A nanoflare model for active region radiance: application of artificial neural networks

Context. Nanoflares are small impulsive bursts of energy that blend with and possibly make up much of the solar background emission. Determining their frequency and energy input is central to understanding the heating of the solar corona. One method is to extrapolate the energy frequency distribution of larger individually observed flares to lower energies. Only if the power law exponent is greater than 2, is it considered possible that nanoflares contribute significantly to the energy input. Aims. Time sequences of ultraviolet line radiances observed in the corona of an active region are modelled with the aim of determining the power law exponent of the nanoflare energy distribution. Methods. A simple nanoflare model based on three key parameters (the flare rate, the flare duration time, and the power law exponent of the flare energy frequency distribution) is used to simulate emission line radiances from the ions Fe XIX, Ca XIII, and Si iii, observed by SUMER in the corona of an active region as it rotates around the east limb of the Sun. Light curve pattern recognition by an Artificial Neural Network (ANN) scheme is used to determine the values. Results. The power law exponents, alpha 2.8, 2.8, and 2.6 for Fe XIX, Ca XIII, and Si iii respectively. Conclusions. The light curve simulations imply a power law exponent greater than the critical value of 2 for all ion species. This implies that if the energy of flare-like events is extrapolated to low energies, nanoflares could provide a significant contribution to the heating of active region coronae.Comment: 4 pages, 5 figure

Soybean Yield, Evapotranspiration, Water Productivity, And Soil Water Extraction Response To Subsurface Drip Irrigation And Fertigation

Soybean [Glycine max (L.) Merr.] yield, irrigation water use efficiency (IWUE), crop water use efficiency (CWUE), evapotranspiration water use efficiency (ETWUE), and soil water extraction response to eleven treatments of full, limited, or delayed irrigation versus a rainfed control were investigated using a subsurface drip irrigation (SDI) system at a research site in south-central Nebraska. The SDI system laterals were 0.40 m deep in every other row middle of 0.76 m spaced plant rows. Actual evapotranspiration (ETa) was quantified in all treatments and used to schedule irrigation events on a 100% ETa replacement basis in all but three of the eleven treatments (i.e., 75% ETa replacement was used in two, and 60% ETa replacement was used in one). The irrigation amount (Ia) applied at each event was 100% of the ETa amount, except for two 100% ETa treatments in which only 65% or 50% of the water needed to cover the treatment plot area was applied to enable a test of a partial surface area-based irrigation approach. The first irrigation event was delayed until soybean stage R3 (begin pod) in two 100% Ia treatments, but thereafter they were irrigated with either 100% or 75% ETa replacement. Two 100% ETa and 100% Ia treatments also were used to evaluate soybean response to nitrogen (N) application methods (i.e., a preplant method versus N injection using the SDI system). Soybean ETa varied from 452 mm for the rainfed treatment to 600 mm (30% greater) for the fully irrigated treatment (100% ETa and 100% Ia) in 2007, and from 473 to 579 mm (20% greater) for the same treatments, respectively, in 2008. Among the irrigated treatments, 100% ETa and 65% Ia had the lowest 2007 ETa value (557 mm), whereas 100% ETa and 50% Ia had the lowest 2008 ETa (498 mm). The 100%, 75%, and 60% ETa treatments with 100% Ia had respective actual ETa values that declined linearly in 2008 (i.e., 579, 538, and 498 mm), but not in 2007. Seasonal totals for ETa versus Ia exhibited a linear relationship (R2 = 0.68 in 2007 and R2 = 0.67 in 2008). Irrigation enhanced soybean yields from rainfed yield baselines of 4.04 ton ha-1 in 2007 and 4.82 ton ha-1 in 2008) to a maximum of 4.94 ton ha-1 attained in 2007 with the delay to R3 irrigation treatment (its yield was significantly greater, p \u3c 0.05, than that of the seven other treatments) and 4.97 ton ha-1 attained in 2008 with the 100% ETa and 100% Ia preplant N treatment. Seed yield had a quadratic relationship with irrigation water applied and a linear relationship with ETa that was stronger in the drier year of 2007. Each 25.4 mm incremental increase in seasonal irrigation water applied increased soybean yield by 0.323 ton ha-1 (beyond the intercept) in 2007 and by 0.037 ton ha-1 in 2008. Each 25.4 mm increase in ETa generated a yield increase of 0.114 ton ha-1 (beyond the intercept) in 2007, but only 0.02 ton ha-1 in the wetter year of 2008. This research demonstrated that delaying the onset of irrigation until the R3 stage and practicing full irrigation thereafter for soybean grown on silt loam soils resulted in yields (and crop water productivity) that were similar to full-season irrigation scheduling strategies, and this result may be applicable in other regions with edaphic and climatic characteristics similar to those in south-central Nebraska

