Multiobjective evolutionary algorithm based on decomposition (MOEA/D) decomposes a multiobjective optimization problem (MOP) into a number of scalar optimization subproblems and then solves them in ...parallel. In many MOEA/D variants, each subproblem is associated with one and only one solution. An underlying assumption is that each subproblem has a different Pareto-optimal solution, which may not be held, for irregular Pareto fronts (PFs), e.g., disconnected and degenerate ones. In this paper, we propose a new variant of MOEA/D with sorting-and-selection (MOEA/D-SAS). Different from other selection schemes, the balance between convergence and diversity is achieved by two distinctive components, decomposition-based-sorting (DBS) and angle-based-selection (ABS). DBS only sorts L closest solutions to each subproblem to control the convergence and reduce the computational cost. The parameter L has been made adaptive based on the evolutionary process. ABS takes use of angle information between solutions in the objective space to maintain a more fine-grained diversity. In MOEA/D-SAS, different solutions can be associated with the same subproblems; and some subproblems are allowed to have no associated solution, more flexible to MOPs or many-objective optimization problems (MaOPs) with different shapes of PFs. Comprehensive experimental studies have shown that MOEA/D-SAS outperforms other approaches; and is especially effective on MOPs or MaOPs with irregular PFs. Moreover, the computational efficiency of DBS and the effects of ABS in MOEA/D-SAS are also investigated and discussed in detail.
Federated learning (FL) is seen as a road toward privacy-preserving distributed artificial intelligence while keeping raw training data on local devices. By leveraging blockchain, this article puts ...forward a blockchain and FL fusioned framework to manage the security and trust issues when applying FL over mobile edge networks. First, a two-layered architecture is proposed that consists of two types of blockchains: local model update chain (LMUC) assisted by device-to-device (D2D) communication and global model update chain (GMUC) supporting task sharding. The D2D-assisted LMUC is designed to chronologically and efficiently record all of the local model training results, which can help to form long-term reputations of local devices. The GMUC is proposed to provide both security and efficiency by preventing mobile edge computing nodes from malfunctioning and dividing them into logically isolated FL task-specific chains. Then a reputation-learning-based incentive mechanism is introduced to make participating local devices more trustful with a reward implemented by a smart contract. Finally, a case study is given to show that the proposed framework performs well in terms of FL learning accuracy and blockchain time delay.
Dissolved organic nitrogen (DON) plays a crucial role in biogeochemical processes of nitrogen (N) and has become a non‐negligible source of increasing groundwater nitrogen contamination. Therefore, ...the extraction accuracy of DON in unsaturated zones is essential for sound understanding of N transport, transformation behaviour and contamination processes. However, there is no uniform extraction standard for measuring DON content in the unsaturated zone. Moreover, the influences of various extraction conditions on the DON measurement are not clear. Hereby, we are the first to address the issues associated with all the extraction indicators (extractant types and concentrations, extraction duration, frequency, and solution volume‐to‐soil weight ratio) for the DON extraction accuracy in unsaturated zones, and present a comprehensive influence analyses. Our results revealed that extraction conditions could significantly influence the extraction accuracy of DON and that the principal impact factor was the concentration of the extractant. We also found that the widely used previous extraction approaches (high‐salinity extraction method) would induce high uncertainty in measuring the DON content in unsaturated zones of different areas. Furthermore, the opposing influences from the ions of extractants can seriously affect the assessment of DON content and hinder comparability even using the same extraction method, which could severely affect the assessment of the DON content in unsaturated zones. Such uncertainty in measurements will eventually influence the observation and evaluation of groundwater nitrogen contamination. Our results demonstrated that the use of the former DON extraction method without considering the research purposes and the specific study areas would lead to a strong bias. Based on detailed response surface analysis, we provide a comprehensive analysis related to the accuracy of DON extraction, which is conducive to improving the extraction accuracy of nitrogen research in global groundwater hydrological processes in the future.
A comprehensive analysis of DON extraction accuracy was firstly presented. Opposite effects from ions of extractants can seriously affect DON accuracy.
