In-Situ Non-intrusive Diagnostics of Toluene Removal by a Gliding Arc Discharge Using Planar Laser-Induced Fluorescence

A non-equilibrium gliding arc discharge anchored on two diverging stainless steel electrodes was extended into open air by a toluene-containing air jet. The removal process of the toluene by the non-equilibrium gliding arc discharge was investigated through in situ and non-intrusive laser-based techniques. Simultaneous planar laser-induced fluorescence (PLIF) of toluene and OH radicals were employed to achieve on-line visualization of the toluene decomposing process by the gliding arc discharge column. Toluene PLIF images with high spatial and temporal resolution showed that the non-equilibrium plasma of the gliding arc discharge is effective in decomposing toluene molecules. Instantaneous toluene removal efficiency was estimated from the toluene PLIF images, showing that the initial toluene concentrations and oxygen concentrations affected the toluene removal efficiency. The toluene removal efficiency decreased with the initial toluene concentration, whereas the efficiency increased with the oxygen concentration. The OH generation in the discharge was found to be enhanced with an increase of the toluene concentration from the OH PLIF results. The relative instantaneous distribution between the OH produced from the discharge channels and the toluene flow was simultaneously visualized. The instantaneous distributions of toluene and OH radicals that were acquired simultaneously by PLIF, were well complementary, suggesting that radicals generated by the gliding arc discharge were responsible for toluene removal in the active volume of the gliding arc discharge. The effective width of the plasma volume for the toluene removal were measured, which gives a new insight into the optimization of industrial design for practical gliding arc reactors

6,6-Dimethyl-2H,5H,6H,7H-1,3-dithiolo[4,5-f][1,5,3]dithia­silepin-2-one

In the structure of the title compound, C7H10OS4Si, the carbonyl O atom lies in the plane of the five-membered dithiole ring with a deviation of only 0.022 (2) Å. The seven-membered ring adopts a chair conformation. The crystal packing is stabilized by S⋯O [3.096 (4) Å] and S⋯S [3.620 (4) Å] contacts, together with C—H⋯S inter­actions

A New Classification Network for Diagnosing Alzheimer’s Disease in class-imbalance MRI datasets

Automatic identification of Alzheimer’s Disease (AD) through magnetic resonance imaging (MRI) data can eectively assist to doctors diagnose and treat Alzheimer’s. Current methods improve the accuracy of AD recognition, but they are insufficient to address the challenge of small interclass and large intraclass dierences. Some studies attempt to embed patch-level structure in neural networks which enhance pathologic details, but the enormous size and time complexity render these methods unfavorable. Furthermore, several self-attention mechanisms fail to provide contextual information to represent discriminative regions, which limits the performance of these classifiers. In addition, the current loss function is adversely aected by outliers of class imbalance and may fall into local optimal values. Therefore, we propose a 3D Residual RepVGG Attention network (ResRepANet) stacked with several lightweight blocks to identify the MRI of brain disease, which can also trade o accuracy and flexibility. Specifically, we propose a Non-local Context Spatial Attention block (NCSA) and embed it in our proposed ResRepANet, which aggregates global contextual information in spatial features to improve semantic relevance in discriminative regions. In addition, in order to reduce the influence of outliers, we propose a Gradient Density Multiple-weighting Mechanism (GDMM) to automatically adjust the weights of each MRI image via a normalizing gradient norm. Experiments are conducted on datasets from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and Australian Imaging, Biomarker and Lifestyle Flagship Study of Aging (AIBL). Experiments on both datasets show that the accuracy, sensitivity, specificity, and Area Under the Curve are consistently better than for state-of-the-art methods

Translational, rotational and vibrational temperatures of a gliding arc discharge at atmospheric pressure air

Gliding arc discharges have generally been used to generate non-equilibrium plasma at atmospheric pressure. Temperature distributions of a gliding arc are of great interest both for fundamental plasma research and for practical applications. In the presented studies, translational, rotational and vibrational temperatures of a gliding arc generated at atmospheric pressure air are investigated. Translational temperatures (about 1100 K) were measured by laser-induced Rayleigh scattering, and two-dimensional temperature imaging was performed. Rotational and vibrational temperatures (about 3600 K and 6700 K, respectively) were obtained by simulating the measured emission spectra of OH

Effects of Radiation Reabsorption on the Laminar Flame Speed and NO Emission during Aviation Kerosene Combustion at Elevated Pressures