Robust Stimulation of Humoral and Cellular Immune Responses following Vaccination with Antigen-Loaded beta-Glucan Particles

beta-Glucan particles (GPs) are purified Saccharomyces cerevisiae cell walls treated so that they are primarily beta1,3-d-glucans and free of mannans and proteins. GPs are phagocytosed by dendritic cells (DCs) via the Dectin-1 receptor, and this interaction stimulates proinflammatory cytokine secretion by DCs. As the hollow, porous GP structure allows for high antigen loading, we hypothesized that antigen-loaded GPs could be exploited as a receptor-targeted vaccine delivery system. Ovalbumin (OVA) was electrostatically complexed inside the hollow GP shells (GP-OVA). Incubation of C57BL/6J mouse bone marrow-derived DCs with GP-OVA resulted in phagocytosis, upregulation of maturation markers, and rapid proteolysis of OVA. Compared with free OVA, GP-OVA was \u3e100-fold more potent at stimulating the proliferation of OVA-reactive transgenic CD8(+) OT-I and CD4(+) OT-II T cells, as measured by in vitro [(3)H]thymidine incorporation using DCs as antigen-presenting cells. Next, immune responses in C57BL/6J mice following subcutaneous immunizations with GP-OVA were compared with those in C57BL/6J mice following subcutaneous immunizations with OVA absorbed onto the adjuvant alum (Alum/OVA). Vaccination with GP-OVA stimulated substantially higher antigen-specific CD4(+) T-cell lymphoproliferative and enzyme-linked immunospot (ELISPOT) responses than that with Alum/OVA. Moreover, the T-cell responses induced by GP-OVA were Th1 biased (determined by gamma interferon [IFN-gamma] ELISPOT assay) and Th17 biased (determined by interleukin-17a [IL-17a] ELISPOT assay). Finally, both the GP-OVA and Alum/OVA formulations induced strong secretions of IgG1 subclass anti-OVA antibodies, although only GP-OVA induced secretion of Th1-associated IgG2c antibodies. Thus, the GP-based vaccine platform combines adjuvanticity and antigen delivery to induce strong humoral and Th1- and Th17-biased CD4(+) T-cell responses

Soybean Yield, Evapotranspiration, Water Productivity, And Soil Water Extraction Response To Subsurface Drip Irrigation And Fertigation

