In Ethiopia, soil erosion is a severe problem and a major cause of the decline of agricultural productivity. Interventions were taken by introducing soil and water conservation practices. However, ...the adoption of these practices is far below the expectation. The objective of this study was to examine factors affecting adoption of introduced soil and water conservation practices in Wereillu Woreda. Mixed research methods design was employed in order to conduct this study. Questionnaire, focus group discussion, in-depth interview and field observation were used to collect data. A binary logistic regression model was employed to analyze the collected data. The analysis result showed that sex of household heads, education status of household heads, access to extension services and training were positively correlated at significantly level with the adoption of the introduced soil and water conservation practices. On the other hand, the age of household heads, off-farm activity, and distance of farmlands from homesteads influenced the adoption of introduced soil and water conservation practices negatively. The finding depicts that the identified physical, socioeconomic, and institutional factors influence the adoption of soil and water conservation so, the Woreda Rural and Agricultural Development Office and other concerned bodies should consider these influential factors to enhance farmers’ adoption of introduced soil and water conservation practices and to promote agricultural productivity and environmental quality.
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•The size of the carbon sink across SWC has increased quadruply.•The contribution of CCR to the regional carbon sink was increasing.•Water and temperature controls on the karst carbon ...sink varied with the lithological background.
South-West China (SWC) is a pivotal region for global greening, recognized as having great carbon sink potential. Multiple evidence underscores the expanding contribution of SWC’s carbon sink to the global carbon sink enhancement. However, our understanding of carbon sink dynamics and the response to climate across bedrock remains limited. In this study, we investigated the divergence in trends in carbon sink across bedrocks, evaluating their respective contributions of bedrocks to the overall carbon sink in SWC. Additionally, we assessed the dominant climatic factors and examined how bedrocks shape the response of carbon sink to climate change. Our results revealed a notable increase in the regional carbon sink, with an average rate of 3.58 TgC/yr from 1981 to 2019. Continuous Carbonate Rocks (CCR) exhibited the highest increased rate of total carbon sequestration (1.57 TgC/yr), surpassing Discontinuous Carbonate Rocks (DCR) by threefold. Non-karst areas contributed the most to both the mean and interannual variations of the overall carbon sink, with CCR exerting the most contribution to the trends. Over time, the contribution of CCR to the overall carbon sink escalated, while the contributions of DCR and non-karst declined. All bedrocks displayed negative correlations between NEP and temperature, with DCR showing higher susceptibility. Non-karst areas experienced adverse impacts from vapor pressure deficit, while CCR benefited from positive soil moisture effects. Our findings implied that bedrock indeed played a critical role in the variations in NEP and the response of NEP to climate change. Bedrock regulated climatic controls on carbon sink through soil water availability as soil water availability is affected by the lithology of basement carbonate. This novel understanding emphasizes the necessity for tailored ecological restoration initiatives that consider the distinctive lithological features of the karst ecosystem, and holds significance for implementing ecologically sound projects in karst regions.
Soil water content (SWC) is significant for understanding and evaluating the conditions of soils and plants. Since traditional methods such as time domain reflectometry (TDR) and neutron probes have ...significant drawbacks such as limitations in spatial resolution, detection depth, efficiency, and non-destruction, ground penetrating radar (GPR) has become a potential method in SWC estimation. Many features extracted from GPR data in the time and frequency domain have been proven to be sensitive to the SWC and can further achieve the estimation of it. However, the methods based on these features are easy to be interfered with by noise and the heterogeneity in soils. This article aims to solve this problem by including more features and integrating these features for a joint estimation. Firstly, we study the relationships between SWC and seven features extracted from GPR data. Consequently, we propose to include new features, i.e. the loss tangent feature and the time-frequency features, in the SWC inversion. Secondly, we achieve the multi-feature ensemble learning based on the Adaboost R. method, which largely enhances the accuracy of SWC inversions compared to the single-feature estimations. During the numerical test, we establish the stochastic medium to model the heterogeneity in the real soil. The test verifies the effectiveness and the robustness of the proposed method. Finally, a field experiment is performed on the transition zone of no-tillage and deep-ploughing croplands. A 2-D SWC map is obtained which distinctly presents the SWC difference between the two regions. Our study provides a new approach to improve the accuracy of SWC estimation using GPR.
•A multi-feature ensemble learning method is proposed to inverse soil water content.•Loss tangent is used for the inversion of soil water content.•A two-dimensional soil water content map of a cropland is obtained.•Soil water content in no-tillage and deep-ploughing zones are strongly different.
•Topographic wetness indexes (TWIs) and Ellenberg’s indicator value (EIV) were used.•All used TWI algorithms explain soil moisture better than the average EIV.•The highest explanatory value resulted ...from the MFD-md algorithm.•The inclusion of soil water capacity (SWC) enhanced the performance of TWIs and EIV.•TWI remains a better predictor than EIV even when the latter was enhanced by SWC.
