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We present the results from deep 21 cm H i mapping of two nearby Blue Compact Dwarf Galaxies (BCDGs), W1016+3754 and W2326+0608, using the Giant Metrewave Radio Telescope (GMRT). These BCDGs are bright in mid-infrared data and undergoing active star formation. With the GMRT observations, we investigate the role of cold neutral gas as the fuel resource of the current intensive star formation activity. Star formation in these galaxies is likely to be due to the infall of H i gas triggered by gravitational perturbation from nearby galaxies. The BCDG W2326+0608 and nearby galaxy SDSS J232603.86+060835.8 share a common H i envelope. We find star formation takes place in the high H i column density gas (≳1021 cm−2) regions for both BCDGs. The recent starburst and infall of metal-free gas have kept the metallicity low for the BCDG W1016+3754. The metallicity for W2326+0608 is higher, possibly due to tidal interaction with the nearby galaxy SDSS J232603.86+060835.8.

 

De Novo design of molecules with targeted properties represents a new frontier in molecule development. Despite enormous progress, two main challenges remain, i.e., (i) generation of novel molecules with targeted and quantifiable properties; (ii) generated molecules having property values beyond the range in the training dataset. To tackle these challenges, we propose a novel reinforced regressional and conditional generative adversarial network (RRCGAN) to generate chemically valid, drug-like molecules with targeted heat capacity (Cv) values as a proof-of-concept study. As validated by DFT, ~80% of the generated samples have a relative error (RE) of < 20% of the targeted Cv values. To bias the generation of molecules with the Cv values beyond the range of the original training molecules, transfer learning was applied to iteratively retrain the RRCGAN model. After only two iterations of transfer learning, the mean Cv of the generated molecules increases to 44.0 cal/(mol·K) from the mean value of 31.6 cal/(mol·K) shown in the initial training dataset. This demonstrated computation methodology paves a new avenue to discovering drug-like molecules with biased properties, which can be straightforwardly repurposed for optimizing individual or multi-objective properties of various matters. 

The unstretched laminar flame speed (LFS) plays a key role in engine models and predictions of flame propagation. It is also an essential parameter in the study of turbulent combustion and can be directly used in many turbulent combustion models. Therefore, it is important to predict the laminar flame speed accurately and efficiently. Two improved correlations for the unstretched laminar flame speed, namely improved power law and improved Arrhenius form correlations, are proposed for iso-octane/air mixtures in this study, using simulated results for typical operating conditions for spark-ignition engines: unburned temperatures of 300-950 K, pressures of 1-120 bar, and equivalence ratios of 0.6-1.5. The original data points used to develop the new correlations were obtained using the detailed combustion kinetics for iso-octane from Lawrence Livermore National Laboratory (LLNL). The three coefficients in the improved power law correlation were determined using a methodology different from previous approaches. The improved Arrhenius form correlation employs a function of unburned gas temperature to replace the flame temperature, making the expression briefer and making the coefficients easier to calculate. The improved Arrhenius method is able to predict the trends and the values of laminar flame speed with improved accuracy over a larger range of operating conditions. The improved power law method also works well but for a relatively narrow range of predictions. The improved Arrhenius method is recommended, considering its overall fitting error was only half of that using the improved power law correlation and it was closer to the experimental measurements. Even though ϕm, the equivalence ratio at which the laminar flame speed reaches its maximum, is not monotonic with pressure, this dependence is still included, since it produces least-rich best torque (LBT). The comparisons between the improved correlations in this study and the experimental measurements and the other correlations from various researchers are shown as well. 

Two improved correlations for the laminar flame speed, an improved power law correlation and an improved Arrhenius form correlation, are proposed for iso-octane in this study based on CONVERGE one-dimensional simulation results using the LLNL reaction mechanism. The typical working conditions for a spark-ignition engine, 300-950 K for unburned temperature, 1-120 bar for pressure, and 0.6-1.5 for equivalence ratio, were chosen to generate the results. Each of the two improved correlations has three parameters to be determined and these parameters are all shown as simple functions of equivalence ratio. The predicted unstretched laminar flame speeds using these two correlations were compared with the experimental measurements and with correlations from other researchers. In summary, both improved correlations, using simple and workable expressions, were able to predict the trends and the values of the unstretched laminar flame speed with improved accuracy. The improved Arrhenius form was more accurate and presented good predictions over a large range of operating conditions, and therefore is recommended for practical calculations and predictions. 

Quaternary ammonium compounds (QACs), a large class of chemicals that includes high production volume substances, have been used for decades as antimicrobials, preservatives, and antistatic agents, and for other functions in cleaning, disinfecting, personal care products, and durable consumer goods. QAC use has accelerated in response to the COVID-19 pandemic and the banning of 19 antimicrobials from several personal care products by the US Food and Drug Administration in 2016. Studies conducted before and after the onset of the pandemic indicate increased human exposure to QACs. Environmental releases of these chemicals have also increased. Emerging information on adverse environmental and human health impacts of QACs is motivating a reconsideration of the risks and benefits across the life cycle of their production, use, and disposal. This paper presents a critical review of the literature and scientific perspective developed by a multidisciplinary, multi-institutional team of authors from academia, governmental, and nonprofit organizations. The review evaluates currently available information on the ecological and human health profile of QACs and identifies multiple areas of potential concern. Adverse ecological effects include acute and chronic toxicity to susceptible aquatic organisms, with concentrations of some QACs approaching levels of concern. Suspected or known adverse health outcomes include dermal and respiratory effects, developmental and reproductive toxicity, disruption of metabolic function such as lipid homeostasis, and impairment of mitochondrial function. QACs’ role in antimicrobial resistance has also been demonstrated. In the US regulatory system, how a QAC is managed depends on how it is used, for example, in pesticides or personal care products. This can result in the same QACs receiving different degrees of scrutiny depending on the use and the agency regulating it. Further, the EPA’s current method of grouping QACs based on structure, first proposed in 1988, is insufficient to address the wide range of QAC chemistries, potential toxicities, and exposure scenarios. Consequently, exposures to common mixtures of QACs and from multiple sources remain largely unassessed. Some restrictions on the use of QACs have been implemented in the US and elsewhere, primarily focused on personal care products. Assessing the risks posed by QACs is hampered by their vast structural diversity and a lack of quantitative data on exposure and toxicity for the majority of these compounds. This review identifies important data gaps and provides research and policy recommendations for preserving the utility of QAC chemistries while also seeking to limit adverse environmental and human health effects.