Soybean [Glycine max (L.) Merr.] yield, irrigation water use efficiency (IWUE), crop water use efficiency (CWUE), evapotranspiration water use efficiency (ETWUE), and soil water extraction response to eleven treatments of full, limited, or delayed irrigation versus a rainfed control were investigated using a subsurface drip irrigation (SDI) system at a research site in south-central Nebraska. The SDI system laterals were 0.40 m deep in every other row middle of 0.76 m spaced plant rows. Actual evapotranspiration (ETa) was quantified in all treatments and used to schedule irrigation events on a 100% ETa replacement basis in all but three of the eleven treatments (i.e., 75% ETa replacement was used in two, and 60% ETa replacement was used in one). The irrigation amount (Ia) applied at each event was 100% of the ETa amount, except for two 100% ETa treatments in which only 65% or 50% of the water needed to cover the treatment plot area was applied to enable a test of a partial surface area-based irrigation approach. The first irrigation event was delayed until soybean stage R3 (begin pod) in two 100% Ia treatments, but thereafter they were irrigated with either 100% or 75% ETa replacement. Two 100% ETa and 100% Ia treatments also were used to evaluate soybean response to nitrogen (N) application methods (i.e., a preplant method versus N injection using the SDI system). Soybean ETa varied from 452 mm for the rainfed treatment to 600 mm (30% greater) for the fully irrigated treatment (100% ETa and 100% Ia) in 2007, and from 473 to 579 mm (20% greater) for the same treatments, respectively, in 2008. Among the irrigated treatments, 100% ETa and 65% Ia had the lowest 2007 ETa value (557 mm), whereas 100% ETa and 50% Ia had the lowest 2008 ETa (498 mm). The 100%, 75%, and 60% ETa treatments with 100% Ia had respective actual ETa values that declined linearly in 2008 (i.e., 579, 538, and 498 mm), but not in 2007. Seasonal totals for ETa versus Ia exhibited a linear relationship (R2 = 0.68 in 2007 and R2 = 0.67 in 2008). Irrigation enhanced soybean yields from rainfed yield baselines of 4.04 ton ha-1 in 2007 and 4.82 ton ha-1 in 2008) to a maximum of 4.94 ton ha-1 attained in 2007 with the delay to R3 irrigation treatment (its yield was significantly greater, p \u3c 0.05, than that of the seven other treatments) and 4.97 ton ha-1 attained in 2008 with the 100% ETa and 100% Ia preplant N treatment. Seed yield had a quadratic relationship with irrigation water applied and a linear relationship with ETa that was stronger in the drier year of 2007. Each 25.4 mm incremental increase in seasonal irrigation water applied increased soybean yield by 0.323 ton ha-1 (beyond the intercept) in 2007 and by 0.037 ton ha-1 in 2008. Each 25.4 mm increase in ETa generated a yield increase of 0.114 ton ha-1 (beyond the intercept) in 2007, but only 0.02 ton ha-1 in the wetter year of 2008. This research demonstrated that delaying the onset of irrigation until the R3 stage and practicing full irrigation thereafter for soybean grown on silt loam soils resulted in yields (and crop water productivity) that were similar to full-season irrigation scheduling strategies, and this result may be applicable in other regions with edaphic and climatic characteristics similar to those in south-central Nebraska

Intelligent opinion mining and sentiment analysis using artificial neural networks

