Disinfection effect of povidone-iodine in aquaculture water of swamp eel (Monopterus albus)

The swamp eel (Monopterus albus) is an important commercial farmed fish species in China. However, it is susceptible to Aeromonas hydrophila infections, resulting in high mortality and considerable economic loss. Povidone-iodine (PVP-I) is a widely used chemical disinfectant in aquaculture, which can decrease the occurrence of diseases and improve the survival. However, environmental organic matter could affect the bactericidal effectiveness of PVP-I, and the efficacy of PVP-I in aquaculture water is still unknown. In this paper, disinfection assays were conducted to evaluate the effectiveness of PVP-I against the A. hydrophila in different types of water. We found that the effective germicidal concentration of PVP-I in outdoor aquaculture water was 25 ppm for 12 h. In indoor aquaculture water with 105 CFU/mL bacteria, 10 ppm and 20 ppm of PVP-I could kill 99% and 100% of the bacteria, respectively. The minimal germicidal concentration of PVP-I in Luria-Bertani broth was 4,000 ppm. Available iodine content assay in LB solutions confirmed that the organic substance had negative impact on the effectiveness of PVP-I, which was consistent with the different efficacy of PVP-I in different water samples. Acute toxicity tests showed that the 24 h-LC50 of PVP-I to swamp eel was 173.82 ppm, which was much higher than the germicidal concentrations in outdoor and indoor aquaculture water, indicating its safety and effectivity to control the A. hydrophila. The results indicated PVP-I can be helpful for preventing the transmission of A. hydrophila in swamp eel aquaculture

High-energy magnetic excitations from heavy quasiparticles in CeCu2_2Si2_2

Magnetic fluctuations is the leading candidate for pairing in cuprate, iron-based and heavy fermion superconductors. This view is challenged by the recent discovery of nodeless superconductivity in CeCu$_2$Si$_2$, and calls for a detailed understanding of the corresponding magnetic fluctuations. Here, we mapped out the magnetic excitations in \ys{superconducting (S-type)} CeCu$_2$Si$_2$ using inelastic neutron scattering, finding a strongly asymmetric dispersion for $E\lesssim1.5$~meV, which at higher energies evolve into broad columnar magnetic excitations that extend to $E\gtrsim 5$ meV. While low-energy magnetic excitations exhibit marked three-dimensional characteristics, the high-energy magnetic excitations in CeCu$_2$Si$_2$ are almost two-dimensional, reminiscent of paramagnons found in cuprate and iron-based superconductors. By comparing our experimental findings with calculations in the random-phase approximation,we find that the magnetic excitations in CeCu$_2$Si$_2$ arise from quasiparticles associated with its heavy electron band, which are also responsible for superconductivity. Our results provide a basis for understanding magnetism and superconductivity in CeCu$_2$Si$_2$, and demonstrate the utility of neutron scattering in probing band renormalization in heavy fermion metals

Mechanical and structural investigation of porous bulk metallic glasses

The intrinsic properties of advanced alloy systems can be altered by changing their microstructural features. Here, we present a highly efficient method to produce and characterize structures with systematically-designed pores embedded inside. The fabrication stage involves a combination of photolithography and deep reactive ion etching of a Si template replicated using the concept of thermoplastic forming. Pt- and Zr-based bulk metallic glasses (BMGs) were evaluated through uniaxial tensile test, followed by scanning electron microscope (SEM) fractographic and shear band analysis. Compositional investigation of the fracture surface performed via energy dispersive X-ray spectroscopy (EDX), as well as Auger spectroscopy (AES) shows a moderate amount of interdiffusion (5 at.% maximum) of the constituent elements between the deformed and undeformed regions. Furthermore, length-scale effects on the mechanical behavior of porous BMGs were explored through molecular dynamics (MD) simulations, where shear band formation is observed for a material width of 18 nm

Scale Up Event Extraction Learning via Automatic Training Data Generation

The task of event extraction has long been investigated in a supervised learning paradigm, which is bound by the number and the quality of the training instances. Existing training data must be manually generated through a combination of expert domain knowledge and extensive human involvement. However, due to drastic efforts required in annotating text, the resultant datasets are usually small, which severally affects the quality of the learned model, making it hard to generalize. Our work develops an automatic approach for generating training data for event extraction. Our approach allows us to scale up event extraction training instances from thousands to hundreds of thousands, and it does this at a much lower cost than a manual approach. We achieve this by employing distant supervision to automatically create event annotations from unlabelled text using existing structured knowledge bases or tables.We then develop a neural network model with post inference to transfer the knowledge extracted from structured knowledge bases to automatically annotate typed events with corresponding arguments in text.We evaluate our approach by using the knowledge extracted from Freebase to label texts from Wikipedia articles. Experimental results show that our approach can generate a large number of highquality training instances. We show that this large volume of training data not only leads to a better event extractor, but also allows us to detect multiple typed events

