esa-sceva/satcom-chunk-collection huggingface dataset:
# Short-Term Effects of Pine Plantations on Vegetation and Soil in Northern Mongolia
## 4 Discussion
The documented reduction in soil organic carbon with increasing soil depth underscores the significance of surface soil layers in carbon sequestration, corroborated by worldwide soil profile investigations [70]. Plantation stands (e.g., BBS, MGS) likely enhance soil organic carbon (SOC) levels by augmenting litterfall and diminishing competition among trees, as observed by the user. This corresponds with observations that plantation can augment soil organic matter inputs and enhance soil quality indices [71]. The relationship between soil moisture and SOC dynamics underscores the significance of water availability in carbon sequestration. For instance, BBS, exhibiting elevated soil moisture (SM = 7.65 \(\pm\) 0.73%), also demonstrates the greatest levels of SOC. This association aligns with research indicating that soil moisture favorably affects SOC buildup by enhancing microbial activity and organic matter breakdown [71]. The findings endorse the utilization of planted forests as carbon farming zones, especially in degraded environments such as steppes (STP). Policies that advocate for afforestation and reforestation can elevate soil organic carbon levels and aid in achieving carbon sequestration objectives under frameworks such as the Paris Agreement. Plantation and soil moisture management must be incorporated into forest management plans to enhance SOC levels and carbon sequestration. The favorable correlation between soil organic carbon (SOC) and tree diversity emphasizes the necessity of reconciling biodiversity protection with carbon sequestration initiatives. Mixed-species plantations can fulfil both goals. The investigation underscores the essential function of plantation forests in augmenting soil organic carbon levels and facilitating carbon sequestration. The identified trends in the plots offer significant insights for carbon farming and silvicultural management, in accordance with global climate change mitigation strategies. Subsequent studies ought to concentrate on refining these approaches to enhance carbon sequestration and biodiversity preservation. We will require the implementation outlined below: Initial planting density: determined by site characteristics and management objectives. Thinning schedule: adjusted according to crown competition and understory growth. Monitoring protocol: systematic evaluation of essential indicators. Adaptive management: a flexible approach to evolving circumstances. Future study necessitates long-term monitoring of growth responses to varying densities, understory development patterns, alterations in soil properties, and the implications of climate change. Furthermore investigated should be the financial consequences of carbon sequestration possibilities, biodiversity preservation successes, and delivery of ecosystem services. These suggestions establish a framework for effective forest management, recognizing the necessity for site-specific modifications and continuous study to enhance strategies in response to evolving problems and possibilities.
# Detecting Anatomical Leg Length Discrepancy Using the Plug-in-Gait Model
###### Abstract  
Leg length discrepancy (LLD) is a significant factor influencing several pathological conditions. Gait analysis is based on biomechanical gait models calculating joint kinematics; however, no previous study has validated its ability to detect anatomical LLD. The aim of the present study was to compare the validity of the Vicon(r) Plug-in-Gait-model (PGM) in measuring femur and tibia segmental length discrepancy with measurements attained by X-ray. Fifteen participants with suspected leg length discrepancies underwent a lower limb X-ray and a standing calibration trial using a motion analysis system (Vicon(r), Oxford Metrics, UK). Femur and tibia segment lengths were deducted from both measurements. No differences were found when measuring the discrepancies between sides for the femur (\(p=0.3\)) and tibia (\(p=0.45\)) segmental length. A high correlation was found between methods (r = 0.808-0.962, \(p<0.001\)), however, a significant difference was observed when measuring the femur and tibia length (\(p<0.0001\)). PGM was found to be a valid model in detecting segmental length discrepancy when based on the location of the joint centers compared to X-ray. A variance was noted in the femur and tibial segmental length. The impact of this inconsistency in segmental length on kinematics and kinetics should be further evaluated.  
Keywords:gait model; Plug-in-Gait; joint center; segmental length +
Footnote †: journal: Applied Sciences
# Superimposed Perfect Binary Array-Aided Channel Estimation for OTFS Systems
## 6 Conclusions  
In this paper, we propose a superimposed PBA-aided channel estimation method with high SE for OTFS systems. In the proposed method, a PBA is superimposed onto data symbols as the pilot in the DD domain. By exploiting the perfect autocorrelation of PBA, channel estimation is performed through linear search and a threshold-based method. The delay-Doppler indices and complex gains of channels are estimated in the same frame, so the SPBA method has better delay-Doppler varying adaptability. Additionally, the optimal power of the superimposed PBA is derived to maximize SE. The results of analyses and simulations show that despite a slight BER degradation, the proposed SPBA-OTFS method significantly improves the SE.  