The article formulates a rigorously developed concept of opinion mining and sentiment analysis using hybrid neural networks. This conceptual method for processing natural-language text enables a variety of analyses of the subjective content of texts. It is a methodology based on hybrid neural networks for detecting subjective content and potential opinions, as well as a method which allows us to classify different opinion type and sentiment score classes. Moreover, a general processing scheme, using neural networks, for sentiment and opinion analysis has been presented. Furthermore, a methodology which allows us to determine sentiment regression has been devised. The paper proposes a method for classification of the text being examined based on the amount of positive, neutral or negative opinion it contains. The research presented here offers the possibility of motivating and inspiring further development of the methods that have been elaborated in this paper.Stuart, KDC.; Majewski, M. (2015). Intelligent opinion mining and sentiment analysis using artificial neural networks. Lecture Notes in Computer Science. 9492:103-110. doi:10.1007/978-3-319-26561-2_13S1031109492Feldman, R.: Techniques and applications for sentiment analysis. Commun. ACM 56(4), 82–89 (2013)Taboada, M., Brooke, J., Tofiloski, M., Voll, K., Stede, M.: Lexicon-based methods for sentiment analysis. Comput. Linguist. 37(2), 267–307 (2011)Mohammad, S.M., Turney, P.D.: Crowdsourcing a word-emotion association lexicon. Comput. Intell. 29(3), 436–465 (2013)Chen, H., Zimbra, D.: AI and opinion mining. IEEE Intell. Syst. 25(3), 74–80 (2010)Majewski, M., Zurada, J.M.: Sentence recognition using artificial neural networks. Knowl. Based Syst. 21(7), 629–635 (2008)Kacalak, W., Stuart, K.D., Majewski, M.: Intelligent natural language processing. In: Jiao, L., Wang, L., Gao, X., Liu, J., Wu, F. (eds.) ICNC 2006. LNCS, vol. 4221, pp. 584–587. Springer, Heidelberg (2006)Kacalak, W., Stuart, K., Majewski, M.: Selected problems of intelligent handwriting recognition. In: Melin, P., Castillo, O., Ramírez, E.G., Kacprzyk, J., Pedrycz, W. (eds.) IFSA 2007. Advances in Soft Computing, vol. 41, pp. 298–305. Springer, Cancun (2007)Stuart, K.D., Majewski, M.: Selected problems of knowledge discovery using artificial neural networks. In: Liu, D., Fei, S., Hou, Z., Zhang, H., Sun, C. (eds.) ISNN 2007, Part III. LNCS, vol. 4493, pp. 1049–1057. Springer, Heidelberg (2007)Stuart, K., Majewski, M.: A new method for intelligent knowledge discovery. In: Castillo, O., Melin, P., Ross, O.M., Cruz, R.S., Pedrycz, W., Kacprzyk, J. (eds.) IFSA 2007. Advances in Soft Computing, vol. 42, pp. 721–729. Springer, Heidelberg (2007)Stuart, K.D., Majewski, M.: Artificial creativity in linguistics using evolvable fuzzy neural networks. In: Hornby, G.S., Sekanina, L., Haddow, P.C. (eds.) ICES 2008. LNCS, vol. 5216, pp. 437–442. Springer, Heidelberg (2008)Stuart, K.D., Majewski, M.: Evolvable neuro-fuzzy system for artificial creativity in linguistics. In: Huang, D.-S., Wunsch II, D.C., Levine, D.S., Jo, K.-H. (eds.) ICIC 2008. LNCS (LNAI), vol. 5227, pp. 46–53. Springer, Heidelberg (2008)Stuart, K.D., Majewski, M., Trelis, A.B.: Selected problems of intelligent corpus analysis through probabilistic neural networks. In: Zhang, L., Lu, B.-L., Kwok, J. (eds.) ISNN 2010, Part II. LNCS, vol. 6064, pp. 268–275. Springer, Heidelberg (2010)Stuart, K.D., Majewski, M., Trelis, A.B.: Intelligent semantic-based system for corpus analysis through hybrid probabilistic neural networks. In: Liu, D., Zhang, H., Polycarpou, M., Alippi, C., He, H. (eds.) ISNN 2011, Part I. LNCS, vol. 6675, pp. 83–92. Springer, Heidelberg (2011)Specht, D.F.: Probabilistic neural networks. Neural Netw. 3(1), 109–118 (1990)Specht, D.F.: A general regression neural network. IEEE Trans. Neural Netw. 2(6), 568–576 (1991

Congenital Prosopagnosia: Multistage Anatomical and Functional Deficits in Face Processing Circuitry

Face recognition is a primary social skill which depends on a distributed neural network. A pronounced face recognition deficit in the absence of any lesion is seen in congenital prosopagnosia. This study investigating 24 congenital prosopagnosic subjects and 25 control subjects aims at elucidating its neural basis with fMRI and voxel-based morphometry. We found a comprehensive behavioral pattern, an impairment in visual recognition for faces and buildings that spared long-term memory for faces with negative valence. Anatomical analysis revealed diminished gray matter density in the bilateral lingual gyrus, the right middle temporal gyrus, and the dorsolateral prefrontal cortex. In most of these areas, gray matter density correlated with memory success. Decreased functional activation was found in the left fusiform gyrus, a crucial area for face processing, and in the dorsolateral prefrontal cortex, whereas activation of the medial prefrontal cortex was enhanced. Hence, our data lend strength to the hypothesis that congenital prosopagnosia is explained by network dysfunction and suggest that anatomic curtailing of visual processing in the lingual gyrus plays a substantial role. The dysfunctional circuitry further encompasses the fusiform gyrus and the dorsolateral prefrontal cortex, which may contribute to their difficulties in long-term memory for complex visual information. Despite their deficits in face identity recognition, processing of emotion related information is preserved and possibly mediated by the medial prefrontal cortex. Congenital prosopagnosia may, therefore, be a blueprint of differential curtailing in networks of visual cognition