Increasing attention has been paid on combustion stability and pollution emission of aviation kerosene due to the emerging interests on supersonic combustion scramjets. Whereas the vitiation component H2O introduced by hydrogen-fueled heaters in high-enthalpy vitiated air during ground experiments has a considerable influence on kerosene combustion, especially through its radiation effect, which needs to be further investigated. In this paper, the radiation reabsorption effects on laminar flame speeds and NO emissions during RP-3/H2O/O2/N2 combustion was assessed numerically over a wide range of equivalence ratio and pressure (ϕ = 0.7–1.4 and P = 1–15 atm) using detailed chemical and radiation models. The surrogate model of RP-3 consisted of vol. 25% 1,3,5-trimethylbenzene (C9H12), 46.31% n-decane (C10H22) and 28.69% iso-dodecane (IC12H26), while the vitiated air had 12% H2O. It was revealed that the radiation reabsorption of H2O in the vitiated air had significant impact on the accurate simulation of laminar flame speeds. As equivalence ratios varied, the role of radiation reabsorption on laminar flame speeds was most pronounced at ϕ = 0.7. As the key radical, the generation of H through the reversed step of CH2OH + H = CH3 + OH was chemically inhibited due to radiation. The radiation reabsorption effect on flame speeds was strengthened with rising pressures, with the reaction H + O2 = O + OH dominant at the pressure range 1–10 atm. In contrast, a slight increase in the impact on laminar flame speeds between 10 and 15 atm was controlled by direct radiative effect. Finally, for NO emission, the reduction of downstream temperature caused by radiative heat loss and the increment of radical concentrations induced by preheating determined radiation reabsorption effects on NO generation

Translational, rotational, vibrational and electron temperatures of a gliding arc discharge

Translational, rotational, vibrational and electron temperatures of a gliding arc discharge in atmospheric pressure air were experimentally investigated using in situ, non-intrusive optical diagnostic techniques. The gliding arc discharge was driven by a 35 kHz alternating current (AC) power source and operated in a glow-type regime. The two-dimensional distribution of the translational temperature (Tt) of the gliding arc discharge was determined using planar laser-induced Rayleigh scattering. The rotational and vibrational temperatures were obtained by simulating the experimental spectra. The OH A–X (0, 0) band was used to simulate the rotational temperature (Tr) of the gliding arc discharge whereas the NO A–X (1, 0) and (0, 1) bands were used to determine its vibrational temperature (Tv). The instantaneous reduced electric field strength E/N was obtained by simultaneously measuring the instantaneous length of the plasma column, the discharge voltage and the translational temperature, from which the electron temperature (Te) of the gliding arc discharge was estimated. The uncertainties of the translational, rotational, vibrational and electron temperatures were analyzed. The relations of these four different temperatures (Te>Tv>Tr >Tt) suggest a high-degree non-equilibrium state of the gliding arc discharge

Measurements of 3D slip velocities and plasma column lengths of a gliding arc discharge

A non-thermal gliding arc discharge was generated at atmospheric pressure in an air flow. The dynamics of the plasma column and tracer particles were recorded using two synchronized highspeed cameras. Whereas the data analysis for such systems has previously been performed in 2D (analyzing the single camera image), we provide here a 3D data analysis that includes 3D reconstructions of the plasma column and 3D particle tracking velocimetry based on discrete tomography methods. The 3D analysis, in particular, the determination of the 3D slip velocity between the plasma column and the gas flow, gives more realistic insight into the convection cooling process. Additionally, with the determination of the 3D slip velocity and the 3D length of the plasma column, we give more accurate estimates for the drag force, the electric field strength, the power per unit length, and the radius of the conducting zone of the plasma column. (C) 2015 AIP Publishing LLC

Evaluating Large Language Models on a Highly-specialized Topic, Radiation Oncology Physics

We present the first study to investigate Large Language Models (LLMs) in answering radiation oncology physics questions. Because popular exams like AP Physics, LSAT, and GRE have large test-taker populations and ample test preparation resources in circulation, they may not allow for accurately assessing the true potential of LLMs. This paper proposes evaluating LLMs on a highly-specialized topic, radiation oncology physics, which may be more pertinent to scientific and medical communities in addition to being a valuable benchmark of LLMs. We developed an exam consisting of 100 radiation oncology physics questions based on our expertise at Mayo Clinic. Four LLMs, ChatGPT (GPT-3.5), ChatGPT (GPT-4), Bard (LaMDA), and BLOOMZ, were evaluated against medical physicists and non-experts. ChatGPT (GPT-4) outperformed all other LLMs as well as medical physicists, on average. The performance of ChatGPT (GPT-4) was further improved when prompted to explain first, then answer. ChatGPT (GPT-3.5 and GPT-4) showed a high level of consistency in its answer choices across a number of trials, whether correct or incorrect, a characteristic that was not observed in the human test groups. In evaluating ChatGPTs (GPT-4) deductive reasoning ability using a novel approach (substituting the correct answer with "None of the above choices is the correct answer."), ChatGPT (GPT-4) demonstrated surprising accuracy, suggesting the potential presence of an emergent ability. Finally, although ChatGPT (GPT-4) performed well overall, its intrinsic properties did not allow for further improvement when scoring based on a majority vote across trials. In contrast, a team of medical physicists were able to greatly outperform ChatGPT (GPT-4) using a majority vote. This study suggests a great potential for LLMs to work alongside radiation oncology experts as highly knowledgeable assistants