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•Nexus between agricultural nitrous oxide emissions and natural resource scarcity.•Top-emitting countries are negatively affected by natural resource scarcity.•Agriculture, forestry, ...fishing, and natural resource scarcity correlate positively.•Evaluation of resource scarcity through fossil fuel consumption.
Natural resource scarcity, fossil fuel energy consumption, and total greenhouse gas emissions are critical issues that require immediate attention. With the global population steadily increasing and economies expanding, the demand for natural resources, particularly fossil fuels, has experienced an unprecedented surge. This surge in consumption is directly linked to the alarming rise in greenhouse gas emissions. The study examines the nexus between agricultural nitrous oxide emissions and natural resource scarcity, taking into account the dynamics of agriculture, forestry, fishing value addition, fossil fuels, and total greenhouse gas emissions in top-emitting countries between 1971 and 2020. Natural resource scarcity positively correlates with agriculture, forestry, fishing, fossil fuel energy consumption, and total greenhouse gas emissions. There is a decrease in natural resource scarcity in countries that emit agricultural nitrous oxide, forestry, fishing emissions, fossil fuel energy consumption, and greenhouse gas emissions. Policy-makers may promote sustainable development, mitigate climate change, and ensure the long-term viability of agricultural systems by addressing the dynamics of agriculture, forestry, and fishing value addition in top-emitting countries. Through strategic policy interventions, supported by technology transfer, capacity building, and market-based instruments, the agricultural, forestry, and fishing sector can achieve a more sustainable future while addressing the challenges of natural resource scarcity.
Crowdsourced Data Management: A Survey Guoliang Li; Jiannan Wang; Yudian Zheng ...
IEEE transactions on knowledge and data engineering,
2016-Sept.-1, 2016-9-1, 20160901, Volume:
28, Issue:
9
Journal Article
Peer reviewed
Any important data management and analytics tasks cannot be completely addressed by automated processes. These tasks, such as entity resolution, sentiment analysis, and image recognition can be ...enhanced through the use of human cognitive ability. Crowdsouring platforms are an effective way to harness the capabilities of people (i.e., the crowd) to apply human computation for such tasks. Thus, crowdsourced data management has become an area of increasing interest in research and industry. We identify three important problems in crowdsourced data management. (1) Quality Control: Workers may return noisy or incorrect results so effective techniques are required to achieve high quality; (2) Cost Control: The crowd is not free, and cost control aims to reduce the monetary cost; (3) Latency Control: The human workers can be slow, particularly compared to automated computing time scales, so latency-control techniques are required. There has been significant work addressing these three factors for designing crowdsourced tasks, developing crowdsourced data manipulation operators, and optimizing plans consisting of multiple operators. In this paper, we survey and synthesize a wide spectrum of existing studies on crowdsourced data management. Based on this analysis we then outline key factors that need to be considered to improve crowdsourced data management.
It has been widely recognized that the cross‐correlation function of ambient seismic noise data recorded at two stations approximates to the part of Greens function between two stations. Therefore, ...the cross‐correlation function should include higher modes, aside from the fundamental mode. However, the problem of measuring or extracting overtones from ambient seismic noise data remains. In this paper, we propose the frequency‐Bessel transform method (F‐J method) for extracting the dispersion curves of higher modes from ambient seismic noise data. We then assess the validity, accuracy, and applicability of the F‐J method by conducting extensive numerical simulations and processing the observed ambient seismic noise data of the USArray. As demonstrated in this study, the F‐J method is a convenient, practical, and accurate method for extracting the dispersion curves of multimodes from ambient seismic noise data and therefore has significant potentiality in the field of ambient seismic noise tomography.