Shaping the Phase of a Single Photon

While the phase of a coherent light field can be precisely known, the phase of the individual photons that create this field, considered individually, cannot. Phase changes within single-photon wave packets, however, have observable effects. In fact, actively controlling the phase of individual photons has been identified as a powerful resource for quantum communication protocols. Here we demonstrate the arbitrary phase control of a single photon. The phase modulation is applied without affecting the photon's amplitude profile and is verified via a two-photon quantum interference measurement, which can result in the fermionic spatial behaviour of photon pairs. Combined with previously demonstrated control of a single photon's amplitude, frequency, and polarisation, the fully deterministic phase shaping presented here allows for the complete control of single-photon wave packets.Comment: 4 pages, 4 figure

Chitosan but not chitin activates the inflammasome by a mechanism dependent upon phagocytosis

Chitin is an abundant polysaccharide found in fungal cell walls, crustacean shells, and insect exoskeletons. The immunological properties of both chitin and its deacetylated derivative chitosan are of relevance because of frequent natural exposure and their use in medical applications. Depending on the preparation studied and the end point measured, these compounds have been reported to induce allergic responses, inflammatory responses, or no response at all. We prepared highly purified chitosan and chitin and examined the capacity of these glycans to stimulate murine macrophages to release the inflammasome-associated cytokine IL-1beta. We found that although chitosan was a potent NLRP3 inflammasome activator, acetylation of the chitosan to chitin resulted in a near total loss of activity. The size of the chitosan particles played an important role, with small particles eliciting the greatest activity. An inverse relationship between size and stimulatory activity was demonstrated using chitosan passed through size exclusion filters as well as with chitosan-coated beads of defined size. Partial digestion of chitosan with pepsin resulted in a larger fraction of small phagocytosable particles and more potent inflammasome activity. Inhibition of phagocytosis with cytochalasin D abolished the IL-1beta stimulatory activity of chitosan, offering an explanation for why the largest particles were nearly devoid of activity. Thus, the deacetylated polysaccharide chitosan potently activates the NLRP3 inflammasome in a phagocytosis-dependent manner. In contrast, chitin is relatively inert

Lung eosinophils elicited during allergic and acute aspergillosis express RORgammat and IL-23R but do not require IL-23 for IL-17 production

Exposure to the mold, Aspergillus, is ubiquitous and generally has no adverse consequences in immunocompetent persons. However, invasive and allergic aspergillosis can develop in immunocompromised and atopic individuals, respectively. Previously, we demonstrated that mouse lung eosinophils produce IL-17 in response to stimulation by live conidia and antigens of A. fumigatus. Here, we utilized murine models of allergic and acute pulmonary aspergillosis to determine the association of IL-23, IL-23R and RORgammat with eosinophil IL-17 expression. Following A. fumigatus stimulation, a population of lung eosinophils expressed RORgammat, the master transcription factor for IL-17 regulation. Eosinophil RORgammat expression was demonstrated by flow cytometry, confocal microscopy, western blotting and an mCherry reporter mouse. Both nuclear and cytoplasmic localization of RORgammat in eosinophils were observed, although the former predominated. A population of lung eosinophils also expressed IL-23R. While expression of IL-23R was positively correlated with expression of RORgammat, expression of RORgammat and IL-17 was similar when comparing lung eosinophils from A. fumigatus-challenged wild-type and IL-23p19-/- mice. Thus, in allergic and acute models of pulmonary aspergillosis, lung eosinophils express IL-17, RORgammat and IL-23R. However, IL-23 is dispensable for production of IL-17 and RORgammat