A Novel Shortcut Addition Algorithm With Particle Swarm for Multisink Internet of Things

[EN] The Internet of Things integrates a large number of distributed nodes to collect or transmit data. When the network scale increases, individuals use multiple sink nodes to construct the network. This increases the complexity of the network and leads to significant challenges in terms of the existing methods with respect to the aspect of data forwarding and collection. In order to address the issue, this paper proposes a Shortcut Addition strategy based on the Particle Swarm algorithm (SAPS) for multisink network. It constructs a network topology with multiple sinks based on a small-world network. In the SAPS, we create a fitness function by combining the average path length and load of the sink node, to evaluate the quality of a particle. Subsequently, crossover and mutation are used to update the particles to determine the optimal solution. The simulation results indicate that the SAPS is superior both to the greedy model with small world and the load-balanced multigateway aware long link addition strategy in terms of the average path length, load balance, and number of added shortcuts.This work was supported by the National Natural Science Foundation of China under Grant 61672131 and Grant 61702365. Paper no. TII-19-0511.Qiu, T.; Li, B.; Zhou, X.; Song, H.; Lee, I.; Lloret, J. (2020). A Novel Shortcut Addition Algorithm With Particle Swarm for Multisink Internet of Things. IEEE Transactions on Industrial Informatics. 16(5):3566-3577. https://doi.org/10.1109/TII.2019.29250233566357716

Alkaline Plasma-Activated Water (PAW) as an Innovative Therapeutic Avenue for Cancer Treatment

Plasma-activated water (PAW) is considered to be an effective anticancer agent due to the diverse aqueous reactive oxygen and nitrogen species (RONS: ROS and RNS), but the drawback of low dose and short duration of RONS in acidified PAW limits their clinical application. Herein, this Letter presents an innovative therapeutic avenue for cancer treatment with highly-effective alkaline PAW prepared by air surface plasma. This anticancer alkaline formulation is comprised of a rich mixture of highly chemical RONS and exhibited a prolonged half-life compared to acidified PAW. The H2O2, NO2-, and ONOO-/O2- concentrations in the alkaline PAW can reach up to 18-, 16-, and 14-fold higher than that in acidic PAW, and the half-life of these species was extended over 8-, 10-, and 26-fold, respectively. The synergistic potent redox action between these RONS with alkaline pH was shown to be more potent than acidic PAW for cancer cell inhibition in vitro. Furthermore, the alkaline PAW injection treatment also significantly inhibited tumor growth in tumor-bearing mice. The possible reasons are that the alkaline PAW would disturb the acid extracellular milieu leading to the inhibition of tumor growth and progression; moreover, the efficient and durable RONS with alkaline pH could induce significant cell apoptosis by altering cell biomolecules and participating apoptosis-related signaling pathways. These findings offer promising applications for developing a strategy with real potential for tumor treatment in clinical applications

Niche Separation of Ammonia Oxidizers in Mudflat and Agricultural Soils Along the Yangtze River, China

Nitrification driven by ammonia oxidizers is a key step of nitrogen removal in estuarine environments. Spatial distribution characteristics of ammonia-oxidizers have been well understood in mudflats, but less studied in the agricultural soils next to mudflats, which also play an important role in nitrogen cycling of the estuarine ecosystem. In the present research, we investigated ammonia oxidizers’ distributions along the Yangtze River estuary in Jiangsu Province, China, sampling soils right next to the estuary (mudflats) and the agricultural soils 100 m away. We determined the relationship between the abundance of amoA genes of ammonia-oxidizing archaea (AOA) and ammonia-oxidizing bacteria (AOB) and the potential nitrification rates of the mudflats and agricultural soils. We also identified the environmental variables that correlated with the composition of the ammonia oxidizers’ communities by 16S rRNA gene pyrosequencing. Results indicated that agricultural soils have significantly higher potential nitrification rates as well as the AOA abundance, and resulted in strong phylogenetic clustering only in AOA communities. The ammonia oxidizers’ community compositions differed dramatically among the mudflat and agricultural sites, and stochasticity played a dominant role. The AOA communities were dominated by the Group 1.1a cluster at the mudflat, whereas the 54D9 and 29i4 clusters were dominant in agriculture soils. The dominant AOB communities in the mudflat were closely related to the Nitrosospira lineage, whereas the agricultural soils were dominated by the Nitrosomonas lineage. Soil organic matter and salinity were correlated with the ammonia oxidizers’ community compositions