Key Points
We proposed a new method (the F‐J method) to image dispersion curves of overtones of Rayleigh waves from ambient seismic noise data
Preliminary applications to USArray data demonstrated the validity and applicability of the F‐J method of Rayleigh waves
The F‐J method would strengthen the ambient noise tomography by providing high‐quality dispersion curves of overtones of Rayleigh waves
SUMMARY
The direct surface wave tomography has become an efficient tool in imaging 3-D shallow Earth structure. However, some fundamental problems still exist in selecting the grids to parametrize ...the model space. This study proposes to implement a model parametrization approach with multiple grids to the direct surface wave tomography. These multiple grids represent several overlapping collocated grids with the same or different grid spacings, such as staggered grids, multiscale grids and multiscale-staggered grids. At each iteration, direct inversion is applied to each individual set of collocated grids to invert for the shear wave velocity (Vs) model; the models are then projected onto a set of predefined base grids (usually the finest grids) using 3-D B-spline interpolation. At the end of each iteration, we average the Vs models of all sets of collocated grids to obtain the average 3-D Vs model, which is then used as the initial model for the next iteration. The properties of this approach are explored by applying it to a newly deployed dense array in Chao Lake (CL), eastern China. Synthetic and field data tests demonstrate that the method using multiple grids recovers anomaly patterns better than that using the individual set of collocated grids, though it does not necessarily achieve the smallest traveltime residual. We then obtain a high-resolution 3-D shallow crustal Vs model beneath the CL. The 3-D Vs model reveals two prominent features: (1) a stripe-like structural pattern of velocity variations, where the Hefei basin and eastern CL display low-velocity anomalies while the Tanlu fault zone (TFZ), Zhangbaling uplift and Yinping mountain present high-velocity anomalies and (2) north-shifted low-velocity anomalies beneath the eastern CL as depths go shallow. The shallow Vs features are consistent well with the local geological units and topography. We suggest that the two main features could be associated with the multistage tectonic activities of the Tanlu fault. The multiple-grid scheme proposed in this study could be conveniently extended to other 3-D direct inversion approaches in the near future.
The detection and classification of arrhythmias are crucial steps in diagnosing cardiovascular diseases. However, current deep learning-based classification methods often fail to consider both the ...morpho-logical and temporal features of the electrocardiogram (ECG) simultaneously. Therefore, we propose a hybrid heartbeat classification method that combines Transformer and multi branch convolutional neural networks (CNNs). Then, use the fusion module to stitch the features obtained from different classifiers. We performed three different heartbeat classification protocols on the MIT-BIH arrhythmia (MIT-BIH-AR) database and analyzed performance on SVEB and VEB classes to validate our method. The first was an intra-patient protocol with an overall accuracy of 99.5%, with 92.4% and 99.9% for Sen and Spe on SVEB and 98.2% and 99.9% for Sen and Spe on VEB. The latter two were inter-patient protocols, and we divided the training and test sets using different records, and the results showed an overall accuracy of 98.8% and 97.2%, respectively.
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•Proposing a multi-branch fusion ECG classification method•The proposed method is validated on the MIT-BIH database•Three different forms of data segmentation are used•The proposed method is of great significance for clinical application
Biomedical engineering: Artificial intelligence
The fabrication of new dermal substitutes providing mechanical support and cellular cues is urgently needed in dermal reconstruction. Silk fibroin (SF)/chondroitin sulfate (CS)/hyaluronic acid (HA) ...ternary scaffolds (95–248μm in pore diameter, 88–93% in porosity) were prepared by freeze-drying. By the incorporation of CS and HA with the SF solution, the chemical potential and quantity of free water around ice crystals could be controlled to form smaller pores in the SF/CS/HA ternary scaffold main pores and improve scaffold equilibrium swelling. This feature offers benefits for cell adhesion, survival and proliferation. In vivo SF, SF/HA and SF/CS/HA (80/5/15) scaffolds as dermal equivalents were implanted onto dorsal full-thickness wounds of Sprague–Dawley rats to evaluate wound healing. Compared to SF and SF/HA scaffolds, the SF/CS/HA (80/5/15) scaffolds promoted dermis regeneration, related to improved angiogenesis and collagen deposition. Further, vascular endothelial growth factor (VEGF), platelet-derived growth factor (PDGF) and basic fibroblast growth factor (bFGF) expression in the SF/CS/HA (80/5/15) groups were investigated by immunohistochemistry to assess the mechanisms involved in the stimulation of secretion of VEGF, PDGF and bFGF and accumulation of these growth factors related to accelerated wound process. These new three-dimensional ternary scaffolds offer potential for dermal tissue regeneration.