Topography is an important determinant of soil moisture (SM) distribution and thus drives the functioning of terrestrial ecosystems, including vegetation composition and structure. To assess soil water spatial variability, a number of indices have been used. In this study, we compared the ability of the topographic wetness index (TWI) and Ellenberg’s indicator values (EIV) for moisture to explain the spatial variation of SM in central European forests. Further, we tested the potential heat load (HL) and soil water capacity (SWC) as additional factors that could improve the regressions between TWI and SM as well as EIV and SM. TWI was calculated using 10 different flow routing algorithms. The average EIV for moisture was calculated on the basis of the presence/absence of plant species. We observed that the flow routing algorithms explain SM variability better than the average EIV. The strongest relationship between TWI and SM was obtained by the MFD-md algorithm. The inclusion of SWC increased the explanatory power of both TWI and EIV. On the other hand, HL did not improve the regressions. The relative increase in the explanatory ability by SWC was particularly pronounced in case of EIV. We interpreted this to be a result of the fact that EIV reflect the synergistic effect of multiple environmental gradients on plant distribution. TWI calculated by any of the flow routing algorithms remains a better explanatory factor of SM than EIV, even if the latter was enhanced by the addition of SWC.
•A smartphone and free motion analysis software can measure jump height accurately.•Low-cost instruments are a valid alternative to laboratory-based equipment.•Vertical jump tests measure ...physiological and biomechanical parameters.•The smartphone-kinovea method can detect changes over the noise of the measure.
Jumping is a simple exercise determined by several biomechanical and physiological factors. Measures of vertical jump height are common and easy to administer tests of lower limb muscle power that are carried out with several types of equipment. This study aimed to validate and address the usefulness of the combination of smartphone and computer-based applications (Smartphone-Kinovea) against a laboratory-based Motion Capture System. One hundred and twelve healthy adults performed three maximal-effort countermovement jumps each. Both instruments measured the heights of the 336 trials concurrently while tracking the excursion of the body center of gravity. The vertical velocity at take-off vto and the impulse J were computed with jump height h measures. Intraclass correlation coefficient (ICC) results indicated very high agreement for h and vto (0.985) and almost perfect agreement for J (0.997), and Cronbach's α=0.99. Low mean differences were observed between instruments for h: -0.22 ± 1.15 cm, vto: -0.01 ± 0.04 m/s, and J: -0.56 ± 2.92 Ns, all p<0.01. The smallest worthwhile change (SWC) and the typical error of measurement (SEM) were 1.34 cm, 0.81 cm for h; 1.15 m/s, 0.03 m/s for vto, and 2.93 Ns, 2.25 Ns for J, so the usefulness of the method is established (SWC/SEM>1). Bland-Altman plots showed very low mean systematic bias ± random errors (-0.22 ± 2.25 cm; -0.01 ± 0.08 m/s; -0.56 ± 5.73 Ns), without association between their magnitudes (r2=0.005, r2=0.005, r2=0.001). Finally, very high to practically perfect correlation between isntruments were observed (r = 0.985; r = 0.986; r = 0.997). Our results suggest that the Smartphone-Kinovea method is a valid and reliable, low-cost instrument to monitor changes in jump performance in a healthy, active population diverse in gender and physical condition.
A decrease in soil water content (SWC) has been observed at the global scale and has led to a reduction in evapotranspiration (ET). However, the trend in SWC in eastern Asia differed from the global ...trend, and this may be due to the overlapping of warm/wet seasons. Because of the limitation of deep soil water content data, especially in drylands, changes in SWC and the correlation between SWC (particularly deep SWC) and ET remain poorly understood. In this study, spatial distribution of correlation coefficient (r) between SWC and ET were calculated based on reanalysis data and remote sensing data, which were validated by in situ data (2004–2005) and sampling data (2016–2017). Firstly, the correlation between SWC and ET decreased with soil depth. The depth of the sharp decrease was 10 cm based on in situ monitoring data (2005–2008) and spatial sampling data (2016–2017). Secondly, the spatial correlation between SWC and ET varied with different vegetation cover types. The correlation increased from the western typical steppe to the eastern forest. The highest values of r were in a forest-covered area, because it had the highest water uptake capacity. However, the difference between r_10 and r_100 (D_r) showed a different spatial pattern, and the lowest negative D_r value was obtained from a forest–grass transition zone in which the enhanced vegetation index showed a significant increasing trend. The significant negative regression determination coefficient (R2 = 0.9, p < 0.01) between B_EVI (0–0.1) and D_r indicated that the narrowed D_r in the transition zone was due to the vegetation increase. This meant that more deep soil water was taken up into the atmosphere. Thus, the deep SWC could become unstable and deep soil could become drier, which would be unsustainable for the ecosystem.
