Novel transport properties of nanostructured α-Fe2O3

Nanophase materials with an average grain sizes ranging from 2 to 20 nm exhibit novel properties relative to conventional materials. Recently, we reported that the mechanical milling of Fe3O4 powders produced nanometer sized particles (∼7 nm) which exhibited a phase transition from cubic (Fe3O4) to hexagonal (α-Fe2O3) phase. In this paper, we present results on the synthesis of nanosized α-Fe2O3 produced by mechanical milling for 1 to 10 h. Some unusual electrical conductivity characteristics were observed. The X-ray diffraction analyses show only the presence characteristic lines of hematite in the ball milled samples. Particle sizes measured from X-ray line broadening varied from 7 to 11 nm. TEM micrograph for the ball milled samples show distribution of particle size. A drastic change of electrical resistivity has been observed from the electrical measurements of different ball milled samples. The resistivity variation of the unmilled sample can be ascribed to typical band conduction. A decrease of about two orders of magnitude of resistivity was observed for the specimen ball milled for 10 h. The resistivity variation of the two activated processes was observed with activation energies of ∼ 0.06 and ∼ 0.7eV, respectively. Large and small particle sizes are responsible for the two activation energies

Opinion of Health Care Professionals towards Submitting a Research Article to a Journal.

There are no specific criteria to measure a journals quality, but indexation of a journal in a reputed database such as PubMed/Medline, SCOPUS, EMBASE etc, and whether the journal is having an impact factor produced by Thomson Reuters are looked upon. Many more indexation database have come up recently, and authors are publishing more articles than before. This questionnaire based study was conducted in November 2012 in two medical colleges in south India with the aim to know the opinion of health care professionals towards submitting a research publication to a journal. Prior approval was taken from the Institutional Ethics Committee to conduct the study. The selected participants were from tutors to professors. The information was recorded and analyzed using Microsoft Excel (2007 version). A total of 297 respondents participated in the study, out of which 263 completed the questionnaire. Assistant professors had more number of publications and also had the maximum number of publications as first author. Among the papers published <10% were published in journals which are pubmed indexed. Highest percentage of pubmed indexed journals were published by professors which was around 10%. The knowledge about impact factor was higher among the junior faculty than the professors. The knowledge regarding quality of a journal, with respect to indexation and impact factor of a journal is grossly inadequate among the doctors. Necessary steps should be taken by editorial board of reputed journals and associations such as International Council Of Medical Journal Editors or regulatory authorities such as Medical Council of India to spread the knowledge about quality of a journal

State-Action Similarity-Based Representations for Off-Policy Evaluation

In reinforcement learning, off-policy evaluation (OPE) is the problem of estimating the expected return of an evaluation policy given a fixed dataset that was collected by running one or more different policies. One of the more empirically successful algorithms for OPE has been the fitted q-evaluation (FQE) algorithm that uses temporal difference updates to learn an action-value function, which is then used to estimate the expected return of the evaluation policy. Typically, the original fixed dataset is fed directly into FQE to learn the action-value function of the evaluation policy. Instead, in this paper, we seek to enhance the data-efficiency of FQE by first transforming the fixed dataset using a learned encoder, and then feeding the transformed dataset into FQE. To learn such an encoder, we introduce an OPE-tailored state-action behavioral similarity metric, and use this metric and the fixed dataset to learn an encoder that models this metric. Theoretically, we show that this metric allows us to bound the error in the resulting OPE estimate. Empirically, we show that other state-action similarity metrics lead to representations that cannot represent the action-value function of the evaluation policy, and that our state-action representation method boosts the data-efficiency of FQE and lowers OPE error relative to other OPE-based representation learning methods on challenging OPE tasks. We also empirically show that the learned representations significantly mitigate divergence of FQE under varying distribution shifts. Our code is available here: https://github.com/Badger-RL/ROPE.Comment: Accepted to Neural Information Processing Systems (NeurIPS) 202

Bis(acetyl­acetonato-κ2 O,O′)(pyridine-κN)zinc(II)

In the title compound, [Zn(C5H7O2)2(C5H5N)], the metal atom has square-pyramidal coordination geometry with the basal plane defined by the four O atoms of the chelating acetyl­acetonate ligands and with the axial position occupied by the pyridine N atom. The crystal packing is characterized by a C—H⋯O hydrogen-bonded ribbon structure approximately parallel to [10]

Response of preservative chemicals on the shelf life of cut lilium (Lilium spp.) flower cv. ‘Pavia’

Lilium cut flowers have commercial importance and extending their vase life is vital. An increase in the vase life quality and quantity can directly increase the viability and price realization of commercially important flowers like lilium. Shelf life of cut lilium flower is influenced by using different preservative chemicals and sucrose added in vase solution. Such an extension of vase life can be achieved via chemical treatment. The trial was carried out to examine the effect of various concentration of two chemicals, AgNO3 (silver nitrate) and 8-HQC (8-Hydroxyquinoline citrate) along with sucrose on the shelf life of lilium cut flower cv. ‘Pavia’ (cross between Asiatic and Longiflorum lilies). In the experiment, sucrose (20%), 8-HQC at 3 concentrations (100, 150, 200 ppm) and AgNO3 at 3 concentrations (50, 75, 100 ppm) and water (distilled) as control were tested alone and with combinations. Cut flowers of lilium were treated at one bud opening stage. The trial was carried out in a completely randomized design (CRD) having 16 treatments and one control in three (3) replications. The fresh weight and relative fresh weight of the cut flower spike, opening of all flowers on a spike, vase solution uptake on a day, total vase solution uptake and vase life of lilium cut flower spike showed the best outcome with AgNO3 (50 ppm) and 20% sucrose treatment combination. Out of the two chemicals, silver nitrate showed better results than 8-HQC as a preservative in enhancing the shelf life of cut Lilium flower cv. ‘Pavia’. Analysis of this new and exciting method will be useful to research institutes, commercial producers, wholesalers, retailers, consumers or anyone to choose right chemical and concentration of holding solution to maximize the post-harvest life of lilium cut flowers