| 1. |
- Sun, Tao, et al.
(författare)
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Contrasting dynamics and trait controls in first-order root compared with leaf litter decomposition
- 2018
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Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 115:41, s. 10392-10397
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Tidskriftsartikel (refereegranskat)abstract
- Decomposition is a key component of the global carbon (C) cycle, yet current ecosystem C models do not adequately represent the contributions of plant roots and their mycorrhizae to this process. The understanding of decomposition dynamics and their control by traits is particularly limited for the most distal first-order roots. Here we followed decomposition of first-order roots and leaf litter from 35 woody plant species differing in mycorrhizal type over 6 years in a Chinese temperate forest. First-order roots decomposed more slowly (k = 0.11 ± 0.01 years−1) than did leaf litter (0.35 ± 0.02 years−1), losing only 35% of initial mass on average after 6 years of exposure in the field. In contrast to leaf litter, nonlignin root C chemistry (nonstructural carbohydrates, polyphenols) accounted for 82% of the large interspecific variation in first-order root decomposition. Leaf litter from ectomycorrhizal (EM) species decomposed more slowly than that from arbuscular mycorrhizal (AM) species, whereas first-order roots of EM species switched, after 2 years, from having slower to faster decomposition compared with those from AM species. The fundamentally different dynamics and control mechanisms of first-order root decomposition compared with those of leaf litter challenge current ecosystem C models, the recently suggested dichotomy between EM and AM plants, and the idea that common traits can predict decomposition across roots and leaves. Aspects of C chemistry unrelated to lignin or nitrogen, and not presently considered in decomposition models, controlled first-order root decomposition; thus, current paradigms of ecosystem C dynamics and model parameterization require revision.
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| 2. |
- Dong, Lili, et al.
(författare)
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Effects of different forms of N deposition on leaf litter decomposition and extracellular enzyme activities in a temperate grassland
- 2019
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Ingår i: Soil Biology and Biochemistry. - : Elsevier. - 0038-0717 .- 1879-3428. ; 134, s. 78-80
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Tidskriftsartikel (refereegranskat)abstract
- Despite the importance of decomposition for biogeochemical cycles, it is still not clear how this process is affected by different forms of nitrogen (N). Equal amounts of N with different ratios of inorganic N: organic N (0 : 0, 10 : 0, 7 : 3, 5 : 5, 3 : 7, and 0 : 10) were added to the soil in a steppe. We studied the response of litter decomposition to different forms of N enrichment. The treatment with 30% organic N resulted in the fastest decomposition, which was higher than with inorganic N or organic N addition alone. Our results highlight the need for studies of N deposition on carbon cycles that consider different components in N deposition.
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| 3. |
- Dong, Lili, et al.
(författare)
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Effects of different forms of nitrogen addition on microbial extracellular enzyme activity in temperate grassland soil
- 2022
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Ingår i: Ecological Processes. - : Springer. - 2192-1709. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- Background Nitrogen (N) deposition alters litter decomposition and soil carbon (C) sequestration by influencing the microbial community and its enzyme activity. Natural atmospheric N deposition comprises of inorganic N (IN) and organic N (ON) compounds. However, most studies have focused on IN and its effect on soil C cycling, whereas the effect of ON on microbial enzyme activity is poorly understood. Here we studied the effects of different forms of externally supplied N on soil enzyme activities related to decomposition in a temperate steppe. Ammonium nitrate was chosen as IN source, whereas urea and glycine were chosen as ON sources. Different ratios of IN to ON (Control, 10:0, 7:3, 5:5, 3:7, and 0:10) were mixed with equal total amounts of N and then used to fertilize the grassland soils for 6 years. Results Our results show that IN deposition inhibited lignin-degrading enzyme activity, such as phenol oxidase (POX) and peroxidase (PER), which may restrain decomposition and thus induce accumulation of recalcitrant organic C in grassland soils. By contrast, deposition of ON and mixed ON and IN enhanced most of the C-degrading enzyme activities, which may promote the organic matter decomposition in grassland soils. In addition, the beta-N-acetyl-glucosaminidase (NAG) activity was remarkably stimulated by fertilization with both IN and ON, maybe because of the elevated N availability and the lack of N limitation after long-term N fertilization at the grassland site. Meanwhile, differences in soil pH, soil dissolved organic carbon (DOC), and microbial biomass partially explained the differential effects on soil enzyme activity under different forms of N treatments. Conclusions Our results emphasize the importance of organic N deposition in controlling soil processes, which are regulated by microbial enzyme activities, and may consequently change the ecological effect of N deposition. Thus, more ON deposition may promote the decomposition of soil organic matter thus converting C sequestration in grassland soils into a C source.
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| 4. |
- Dong, Lili, et al.