Vertical jump performance is a commonly used test to measure lower-limb muscle power that is carried out with several types of equipment. The aim of this study was to validate an open-source jump mat ...(Chronojump Boscosystems) against a proprietary jump mat (Globus Ergo Tester). Sixty-three active sportsmen (age 23.3 ± 2.4 years) completed 8 maximal-effort countermovement jumps (CMJ). The heights of the 504 CMJ were measured from the two jump mats simultaneously. Reliability was examined with intra-class correlation coefficients (ICC), paired samples t-tests, coefficient of variation (CV) and Cronbach’s α. Bivariate Pearson’s correlation coefficient (r) was used to examine validity. Effects were evaluated using non-clinical magnitudebased inference. There was almost perfect agreement between instruments (ICC = 0.999−1.000, most likely positive 100/0/0). Paired t-test showed a mean difference of 0.03 ± 0.21 cm (90% CI -0.04 − -0.01) between
The Smart Contract Weakness Classification Registry (SWC Registry) is a widely recognized list of smart contract weaknesses specific to the Ethereum platform. Despite the SWC Registry not being ...updated with new entries since 2020, the sustained development of smart contract analysis tools for detecting SWC-listed weaknesses highlights their ongoing significance in the field. However, evaluating these tools has proven challenging due to the absence of a large, unbiased, real-world dataset. To address this problem, we aim to build a large-scale SWC weakness dataset from real-world DApp projects. We recruited 22 participants and spent 44 person-months analyzing 1,199 open-source audit reports from 29 security teams. In total, we identified 9,154 weaknesses and developed two distinct datasets, i.e., DAppSCAN-Source and DAppSCAN-Bytecode . The DAppSCAN-Source dataset comprises 39,904 Solidity files, featuring 1,618 SWC weaknesses sourced from 682 real-world DApp projects. However, the Solidity files in this dataset may not be directly compilable for further analysis. To facilitate automated analysis, we developed a tool capable of automatically identifying dependency relationships within DApp projects and completing missing public libraries. Using this tool, we created DAppSCAN-Bytecode dataset, which consists of 6,665 compiled smart contract with 888 SWC weaknesses. Based on DAppSCAN-Bytecode , we conducted an empirical study to evaluate the performance of state-of-the-art smart contract weakness detection tools. The evaluation results revealed sub-par performance for these tools in terms of both effectiveness and success detection rate, indicating that future development should prioritize real-world datasets over simplistic toy contracts.
The sustainability of the ongoing national Campaign-Based Watershed Management (CBWM) program of Ethiopia depends on active participation of farmers in the planning and implementation activities. ...This study analyzes farmers’ participation level in CBWM program and factors that determine their participation, using mixed research methods. Key informant interviews were conducted with 29 purposively selected actors (excluding farmers) to discern their decision-making processes and to gain insight into the factors influencing farmers' participation in the program. Additionally, individual case studies were conducted with 15 farmers to explore their personal experiences. Furthermore, a household survey was administered to 351 households to explain key factors shaping their decisions to participate in the program. Our study shows that the farmers’ level of participation in the CBWM program was quite low (53.0%). Compared to the implementation and post-implementation stages, the level of participation was lowest at the planning stage of the program. Three key factors influenced the farmers’ level of participation in the program: location or proximity of farmers to the micro-watersheds during campaign works, the commitment of local leaders, and awareness and motivation of farmers. This suggests the need to (1) focus on smaller watersheds to minimize the effect of distance between farmers’ homesteads and the micro-watersheds, (2) include local livelihood opportunities to mitigate the impact of location or out-migration and ensure their availability for campaign works, (3) enhance the performance/commitment of local leaders, (4) improve farmers’ awareness and motivation through capacity building. However, given that the effect of these factors varies across the studied villages and stages of the program, a more bottom-up planning approach that considers socio-economic and biophysical contexts should be introduced in the study area and other similar localities where watershed management activities are carried out through community participation.
•The national Campaign-Based Watershed Management program of Ethiopia can only be sustainable through community participation.•Analyzing factors that influence farmers’ participation is essential to explore sustainable watershed management strategies.•Farmers’ participation was influenced by their location, awareness, and motivation, and the commitment of local government.•Capacity building of key actors and bottom-up planning are crucial to ensure the sustainability of the program.
This work proposes the development of a novel sensor comprising a rectangular microstrip antenna enclosed within a small cubic container made of acrylonitrile-butadiene-styrene (ABS). A complementary ...split ring resonator (CSRR) has been incorporated into the antenna, endowing it with two resonance frequencies within the desired range. The sensor is designed to determine the soil water content (SWC) of various soil types. The operational principle relies on the modulation of two resonance frequencies of the antenna due to changes in the relative permittivity of the material under test (MUT). The sensor’s sensitivity was thoroughly examined and compared with various sensors documented in the literature. Additionally, an electric field analysis was conducted, revealing that optimizing the dimensions of the CSRR can enhance its sensitivity. Consequently, the proposed sensor exhibited superior sensitivity compared to other sensors reported in the literature.
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•Sensitivity analysis of the proposed Compact CSRR-Based sensor.•The optimization of the sensor based in the electromagnetic fields’ analysis.•The analysis of dielectric properties of two different types of soil.•Determination of soil water content with the proposed sensor and fitted equations.•Improvement of the sensitivity compared with the other systems presented.
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