Disentangling superconducting and magnetic orders in NaFe_1-xNi_xAs using muon spin rotation

Muon spin rotation and relaxation studies have been performed on a "111" family of iron-based superconductors NaFe_1-xNi_xAs. Static magnetic order was characterized by obtaining the temperature and doping dependences of the local ordered magnetic moment size and the volume fraction of the magnetically ordered regions. For x = 0 and 0.4 %, a transition to a nearly-homogeneous long range magnetically ordered state is observed, while for higher x than 0.4 % magnetic order becomes more disordered and is completely suppressed for x = 1.5 %. The magnetic volume fraction continuously decreases with increasing x. The combination of magnetic and superconducting volumes implies that a spatially-overlapping coexistence of magnetism and superconductivity spans a large region of the T-x phase diagram for NaFe_1-xNi_xAs . A strong reduction of both the ordered moment size and the volume fraction is observed below the superconducting T_C for x = 0.6, 1.0, and 1.3 %, in contrast to other iron pnictides in which one of these two parameters exhibits a reduction below TC, but not both. The suppression of magnetic order is further enhanced with increased Ni doping, leading to a reentrant non-magnetic state below T_C for x = 1.3 %. The reentrant behavior indicates an interplay between antiferromagnetism and superconductivity involving competition for the same electrons. These observations are consistent with the sign-changing s-wave superconducting state, which is expected to appear on the verge of microscopic coexistence and phase separation with magnetism. We also present a universal linear relationship between the local ordered moment size and the antiferromagnetic ordering temperature TN across a variety of iron-based superconductors. We argue that this linear relationship is consistent with an itinerant-electron approach, in which Fermi surface nesting drives antiferromagnetic ordering.Comment: 20 pages, 14 figures, Correspondence should be addressed to Prof. Yasutomo Uemura: [email protected]

Dietary polyphenols as antidiabetic agents: Advances and opportunities

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Genome-Wide Identification and Characterization of BrrTCP Transcription Factors in Brassica rapa ssp. rapa

The teosinte branched1/cycloidea/proliferating cell factor (TCP) gene family is a plant-specific transcription factor that participates in the control of plant development by regulating cell proliferation. However, no report is currently available about this gene family in turnips (Brassica rapa ssp. rapa). In this study, a genome-wide analysis of TCP genes was performed in turnips. Thirty-nine TCP genes in turnip genome were identified and distributed on 10 chromosomes. Phylogenetic analysis clearly showed that the family was classified as two clades: class I and class II. Gene structure and conserved motif analysis showed that the same clade genes have similar gene structures and conserved motifs. The expression profiles of 39 TCP genes were determined through quantitative real-time PCR. Most CIN-type BrrTCP genes were highly expressed in leaf. The members of CYC/TB1 subclade are highly expressed in flower bud and weakly expressed in root. By contrast, class I clade showed more widespread but less tissue-specific expression patterns. Yeast two-hybrid data show that BrrTCP proteins preferentially formed heterodimers. The function of BrrTCP2 was confirmed through ectopic expression of BrrTCP2 in wild-type and loss-of-function ortholog mutant of Arabidopsis. Overexpression of BrrTCP2 in wild-type Arabidopsis resulted in the diminished leaf size. Overexpression of BrrTCP2 in triple mutants of tcp2/4/10 restored the leaf phenotype of tcp2/4/10 to the phenotype of wild type. The comprehensive analysis of turnip TCP gene family provided the foundation to further study the roles of TCP genes in turnips

Individual differences in false memory from misinformation: Cognitive factors

This research investigated the cognitive correlates of false memories that are induced by the misinformation paradigm. A large sample of Chinese college students (N=436) participated in a misinformation procedure and also took a battery of cognitive tests. Results revealed sizable and systematic individual differences in false memory arising from exposure to misinformation. False memories were significantly and negatively correlated with measures of intelligence (measured with Raven's Advanced Progressive Matrices and Wechsler Adult Intelligence Scale), perception (Motor-Free Visual Perception Test, Change Blindness, and Tone Discrimination), memory (Wechsler Memory Scales and 2-back Working Memory tasks), and face judgement (Face Recognition and Facial Expression Recognition). These findings suggest that people with relatively low intelligence and poor perceptual abilities might be more susceptible to the misinformation effect