(författare)
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Response of fine root decomposition to different forms of N deposition in a temperate grassland
- 2020
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Ingår i: Soil Biology and Biochemistry. - : Elsevier. - 0038-0717 .- 1879-3428. ; 147
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Tidskriftsartikel (refereegranskat)abstract
- Despite the importance of plant litter decomposition for ecosystem nutrient cycling and soil fertility, it is still largely unknown how this biogeochemical process is affected by different forms of nitrogen (N). Numerous studies have investigated the effects of exogenous N addition on leaf litter decomposition, while the response of decomposing roots and their microbial communities to externally applied N is rarely studied. Fine roots, however, represent a key input to soil organic matter and understanding their decomposition under elevated atmospheric N deposition is important for predicting soil carbon (C) dynamics in response to changes in climatic conditions. In this study, we decomposed fine roots of five dominant grassland species for two years in field plots fertilized with different forms of N in a typical temperate grassland in Inner Mongolia. Ammonium nitrate was selected as inorganic N (IN), while urea and glycine were chosen as organic N (ON). Equal amounts of N (10 g N·m−2·yr−1) with different ratios of IN: ON (control, 10 : 0, 7 : 3, 5 : 5, 3 : 7, and 0 : 10) were added to the soil. Our results showed that all exogenous N additions, either IN or ON forms, stimulated the decomposition rates across species. Furthermore, the treatment with a mixture of IN and ON fertilizers led to the strongest responses in decomposition rate, which were, on average, 20% higher than control, and 12% higher than using just IN addition across the five studied species. Our results suggest that we need to consider the different components in N deposition when examining nitrogen deposition effects on terrestrial ecosystem carbon and nutrient cycles.
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| 5. |
- Hai, Tao, et al.
(författare)
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Enhanced security using multiple paths routine scheme in cloud-MANETs
- 2023
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Ingår i: Journal of Cloud Computing. - : Springer. - 2192-113X. ; 12:1
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Tidskriftsartikel (refereegranskat)abstract
- Cloud Mobile Ad-hoc Networks (Cloud-MANETs) is a framework that can access and deliver cloud services to MANET users through their smart devices. MANETs is a pool of self-organized mobile gadgets that can communicate with each other with no support from a central authority or infrastructure. The main advantage of MANETs is its ability to manage mobility while data communication between different users in the system occurs. In MANETs, clustering is an active technique used to manage mobile nodes. The security of MANETs is a key aspect for the fundamental functionality of the network. Addressing the security-related problems ensures that the confidentiality and integrity of the data transmission is secure. MANETs are highly prone to attacks because of their properties.In clustering schemes, the network is broken down to sub-networks called clusters. These clusters can have overlapping nodes or be disjointed. An enhanced node referred to asthe Cluster Head (CH) is chosen from each set to overseetasks related to routing. It decreases the member nodes’ overhead and improvesthe performance of the system. The relationship between the nodes and CH may vary randomly, leading to re-associations and re-clustering in a MANET that is clustered. An efficient and effective routing protocol is required to allow networking and to find the most suitable paths between the nodes. The networking must be spontaneous, infrastructure-less, and provide end-to-end interactions. The aim of routing is the provision of maximum network load distribution and robust networks. This study focused on the creation of a maximal route between a pair of nodes, and to ensure the appropriate and accurate delivery of the packet. The proposed solution ensured that routing can be carried out with the lowest bandwidth consumption. Compared to existing protocols, the proposed solution had a control overhead of 24, packet delivery ratio of 81, the lowest average end-to-end delay of 6, and an improved throughput of 80,000, thereby enhancing the output of the network. Our result shows that multipath routing enables the network to identify alternate paths connecting the destination and source. Routing is required to conserve energy and for optimum bandwidth utilization.
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| 6. |
- Hai, Tao, et al.
(författare)
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Task scheduling in cloud environment: optimization, security prioritization and processor selection schemes
- 2023
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Ingår i: Journal of Cloud Computing. - : Springer. - 2192-113X. ; 12
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Tidskriftsartikel (refereegranskat)abstract
- Cloud computing is an extremely important infrastructure used to perform tasks over processing units. Despite its numerous benefits, a cloud platform has several challenges preventing it from carrying out an efficient workflow submission. One of these is linked to task scheduling. An optimization problem related to this is the maximal determination of cloud computing scheduling criteria. Existing methods have been unable to find the quality of service (QoS) limits of users- like meeting the economic restrictions and reduction of the makespan. Of all these methods, the Heterogeneous Earliest Finish Time (HEFT) algorithm produces the maximum outcomes for scheduling tasks in a heterogeneous environment in a reduced time. Reviewed literature proves that HEFT is efficient in terms of execution time and quality of schedule. The HEFT algorithm makes use of average communication and computation costs as weights in the DAG. In some cases, however, the average cost of computation and selecting the first empty slot may not be enough for a good solution to be produced. In this paper, we propose different HEFT algorithm versions altered to produce improved results. In the first stage (rank generation), we execute several methodologies to calculate the ranks, and in the second stage, we alter how the empty slots are selected for the task scheduling. These alterations do not add any cost to the primary HEFT algorithm, and reduce the makespan of the virtual machines’ workflow submissions. Our findings suggest that the altered versions of the HEFT algorithm have a better performance than the basic HEFT algorithm regarding decreased schedule length of the workflow problems.
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| 7. |
- Sun, Tao, et al.