Fatigue and diarrhea are the most frequent adverse effects of pelvic radiotherapy, while their etiologies are largely unknown. The aim of this study is to investigate the correlations between ...fatigue, diarrhea, and alterations in gut microbiota induced by pelvic radiotherapy. During the 5-week treatment of pelvic radiotherapy in 11 cancer patients, the general fatigue score significantly increased and was more prominent in the patients with diarrhea. The fatigue score was closely correlated with the decrease of serum citrulline (an indicator of the functional enterocyte mass) and the increases of systemic inflammatory proteins, including haptoglobin, orosomuoid, α1-antitrypsin and TNF-α. Serum level of lipopolysaccharide (LPS) was also elevated, especially in the patients with diarrhea indicating epithelial barrier breach and endotoxemia. Pyrosequencing analysis of 16S rRNA gene revealed that microbial diversity, richness, and the Firmicutes/Bacteroidetes ratio were significantly altered prior to radiotherapy in patients who later developed diarrhea. Pelvic radiotherapy induced further changes in fecal microbial ecology, some of which were specific to the patients with or without diarrhea. Our results indicate that gut microbial dysbiosis prior to radiation therapy may be exploited to predict development of diarrhea and to guide preventive treatment options. Radiation-induced dysbiosis may contribute to pelvic radiation disease, including mucositis, diarrhea, systemic inflammatory response, and pelvic radiotherapy-associated fatigue in cancer patients.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Deinococcus radiodurans (D. radiodurans) can tolerate various extreme environments including radiation. Protein phosphorylation plays an important role in radiation resistance mechanisms; however, ...there is currently a lack of systematic research on this topic in D. radiodurans. Based on label-free (phospho)proteomics, we explored the dynamic changes of D. radiodurans under various doses of heavy ion irradiation and at different time points. In total, 2359 proteins and 1110 high-confidence phosphosites were identified, of which 66% and 23% showed significant changes, respectively, with the majority being upregulated. The upregulated proteins at different states (different doses or time points) were distinct, indicating that the radio-resistance mechanism is dose- and stage-dependent. The protein phosphorylation level has a much higher upregulation than protein abundance, suggesting phosphorylation is more sensitive to irradiation. There were four distinct dynamic changing patterns of phosphorylation, most of which were inconsistent with protein levels. Further analysis revealed that pathways related to RNA metabolism and antioxidation were activated after irradiation, indicating their importance in radiation response. We also screened some key hub phosphoproteins and radiation-responsive kinases for further study. Overall, this study provides a landscape of the radiation-induced dynamic change of protein expression and phosphorylation, which provides a basis for subsequent functional and applied studies.
The interaction of mining and the surface water or aquifer system in varying overburden strata conditions is one of the most critical aspects of sustainable mining practices, that can lead to water ...loss or water inrush into openings. This paper examined this phenomenon in a complex strata condition via a case study, and proposed a new mining design to minimize the impact of longwall mining on the overlaying aquifer. A range of factors have been identified contributing to the potential disturbance of the aquifer, including the extent of the water-rich area, the characteristics of overburden rock units, and the development height of the water-conducting fracture zone. In this study, the transient electromagnetic method and the high-density three-dimensional electrical method were used to identify two areas prone to water inrush danger in the working face. The vertical range of the water-rich abnormal area 1 is 45-60 m away from the roof, with an area of 3334 m
. The vertical range of the water-rich abnormal area 2 is 30-60 m away from the roof, with an area of approximately 2913 m
. The bedrock drilling method was used to determine that the thinnest part of the bedrock, with a thickness of approximately 60 m, and the thickest part, with a thickness of approximately 180 m. The maximum mining-induced height of the fracture zone was 42.64 m using empirical method, theoretical prediction based on the rock stratum group, field monitoring. In summary, the high risk area was determined, and the analysis shows that the size of the water prevention) pillar was 52.6 m, which was smaller than the safe water prevention pillar actually set in the mining range. The research conclusion provides important safety guidance significance for the mining of similar mines.