Plasma metabonomics of classical swine fever virus-infected pigs

Classical swine fever (CSF) is an infectious disease caused by Classical swine fever virus (CSFV), which is characterized by depression, high fever, extensive skin bleeding, leukopenia, anorexia, alternating constipation, and diarrhea. Hemorrhagic infarction of the spleen is the main characteristic pathological change following CSFV infection. Large-scale outbreaks of CSF are rare in China and are mainly distributed regionally. The clinical symptoms of CSF are not obvious, and show variation from typical to atypical symptoms, which makes diagnosis based on clinical symptoms and pathology challenging. In recent years, the incidence of CSF-immunized pig farms in China has increased and new CSFV gene subtypes have appeared, posing new challenges to the prevention and control of CSF in China. Changes in metabolites caused by viral infection reflect the pathogenic process. Metabonomics can reveal the trace metabolites of organisms; however, plasma metabonomics of CSFV-infected pigs have rarely been investigated. Therefore, we used an established pig CSFV infection model to study changes in plasma metabolites. The results showed significant differences in forty-five plasma metabolites at different time periods after CSFV infection in pigs, with an increase in twenty-five metabolites and a decrease in twenty metabolites. These changed metabolites were mainly attributed to the tricarboxylic acid cycle, amino acid cycle, sugar metabolism, and fat metabolism. Thirteen metabolic pathways changed significantly in CSFV-infected pigs, including tricarboxylic acid cycle, inositol phosphate metabolism, glycine, serine and threonine metabolism,lysine degradation, alanine, aspartate and glutamic acid metabolism, pantothenate and CoA biosynthesis, β-alanine metabolism, lysine degradation, arginine and proline metabolism, glycerolipid metabolism, phenylalanine metabolism, arachidonic acid metabolism, linoleic acid metabolism. Among these, changes in fatty acid biosynthesis and metabolism occurred at all time periods post-infection. These results indicate that CSFV infection in pigs could seriously alter metabolic pathways

Gene expression and DNA methylation altering lead to the high oil content in wild allotetraploid peanut (A. monticola)

IntroductionThe wild allotetraploid peanut Arachis monticola contains a higher oil content than the cultivated allotetraploid Arachis hypogaea. Besides the fact that increasing oil content is the most important peanut breeding objective, a proper understanding of its molecular mechanism controlling oil accumulation is still lacking.MethodsWe investigated this aspect by performing comparative transcriptomics from developing seeds between three wild and five cultivated peanut varieties.ResultsThe analyses not only showed species-specific grouping transcriptional profiles but also detected two gene clusters with divergent expression patterns between two species enriched in lipid metabolism. Further analysis revealed that expression alteration of lipid metabolic genes with co-expressed transcription factors in wild peanut led to enhanced activity of oil biogenesis and retarded the rate of lipid degradation. In addition, bisulfite sequencing was conducted to characterize the variation of DNA methylation between wild allotetraploid (245, WH 10025) and cultivated allotetraploid (Z16, Zhh 7720) genotypes. CG and CHG context methylation was found to antagonistically correlate with gene expression during seed development. Differentially methylated region analysis and transgenic assay further illustrated that variations of DNA methylation between wild and cultivated peanuts could affect the oil content via altering the expression of peroxisomal acyl transporter protein (Araip.H6S1B).DiscussionFrom the results, we deduced that DNA methylation may negatively regulate lipid metabolic genes and transcription factors to subtly affect oil accumulation divergence between wild and cultivated peanuts. Our work provided the first glimpse on the regulatory mechanism of gene expression altering for oil accumulation in wild peanut and gene resources for future breeding applications

Personalized Sliding Window Recommendation Algorithm Based on Sequence Alignment

With the explosive growth of the amount of information in social networks, the recommendation system, as an application of social networks, has attracted widespread attention in recent years on how to obtain user-interested content in massive data. At present, in the process of algorithm design of the recommending system, most methods ignore structural relationships between users. Therefore, in this paper, we designed a personalized sliding window for different users by combining timing information and network topology information, then extracted the information sequence of each user in the sliding window and obtained the similarity between users through sequence alignment. The algorithm only needs to extract part of the data in the original dataset, and the time series comparison shows that our method is superior to the traditional algorithm in recommendation Accuracy, Popularity, and Diversity

Effects of deposition paramaters on the microstructure evolution of wire arc additive manufactured Al–Zn–Mg–Cu alloy

Wire arc additive manufacturing (WAAM) is a suitable method for fabricating large high-strength components made of the Al–Zn–Mg–Cu alloy. However, the solidification behavior of this alloy is complex due to its composition. The inhomogeneous solidification microstructure results in numerous defects during the deposition process, hindering the application of the deposited Al–Zn–Mg–Cu alloy. This study aims to analyze the microstructure evolution under different process parameters and reveal the relationship between the solidification behavior of the molten pool, pore defects, and grain morphology. Thin-walled components based on Al–Zn–Mg–Cu alloy were fabricated using WAAM under different parameters. The results showed that increasing deposition current initially decreased and subsequently increased pore defects, while the proportion of twinned dendrites exhibited the opposite trend. A lower deposition speed reduced pore defects by promoting gas escape, whereas a higher deposition speed led to the precipitation of Al3Zr, grain refinement, and the suppression of twin dendrite growth. A faster wire feeding speed had a better suppression effect on defects, while a slower wire feeding speed inhibited the growth of twinned dendrites, promoting the directional growth of regular dendrites