experiments, and wrote the original draft; [PERSON] analyzed the data; [PERSON] reviewed and edited the draft. All authors read the final manuscript and approved the submission. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was funded by the National Natural Science Foundation of China (Grant No. 41371053, 30972422, 51669034, 51809224), National key research and development project of China (Grant No. 2017 YFC0506706, 2017 YFC0504704) and Science research launch project of PhD (205040305).  
**Acknowledgments:** We are grateful to all the members of Naiman Desertification Research Station, Chinese Academy of Sciences, for their help in field work. We are also grateful to other anonymous reviewers for their valuable comments on the manuscript.  
**Conflicts of Interest:** The authors declare no competing interests.