The rice blast fungus Magnaporthe oryzae forms specialized infectious structures called appressoria that breach host cells to initiate infection. Previous studies demonstrated that the regulator of ...G-protein signaling (RGS)-like protein MoRgs7 undergoes endocytosis upon fungal sensing of hydrophobic environmental cues to activate cAMP signaling required for appressorium formation. However, the mechanism by which MoRgs7 internalizes and its fate remains undetermined. We here show that MoSep1, a conserved protein kinase of Mitotic Exit Network (MEN), phosphorylates MoRgs7 to regulate its function. MoRgs7 phosphorylation determines its interaction with MoCrn1, a coronin-like actin-binding protein homolog that also modulates the internalization of MoRgs7. Importantly, the endocytic transport of MoRgs7 is critical for its GTPase-activating protein (GAP) function important in cAMP signaling. Together, our findings revealed a novel mechanism by which M. oryzae activates MoRgs7-mediated hydrophobic cue-sensing signal transduction involving protein phosphorylation and endocytic transport to govern appressorium formation and fungal pathogenicity.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Autophagy and Cell wall integrity (CWI) signaling are critical stress-responsive processes during fungal infection of host plants. In the rice blast fungus Magnaporthe oryzae, autophagy-related (ATG) ...proteins phosphorylate CWI kinases to regulate virulence; however, how autophagy interplays with CWI signaling to coordinate such regulation remains unknown. Here, we have identified the phosphorylation of ATG protein MoAtg4 as an important process in the coordination between autophagy and CWI in M. oryzae. The ATG kinase MoAtg1 phosphorylates MoAtg4 to inhibit the deconjugation and recycling of the key ATG protein MoAtg8. At the same time, MoMkk1, a core kinase of CWI, also phosphorylates MoAtg4 to attenuate the C-terminal cleavage of MoAtg8. Significantly, these two phosphorylation events maintain proper autophagy levels to coordinate the development and pathogenicity of the rice blast fungus.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Selecting a representative optical deep-water area is crucial for accurate satellite-derived bathymetry (SDB) based on semi-theoretical and semi-empirical models. This study proposed a deep-water ...area selection method where potential areas were identified by integrating remote sensing imagery with existing global bathymetric data. Specifically, the effects of sun glint correction for deep-water areas on SDB estimation were investigated. The results indicated that the computed SDB had significant instabilities when different optical deep-water areas without sun glint correction were used for model training. In comparison, when sun glint correction was applied, the SDB results from different deep-water areas had greater consistency. We generated bathymetric maps for the Langhua Reef in the South China Sea and Buck Island near the U.S. Virgin Islands using Sentinel-2 multispectral images and 70% of the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) bathymetry data. Additionally, 30% of the ICESat-2 bathymetry data and NOAA NGS Topo-bathy Lidar data served as the validation data to evaluate the qualities of the computed SDB, respectively. The results showed that the average quality of the SDB significantly improved with sun glint correction application by a magnitude of 0.60 m in terms of the root mean square error (RMSE) for two study areas. Moreover, an evaluation of the SDB data computed from different deep-water areas showed more consistent results, with RMSEs of approximately 0.4 and 1.4 m over the Langhua Reef and Buck Island, respectively. These values were consistently below 9% of the maximum depth. In addition, the effects of the optical image selection on SDB inversion were investigated, and the SDB calculated from the images over different time periods demonstrated similar results after applying sun glint correction. The results showed that this approach for optical deep-water area selection and correction could be used for improving the SDB, particularly in challenging scenarios, thereby enhancing the accuracy and robustness of SDB.
•A new algorithm was proposed to remove noise photons induced by specular reflection.•The proposed noise removal algorithm is superior to the ATL03 built-in algorithm.•The proposed noise removal ...algorithm is not sensitive to the input parameter.•The weak beam achieved higher water elevation accuracy than that of the strong beam.•The proposed noise removal algorithm can reduce the underestimation of water level.
The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) data may contain abundant noise photons induced by specular reflection, which make the signal photon detection and surface elevation extraction challenging, especially on flat surfaces with high reflectivity. However, no efficient algorithm for specular return noise removal has been proposed. Therefore, this study aims to propose a novel methodological framework based on statistical features to remove noise photons induced by specular reflection. First, ICESat-2 data preprocessing was performed to improve the speed and accuracy of subsequent processing. Second, the statistical features of outlier distance were calculated and utilized to filter out noise photons. Third, the specular return noise was removed according to the extreme points in the elevation distribution histogram. Finally, the manually labeled of photons and in-situ data were utilized to evaluate the performance of the proposed framework. Additionally, the proposed framework was compared with three existing signal photon extraction algorithms (ATL03, ATL13, AVEBM) for further assessment. The experimental results show that the F1-score of the proposed framework is 99.9 % and the accuracy of water level estimation is extremely high (bias = 0.041 m, and RMSE = 0.082 m). Further analysis demonstrates that our framework has the high robustness because it is not sensitive to input parameter. Meanwhile, the weak beam achieved higher water elevation accuracy than that of the strong beam. Besides, the proposed framework performs better than the existing methods in extracting water surface photons and water level. All in all, the proposed framework has been shown to effectively remove noise photons of specular returns in the raw ICESat-2 data and reduce the underestimation of the water level.
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