(författare)
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Empirical evidence that manganese enrichment accelerates decomposition
- 2021
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Ingår i: Agriculture, Ecosystems & Environment. Applied Soil Ecology. - : Elsevier. - 0929-1393 .- 1873-0272. ; 168
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Tidskriftsartikel (refereegranskat)abstract
- Our understanding of the controls regulating the rate of litter decomposition is important for improving confidence in the parameterization of carbon cycle–climate feedbacks. Traditional conceptual models rely primarily on climate and lignin/N ratios as the main regulators of decomposition. Here we studied the effects of manganese (Mn) addition on long-term decomposition across 18 substrates in a laboratory incubation. Mn addition remarkably promoted later stage of decomposition, resulting into a smaller fraction of slowly decomposing litter. This dynamic is closely associated with the changes of activities of manganese peroxidase, an important enzyme with greater capacity for lignin degradation. Our findings suggest the necessity of incorporating the interaction of Mn and decomposition into biogeochemical models.
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| 8. |
- Wang, Yan Ming, et al.
(författare)
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Colorado geoid computation experiment : overview and summary
- 2021
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Ingår i: Journal of Geodesy. - : Springer. - 0949-7714 .- 1432-1394. ; 95:12
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Tidskriftsartikel (refereegranskat)abstract
- The primary objective of the 1-cm geoid experiment in Colorado (USA) is to compare the numerous geoid computation methods used by different groups around the world. This is intended to lay the foundations for tuning computation methods to achieve the sought after 1-cm accuracy, and also evaluate how this accuracy may be robustly assessed. In this experiment, (quasi)geoid models were computed using the same input data provided by the US National Geodetic Survey (NGS), but using different methodologies. The rugged mountainous study area (730 km x 560 km) in Colorado was chosen so as to accentuate any differences between the methodologies, and to take advantage of newly collected GPS/leveling data of the Geoid Slope Validation Survey 2017 (GSVS17) which are now available to be used as an accurate and independent test dataset. Fourteen groups from fourteen countries submitted a gravimetric geoid and a quasigeoid model in a 1' x 1' grid for the study area, as well as geoid heights, height anomalies, and geopotential values at the 223 GSVS17 marks. This paper concentrates on the quasigeoid model comparison and evaluation, while the geopotential value investigations are presented as a separate paper (Sanchez et al. in J Geodesy 95(3):1. https://doi.org/10.1007/s00190-021-01481-0, 2021). Three comparisons are performed: the area comparison to show the model precision, the comparison with the GSVS17 data to estimate the relative accuracy of the models, and the differential quasigeoid (slope) comparison with GSVS17 to assess the relative accuracy of the height anomalies at different baseline lengths. The results show that the precision of the 1' x 1' models over the complete area is about 2 cm, while the accuracy estimates along the GSVS17 profile range from 1.2 cm to 3.4 cm. Considering that the GSVS17 does not pass the roughest terrain, we estimate that the quasigeoid can be computed with an accuracy of similar to 2 cm in Colorado. The slope comparisons show that RMS values of the differences vary from 2 to 8 cm in all baseline lengths. Although the 2-cm precision and 2-cm relative accuracy have been estimated in such a rugged region, the experiment has not reached the 1-cm accuracy goal. At this point, the different accuracy estimates are not a proof of the superiority of one methodology over another because the model precision and accuracy of the GSVS17-derived height anomalies are at a similar level. It appears that the differences are not primarily caused by differences in theory, but that they originate mostly from numerical computations and/or data processing techniques. Consequently, recommendations to improve the model precision toward the 1-cm accuracy are also given in this paper.
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| 9. |
- Zhou, Jincheng, et al.
(författare)
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Voice spoofing countermeasure for voice replay attacks using deep learning
- 2022
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Ingår i: Journal of Cloud Computing. - : Springer. - 2192-113X. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- In our everyday lives, we communicate with each other using several means and channels of communication, as communication is crucial in the lives of humans. Listening and speaking are the primary forms of communication. For listening and speaking, the human voice is indispensable. Voice communication is the simplest type of communication. The Automatic Speaker Verification (ASV) system verifies users with their voices. These systems are susceptible to voice spoofing attacks - logical and physical access attacks. Recently, there has been a notable development in the detection of these attacks. Attackers use enhanced gadgets to record users’ voices, replay them for the ASV system, and be granted access for harmful purposes. In this work, we propose a secure voice spoofing countermeasure to detect voice replay attacks. We enhanced the ASV system security by building a spoofing countermeasure dependent on the decomposed signals that consist of prominent information. We used two main features— the Gammatone Cepstral Coefficients and Mel-Frequency Cepstral Coefficients— for the audio representation. For the classification of the features, we used Bi-directional Long-Short Term Memory Network in the cloud, a deep learning classifier. We investigated numerous audio features and examined each feature’s capability to obtain the most vital details from the audio for it to be labelled genuine or a spoof speech. Furthermore, we use various machine learning algorithms to illustrate the superiority of our system compared to the traditional classifiers. The results of the experiments were classified according to the parameters of accuracy, precision rate, recall, F1-score, and Equal Error Rate (EER). The results were 97%, 100%, 90.19% and 94.84%, and 2.95%, respectively.
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