Conceptualization, Z.T. and H.K.; methodology, Z.T., H.K. and J.W.; software, H.K. and Z.W.; validation, H.K. and Z.W.; formal analysis, Z.T., H.K. and Z.W.; investigation, H.K.; resources, J.W.; data curation, H.K. and Z.W.; writing--original draft preparation, Z.T. and H.K.; writing--review and editing, Z.T., H.K., Z.W. and J.W.; visualization, H.K. and Z.W.; supervision, Z.T. and J.W.; project administration, J.W.; funding acquisition, J.W. All authors have read and agreed to the published version of the manuscript.  
This research was supported by the Key Research and Development Program of Hubei Province under Grant 2022 BID017 and the Key-Area Research and Development Program of Guangdong Province under Grant 2019B010158001.  
Not applicable.
# Numerical Study on the Yaw Control for Two Wind Turbines under Different Spacings
## 4 Results
### Average Output Power Analysis  
In order to evaluate the total output power of two turbines clearly, the average output power of the turbines will be analyzed in this section as shown in Figure 9.  
Figure 8: Standard deviations of the power fluctuation of WT2 under various working conditions.  
Figure 9: Average output power of the turbines.  
When the yaw angle increases from 0\({}^{\circ}\) to 30\({}^{\circ}\), the output power of WT1 gradually decreases while the output power of WT2 increases. In the range of 0\({}^{\circ}\) to 20\({}^{\circ}\), the total power of two turbines shows an upward trend. When the yaw angle increases from 20\({}^{\circ}\) to 30\({}^{\circ}\), the total power of two turbines with the spacing of 5D, 6D and 7D still increases, but it does not change significantly when the spacing is 8D.  
The relationship between total power and the spacing of two turbines is also discussed here in different yaw angles. It can be found that when the yaw angle is 0\({}^{\circ}\), the total power does not increase significantly when the spacing between two turbines increases from 5D to 8D. At the yaw angle of 0\({}^{\circ}\), WT2 has a large loss of output power as a result of being fully affected by the wake of the upstream turbine.  
When the yaw angles are 10\({}^{\circ}\) and 20\({}^{\circ}\), there is a significant increase in the total power from 5D to 6D. Then, the improvement of the total power is not obvious from 6D to 7D, but the total power increases again from 7D to 8D. When the yaw angle is 30\({}^{\circ}\), the total power increases slightly with the increase in spacing. Under the fixed spacing, the yaw control of WT1 has a significant impact on the increase in the total power. For the 5D, 6D, 7D and 8D cases, the total power with a 30\({}^{\circ}\) yaw angle increases by 18.31%, 19.20%, 21.29% and 21.99%, respectively, compared to a 0\({}^{\circ}\) yaw angle. However, at the same time, it can be found that the increase in yaw angle does not have a simple monotonic relationship with the increase in total power. When the spacing is 8D, the total power under the yaw angle of 20\({}^{\circ}\) and 30\({}^{\circ}\) is similar, this phenomenon can also be found in the study of [PERSON] [31]. For the 0\({}^{\circ}\), 10\({}^{\circ}\), 20\({}^{\circ}\) and 30\({}^{\circ}\) cases, the total power with a 8D spacing increases by 1.45%, 4.93%, 8.26% and 4.61%, respectively, compared to a 5D spacing, the increase in spacing has the most obvious effect on the increase in total power under 20\({}^{\circ}\) cases. In general, the total power of two turbines is related to the yaw control of WT1 and the spacing. When the spacing is within 8D, the yaw control of WT1 plays a more significant role in improving the total power.
# Smart Antenna for Application in UAVs
## 5 Construction and Implementation of the Smart Antenna
### Experimental Results  
The experimental results of the antenna were obtained in the anechoic chamber of the scientific area of the Institute of Telecommunications at IST because technical limitations were the only available conditions to measure the S11 (reflection coefficient of the antenna) and the radiation diagram of the antenna (Figures 20-24).  