Recently, growing studies have demonstrated that circular RNAs (circRNAs) function as critical players in multiple human tumors, including papillary thyroid carcinoma (PTC). However, the expression ...and underlying potential mechanism of circRNAs in PTC are still not fully elucidated. In this study, 14 candidate differentially expressed circRNAs (DECs) between normal thyroid tissues and benign thyroid tissues or PTC were first screened using the GSE93522 dataset by the GEO2R online tool. Then, the structural loop graphs of these 14 circRNAs were obtained through the CSCD database. After performing miRNA co-prediction by combination of CSCD and CRI databases, a potential circRNA-miRNA sub-network, consisting of 9 circRNAs and 21 miRNAs, was successfully constructed. Subsequently, the expression and prognostic values of these miRNAs were further determined by starBase, and two miRNAs, namely, miR-605-5p and miR-876-3p, were identified as key miRNAs in PTC. Then, their downstream target genes were predicted by the miRNet database. CTNNB1 and CCND1 were found to be two most potential targets of miR-876-3p by combination of multiple
analyses, including protein-protein interaction (PPI), hub gene screening, correlation analysis, and expression analysis. Conclusively, we established a key hsa_circ_0088494-miR-876-3p-CTNNB1/CCND1 axis linked to carcinogenesis and progression of PTC, which may provide promising therapeutic targets in treating PTC in the future.
Rock salt is considered a suitable medium for the permanent disposal of heat‐generating radioactive waste due to its isolation properties. However, excavation damage and heating induce complex and ...heterogeneous thermal‐hydrological‐mechanical (THM) processes across different zones. Quantifying this heterogeneity is crucial for accurate long‐term performance assessment models, but traditional methods lack the necessary resolution. This study employs 4D electrical resistivity tomography (ERT) monitoring during controlled heating experiments in a salt formation to unravel the spatiotemporal dynamics of THM processes. Advanced time‐lapse inversion and clustering analysis quantify subsurface properties and map the heterogeneity of THM dynamics. The ERT results can estimate subsurface properties and delineate the damaged and intact zones, enabling appropriate parameterization and representation of processes for long‐term modeling. This approach may be used in further improving the predictive models and ensuring the safe long‐term disposal of radioactive waste in rock salt.
Plain Language Summary
Rock salt is great for the disposal of heat‐generating radioactive waste because it prevents releasing harmful radiation into the environment. However, mining and heating can cause complex changes in temperature, water flow, and pressure, affecting rock salt in various ways. It is important to understand these changes accurately for planning how the disposal will affect the rock salt, but the traditional ways of studying them are not detailed enough. In this study, we used a special technique called 4D ERT while heating up the rock salt to see how these changes happen over time and space. We analyzed the data in advanced ways to measure the underground properties and understand the complex changes. The information can improve how we model and plan the disposal of heat‐generating waste. This new insight makes it easier to ensure that storing heat‐generating radioactive waste in rock salt is safe for a long time.
Key Points
We employ 4D electrical resistivity tomography (ERT) monitoring during a controlled heating experiment in salt formations
The resistivity data exhibits contrasting trends throughout and post‐heating, indicating the heterogeneous thermal‐hydrological‐mechanical processes in rock salt are likely linked to the different levels of excavation damages
Employing time‐series clustering technology enables quantification and spatial distributions of excavation damage/disturbed zones within the salt formations which may help further improve the parameterization of long‐term predictive models
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