Dataset on optimized biodiesel production from seeds of Vitis vinifera using ANN, RSM and ANFIS

This dataset disclose the investigational data on the extraction of bio-oil from seeds of Vitis vinifera through combination of mechanical pressing and soxhlet solvent extractor. Biodiesel is produced through single stage base catalysed transesterification process due to lower free fatty acid content in the Vitis vinifera bio-oil. Independent variable process parameters like molar ratio, reaction time and catalyst concentration are optimized using Artificial Neural Network, Response Surface Methodology and Adaptive Neuro-Fuzzy Interference System to predict the maximum biodiesel yield and the results are compared with the experimental data. Response Surface Methodology predicted a maximum Vitis vinifera biodiesel yield of 97.62% at methanol to oil molar ratio 0.2758 v/v, catalyst concentration 1.045 gm of NaOH and reaction duration of 1.11 hrs which is also confirmed with experimental results.

Tripled yield in direct-drive laser fusion through statistical modelling

Focusing laser light onto a very small target can produce the conditions for laboratory-scale nuclear fusion of hydrogen isotopes. The lack of accurate predictive models, which are essential for the design of high-performance laser-fusion experiments, is a major obstacle to achieving thermonuclear ignition. Here we report a statistical approach that was used to design and quantitatively predict the results of implosions of solid deuterium-tritium targets carried out with the 30-kilojoule OMEGA laser system, leading to tripling of the fusion yield to its highest value so far for direct-drive laser fusion. When scaled to the laser energies of the National Ignition Facility (1.9 megajoules), these targets are predicted to produce a fusion energy output of about 500 kilojoules-several times larger than the fusion yields currently achieved at that facility. This approach could guide the exploration of the vast parameter space of thermonuclear ignition conditions and enhance our understanding of laser-fusion physics.

Observations of Multiple Nuclear Reaction Histories and Fuel-Ion Species Dynamics in Shock-Driven Inertial Confinement Fusion Implosions

Fuel-ion species dynamics in hydrodynamiclike shock-driven DT^{3}He-filled inertial confinement fusion implosion is quantitatively assessed for the first time using simultaneously measured D^{3}He and DT reaction histories. These reaction histories are measured with the particle x-ray temporal diagnostic, which captures the relative timing between different nuclear burns with unprecedented precision (∼10  ps). The observed 50±10  ps earlier D^{3}He reaction history timing (relative to DT) cannot be explained by average-ion hydrodynamic simulations and is attributed to fuel-ion species separation between the D, T, and ^{3}He ions during shock convergence and rebound. At the onset of the shock burn, inferred ^{3}He/T fuel ratio in the burn region using the measured reaction histories is much higher as compared to the initial gas-filled ratio. As T and ^{3}He have the same mass but different charge, these results indicate that the charge-to-mass ratio plays an important role in driving fuel-ion species separation during strong shock propagation even for these hydrodynamiclike plasmas.

Relevance Predictability in Information Retrieval Systems

An experiment is described which attempts to derive quantitative indicators regarding the potential relevance predictability of the intermediate stimuli used to represent documents in information retrieval systems. In effect, since the decision to peruse an entire document is often predicated upon the examination of one »level of processing« of the document (e.g., the citation and/or abstract), it became interesting to analyze the properties of what constitutes »relevance«. However, prior to such an analysis, an even more elementary step had to be made, namely, to determine what portions of a document should be examined.

An evaluation of the ability of intermediate response products (IRPs), functioning as cues to the information content of full documents, to predict the relevance determination that would be subsequently made on these documents by motivated users of information retrieval systems, was made under controlled experimental conditions. The hypothesis that there might be other intermediate response products (selected extracts from the document, i.e., first paragraph, last paragraph, and the combination of first and last paragraph), that would be as representative of the full document as the traditional IRPs (citation and abstract) was tested systematically. The results showed that:

1. there is no significant difference among the several IRP treatment groups on the number of cue evaluations of relevancy which match the subsequent user relevancy decision on the document;

2. first and last paragraph combinations have consistently predicted relevancy to a higher degree than the other IRPs;

3. abstracts were undistinguished as predictors; and

4. the apparent high predictability rating for citations was not substantive.

Some of these results are quite different than would be expected from previous work with unmotivated subjects.

Feasibility and Clinical Utility of High-definition Transcranial Direct Current Stimulation in the Treatment of Persistent Hallucinations in Schizophrenia

Persistent auditory verbal hallucination is a clinically significant problem in schizophrenia. Recent studies suggest a promising role for add-on transcranial direct current stimulation (tDCS) in treatment. An optimised version of tDCS, namely high-definition tDCS (HD-tDCS), uses smaller electrodes arranged in a 4x1 ring configuration and may offer more focal and predictable neuromodulation than conventional tDCS. This case report illustrates the feasibility and clinical utility of add-on HD-tDCS over the left temporoparietal junction in a 4x1 ring configuration to treat persistent auditory verbal hallucination in schizophrenia.

Electron Shock Ignition of Inertial Fusion Targets

It is shown that inertial confinement fusion targets designed with low implosion velocities can be shock-ignited using laser-plasma interaction generated hot electrons (hot-e's) to obtain high energy gains. These designs are robust to multimode asymmetries and are predicted to ignite even for significantly distorted implosions. Electron shock ignition requires tens of kilojoules of hot-e's which can be produced only at a large laser facility like the National Ignition Facility, with the laser-to-hot-e conversion efficiency greater than 10% at laser intensities ∼10^{16}  W/cm^{2}.

Publisher's Note: Demonstration of Fuel Hot-Spot Pressure in Excess of 50 Gbar for Direct-Drive, Layered Deuterium-Tritium Implosions on OMEGA [Phys. Rev. Lett. 117, 025001 (2016)]

This corrects the article DOI: 10.1103/PhysRevLett.117.025001.

Demonstration of Fuel Hot-Spot Pressure in Excess of 50 Gbar for Direct-Drive, Layered Deuterium-Tritium Implosions on OMEGA

A record fuel hot-spot pressure P_{hs}=56±7  Gbar was inferred from x-ray and nuclear diagnostics for direct-drive inertial confinement fusion cryogenic, layered deuterium-tritium implosions on the 60-beam, 30-kJ, 351-nm OMEGA Laser System. When hydrodynamically scaled to the energy of the National Ignition Facility, these implosions achieved a Lawson parameter ∼60% of the value required for ignition [A. Bose et al., Phys. Rev. E 93, 011201(R) (2016)], similar to indirect-drive implosions [R. Betti et al., Phys. Rev. Lett. 114, 255003 (2015)], and nearly half of the direct-drive ignition-threshold pressure. Relative to symmetric, one-dimensional simulations, the inferred hot-spot pressure is approximately 40% lower. Three-dimensional simulations suggest that low-mode distortion of the hot spot seeded by laser-drive nonuniformity and target-positioning error reduces target performance.