The combinations of the used diodes can be seen in Table 10.  
Figure 23: Representation of the radiation diagram for 0\({}^{\circ}\) in the E plane.  
Figure 21: Representation of the radiation diagram for 0\({}^{\circ}\) in the H plane.  
Figure 22: Comparison of the radiation diagram to \(\pm\) 5\({}^{\circ}\) in the H plane.  
Starting with the analysis of the \(|\)S11\(|\) parameter, it was possible to verify that the resonance frequency was very close to the frequency in which antenna design was carried out, that is, the measured value was 1.41 GHz, and the antenna was dimensioned for 1.33 GHz. To correct this small deviation, it would be necessary to study the behavior of the resonance frequency with slight changes of distances 0 in the patch.  
Regarding the tax requirement of \(|\)S11\(|\)\(\leq-10\) dB, this was not observed in the results obtained through the network analyzer. In the results obtained through the simulator, the requirement was always fulfilled by a comfortable margin, so it would be necessary to correct the height of the hg air layer and to verify, through the network analyzer, the variations of the parameter \(|\)S11\(|\). The height of the air layer was not constant throughout the antenna since it is impossible to obtain the accuracy imposed by the simulation.  
In addition to the hg correction, there was still interference caused by power cables with a length approximately equal to \(\lambda/2\). During the scanning from 0 to 2 GHz, it was possible to observe the interference caused by the cables.  
Analyzing the radiation diagram, it was possible to verify that the radiation lobe of the P-ESPAR antenna was displaced \(-6^{\circ}\) in relation to the expected azimuth. This variation corresponds to the side on which the power cables were placed, so they could be responsible for this small deviation.  
In relation to the azimuthal variation of \(\pm 5^{\circ}\) with \(0^{\circ}\) azimuth, extremely positive results were obtained.  
Inspecting the results, it was possible to verify that the variation range of the main lobe was between \(-11^{\circ}\) and \(-2^{\circ}\).  
These results summarized in Table 11 prove that the measured results go against the simulated ones, this being because there are integrated elements in the antenna that the simulator does not allow to consider. However, it is possible to improve the obtained results with minor changes to the insulation of the feed paths of the P-ESPAR antenna diodes and by reducing the length of the cables of the diode feed system.
# Ballast Flow Characteristics of Discharging Pipeline in Shield Slurry System
## 4 Ballast-Carrying Performance and Distribution State in Slurry System
### Influence Law of Ballast Mass Flow Rate  
The ballast mass flow rate \(K_{m}\) in the inclined, the horizontal, and the vertical sections is the same based on the statistical data when the ballast transportation in the slurry pipeline system enters a steady state. The main factors influencing \(K_{m}\) are slurry flow rate and ballast volumetric concentration, whereas the ballast size has little influence. When the ballast size is 32 mm, the rule of the influence of slurry flow rate on \(K_{m}\) is as shown in Figure 11a. When the slurry flow rate increased from 636 to 1400 m\({}^{3}\)/h, we observed a linear growth trend under different ballast volumetric concentrations, increasing by 40%, 79%, and 120%, respectively. When \(C_{v}\) was 6%, \(K_{m}\) increased from 31.1 to 68.4 kg/s, showing the greatest increase. Figure 11b shows the influence rule of the ballast volumetric concentration on \(K_{m}\) under the same working conditions. Similar to the slurry flow rate influence law, increasing ballast volumetric concentration also shows a linear growth trend with \(K_{m}\). When ballast volumetric concentration increased from 1.5% to 6%, \(K_{m}\) increased by 104%, 210%, and 322% under different slurry flow rate conditions. Among them, when the \(Q\) was 1400 m\({}^{3}\)/h, \(K_{m}\) increased from 16.2 to 68.4 kg/s, reflecting the maximum increase. By comparing the slurry flow rate and the ballast volumetric concentration, we found that both can improve the mass flow rate.  
Figure 11: Factors influencing ballast mass flow rate: (**a**) the effect of the slurry flow rate and (**b**) the effect of ballast volumetric concentration.  
Figure 10: Schematic diagram of monitoring surface for each pipe section.
## 3 Results and Discussion  
### Mean Annual Precipitation  
The interpolated maps of mean annual precipitation (MAP), using gauge observations and estimates from the different precipitation products, are displayed in Figure 2. The observed MAP for Malaysia was 2852 mm/year, with a maximum value of more than 4800 mm/year recorded by a rain gauge in southern EM and a minimum of about 500 mm/year in middle PM (Figure 2g). PM exhibited a trend for MAP to decrease from the east coast to the southwest. High precipitation (1300 to 4500 mm/year) was also found in the eastern and western PM. \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Time Scale**} & \multicolumn{2}{c}{**3B42 RT**} & \multicolumn{2}{c}{**3B42V7**} & \multicolumn{2}{c}{**GPCP-1 DD**} & \multicolumn{2}{c}{**PERSIANN-CDR**} & \multicolumn{2}{c}{**CMORPH**} & \multicolumn{2}{c}{**APHRODITE**} \\ \cline{2-11}  & **t stat** & \(p\) & **t stat** & \(p\) & **t stat** & \(p\) & **t stat** & \(p\) & **t stat** & \(p\) \\ \hline Annual & \(-\)1.84 & \(-\)4.61 & * & 2.91 & * & \(-\)2.21 & * & 12.15 & * & 20.92 & * \\ NEM & \(-\)0.09 & \(-\)3.62 & * & 8.63 & * & 4.31 & * & 22.02 & * & 20.03 & * \\ SWM & \(-\)0.42 & \(-\)6.98 & * & \(-\)4.01 & * & \(-\)10.51 & * & 3.78 & * & 20.97 & * \\ Monthly & \(-\)3.06 & * & \(-\)7.45 & * & 4.87 & * & \(-\)3.66 & * & 21.66 & * & 34.58 & * \\ Daily & \(-\)5.41 & * & \(-\)12.25 & * & 8.60 & * & \(-\)6.68 & * & 38.43 & * & 62.69 & * \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Student’s _t_-test analysis of observed and estimated precipitations. \(P\) is the significant level, * represents significance at 0.05. Table 3 presents the Student's _t_-test analysis of the daily, monthly, seasonal, and annual precipitation (2003-2007) between precipitation products and 342 rain gauges. All precipitation products exhibited significant differences with observations at \(p\) < 0.05, except the 3B42 RT. APHRODITE showed the best performance for annual precipitations with a value of R\({}^{2}\) = 0.46, followed by the 3B42V7 (R\({}^{2}\) = 0.45), CMORPH (R\({}^{2}\) = 0.33), 3B42 RT (R\({}^{2}\) = 0.32), PERSIANN-CDR (R\({}^{2}\) = 0.31), and GPCP-1 DD (R\({}^{2}\) = 0.25) (Table 4). The 3B42 RT, 3B42V7, and PERSIANN-CDR slightly overestimated MAP, while GPCP-1 DD showed slight underestimations. By contrast, APHRODITE and CMORPH were characterized by large underestimation of annual precipitation, by 19.7% and 13.2%, respectively. Over the study period, 3B32V7 performed the best, while GPCP-1 DD performed the worst (Figure 2). Moreover, a MAP underestimation was observed along the coastline regions for most of the SPPs, with the exception of 3B42V7. This might be due to the poor performance of precipitation detection over water/land mixed cells as previously pointed out by [PERSON] _et al._[35].
## 2 Materials and Methods
### Preparation for Electron Microscope Investigation  
Scanning electron microscopy (SEM) imaging provides a relatively quick and straightforward method for assessing cell coverage on surfaces, though it requires several days of sample preparation. After 3 to 5 days of incubation, the samples were retrieved and prepared for SEM analysis. The preparation process involved rinsing the samples with phosphate-buffered saline (PBS), followed by fixation in 6.25% glutaraldehyde (SERVA Electrophoresis GmbH, Heidelberg, Germany) in PBS overnight. The samples were then dehydrated through a graded ethanol series, and final drying was performed using hexamethyldisilazane (HMDS, Carl Roth GmbH + Co. KG, Karlsruhe, Germany) overnight to prevent the deformation and shrinkage of the structures. Once dried, the samples were sputter-coated with a gold layer for 80 s at 22 mA. The coated samples were subsequently examined using a scanning electron microscope (1540 XB, Zeiss, Oberkochen, Germany) at an acceleration voltage of 5 kV. Control samples without cells were only sputter-coated with gold and directly analyzed with SEM.
# Improved Simplified Engineering Fault Displacement Hazard Evaluation Method for On-Fault Sites
## 2 Development of the Improved, Simplified Hazard Evaluation Method
### Geometrical Conditions for the Sites on the Mapped Fault Line
In [5], the ratio of the rupture length to the mapped fault length is assumed for the conditional probability of the rupture intersecting the site, \(P(intersecting\ the\ site|L)=L/FL\), and the total probability for intersecting the site is calculated as \(P(intersects\ the\ site|L)=\sum\limits_{i}P(intersects\ the\ site|L)P(L_{i}|m_{i})\). The summation is over the elementary intervals within \([m_{0},\ m_{u}]\). It means that all ruptures in the interval \([\ L_{min}(m_{0}),\ L_{max}(m_{u})]\) are accounted for. Compared to this, the above screening procedure reduces the number of ruptures crossing the site due to the geometrical limitations. Consequently, the conditional probability for intersecting the site is less than \(P(x_{i},\ x_{s},L,\ FL)\ll P(intersecting\ the\ site|L)=L/FL\), which will be shown below.
## 2 State of the Art
PLC networks are under the permanent influence of two noise components: external/background  
Figure 1: Power grid network with communication technologies typical for low voltage (LV), medium voltage (MV) and high voltage (HV). noise and impulsive noise with both periodic and aperiodic components introduced by noisy loads or switching devices [40; 43]. Impulsive noise influences PLC networks significantly, so minimizing its impact has crucial influence on the performance of the whole network [44]. In some cases the noise effect might be minimized by using a phase-to-phase signaling scheme instead of traditional phase-to-ground systems, as stated in [45]. The time variance of a power line and its impact on communication is further described in [46; 47; 48; 49; 50; 51]. PLC devices during their operation also radiate into nearby areas, so the device itself has to meet current EMC (Electromagnetic compatibility) regulation limits [52]. Utility equipment related RF noise (the source of this type of noise normally must be identified, and the device or component causing the noise must be replaced) typically has a high amplitude and spans a significant section of the BPL-usable spectrum (broadband noise). A field trial revealed that most of the MV line noise causing low signal-to-noise ratios was generated by utility equipment, components or devices [53]. Unfortunately, there is not a simple formula that would easily determine the need to involve repeaters in the powerline network. Such knowledge would help in establishing locations of nodes, where deployment of repeaters would be vital for successful operation. Sufficient data throughput, low latency and no need for extra devices would be extremely beneficial.
# A Lightweight Secure and Energy-Efficient Fog-Based Routing Protocol for Constraint Sensors Network
## 5 Conclusions  
In recent decades, IoT sensors and WSN have been merged to provide rapid routing performance for network users. The limited resources on sensor nodes impose significant optimization problems in terms of network lifetime and data security for both academic and industrial domains. This paper presents the lightweight secure and energy-efficient fog-based routing protocol for constraint sensor networks, which uses a dynamic threshold using multiple parameters for the selection of cluster heads with minimum transmission overhead. Moreover, it uses the multi-facet QoS attributes for the selection of next-hop from the observing area to fog layer with minimum energy consumption and delay rate. The SEFR protocol also ensures two levels of security using cryptographic-based secret keys using the Blum Blum Shub algorithm, that increases the trustworthiness. The results of the SEFR protocol demonstrated that it improves the performance of the constraint-oriented network in terms of energy consumption and network throughput. Also, it decreases the chances of packet drop ratio and data latency with nominal communication overheads. In the future, we aim to offer fog computing with intelligent data management based on machine learning techniques to facilitate real-time applications with the least processing cost. Also, the security level has to be investigated in terms of the distributed threats model.  
Conceptualization, K.H. and N.I.; Methodology, K.H. and N.I.; Software, K.H.; Validation, Y.J., U.T.; Formal Analysis, K.H.; Investigation, N.I.; Resources, Y.J.; Data Curation, U.T.; Writing--Original Draft Preparation, K.H.; Writing--Review & Editing, U.T.; Visualization, N.I.; Supervision, U.T.; Project Administration, Y.J.; Funding Acquisition, Y.J. All authors have read and agreed to the published version of the manuscript.  
The authors would like to acknowledge the support of Prince Sultan University for paying the Article Processing Charges (APC) of this publication.  
The authors declare no conflict of interest.