Solvent-Mediated Hetero/Homo-Phase Crystallization of Copper Nanoclusters and Superatomic Kernel-Related NIR Phosphorescence.

Atomically precise superatomic copper nanoclusters (Cu NCs) have been the subject of immense interest for their intriguing structures and diverse properties; nonetheless, the variable oxidation state of copper ions and complex solvation effects in wet synthesis systems pose significant challenges for comprehending their synthesis and crystallization mechanism. Herein, we present a solvent-mediated approach for the synthesis of two Cu NCs, namely, superatomic Cu26 and pure-Cu(I) Cu16. They initially formed as a hetero-phase and then separated as a homo-phase via modulating binary solvent composition. In situ UV/vis absorption and electrospray ionization mass spectra revealed that the solvent-mediated assembly was determined to be the underlying mechanism of hetero/homo-phase crystallization. Cu26 is a 2-electron superatom with a kernel-shell structure that includes a [Cu20Se12]4- shell and [Cu6]4+ kernel, containing two 1S jellium electrons. Conversely, Cu16 is a pure-Cu(I) Cu/Se nanocluster that features a [Cu16Se6]4+ core protected by extra dimercaptomaleonitrile ligands. Remarkably, Cu26 exhibits unique near-infrared phosphorescence (NIR PH) at 933 nm due to the presence of a superatomic kernel-related charge transfer state (3MM(Cu)CT). Overall, this work not only showcases the hetero/homo-phase crystallization of Cu NCs driven by a solvent-mediated assembly mechanism but also enables the rare occurrence of NIR PH within the 2-electron copper superatom family.

Assessment of spatiotemporal variability and trend analysis of reference crop evapotranspiration for the southern region of Peninsular India.

Accurate estimation of reference evapotranspiration (ET0) is an essential requirement for water resource management and scheduling agricultural activities. Several empirical methods have been employed in estimating ET0 across diverse climate regimes over the past decades. In this study, the Python implementation for estimation of daily and monthly ET0 values of representative stations of ten agro-climatic zones of Karnataka from 1979 to 2014 using the standard FAO Penman-Monteith method was carried out. The assessment of temporal and spatial variability of monthly ET0 values across the various agro-climatic zones done by the various statistical measures revealed that the variation in spatial ET0 values was higher than temporal variation, indicating major difference in ET0 values was with respect to the stations rather than years under study. The nonparametric Mann-Kendall test conducted at 1% significance level on the annual ET0 values revealed a statistically significant increasing trend for all the ten stations during the study period. The trend test conducted on the climate variables like mean air temperature, wind speed, relative humidity, and solar radiation signifies their influence on the annual ET0 values. The magnitude changes in the trends detected by the Theil Sen's slope indicated that increasing values of mean temperature, solar radiation, and decreasing values of relative humidity predominantly contributed to the annual upward trend in ET0 values for the 10 stations. A trivial impact of wind speed on annual ET0 values was observed for the stations. Kalburgi and Udupi stations exhibited a positive ET0 trend with the highest and lowest annual values among ten stations.

Modulation effects of S vacancy and Mo edge on the adsorption and dissociation behaviors of toxic gas (H2S, SO2) molecules on the MoS2 monolayer.

This study focuses on the modulation effects of S vacancy and Mo edges on the adsorption and dissociation behaviors of toxic gases (H2S and SO2) on MoS2 by first-principles calculations. Both molecules are found to chemisorb at the S vacancy (SV) and pristine Mo edge and physisorb at the Mo edge with a 50% sulfur coverage (Mo-50 edge). Among them, SO2 has larger adsorption energy than H2S on both S vacancy and pristine Mo edge, which is related to a more electronegative O than S atom and electronically rich for the pristine Mo edge. The defective states of MoS2 induced by SV can be removed by forming Mo-S, Mo-O and Mo-H bonds upon the adsorption of SO2 and the dissociation of H2S, which is applicable in designing MoS2 based nano-electronics devices in the future. The dissociations of H2S and SO2 on pristine Mo edges are found to be more favorable than those on S vacancies due to the catalytically active Mo4+ states at edge sites. H2S is found to dissociate on the Mo-50 edge more easily than SO2. The adsorptions and dissociations of toxic gas on MoS2 with SV or Mo edges suggest MoS2 is a potential candidate in detecting and removal of toxic gases.

Antimicrobial resistance and the post antibiotic era: better late than never effort.

Introduction: Antimicrobial resistance (AMR) is a multi-layered problem with a calamitous impact on humans, livestock, the environment, and the biosphere. Initiatives and action plan to preclude AMR remain poorly implemented in India.Area covered: This review highlights essential factors contributing to AMR, epidemiology of the resistant bacteria, current treatment options, economic impact, and regulatory efforts initiated by the Indian government to tackle AMR.Expert opinion: Health-care professionals, hospitals, and the general public must understand and cooperatively implement the 'One Health approach,' which entails judicious use of antibiotics in humans, animals, and the environment. Neglecting the AMR problem predicts the expansion of the 'Post-antibiotic era' characterized by drying antibiotic discovery pipelines, overuse of 'Watch' and 'Reserve' groups, coupled with underuse of 'Access' antibiotics, increased daily defined doses, increased healthcare cost, rise in morbidity, mortality, and environmental degradation. The Indian case study elucidates a looming international crisis that demands global attention and commitment for envisaging and implementing locally relevant solutions.

Estimation of Aminophylline effectiveness at Neonatal Intensive Care Unit (NICU) using Artificial Intelligence

@#Introduction: The estimation of drug competence using Artificial Intelligence is presented in various literature for the adult population, but it is still new for drug dosage optimization in neonates. Aminophylline, a methylxanthine is administered as central nervous system stimulant for reducing Apnea episodes in neonates. Methods: The paper describes comparative evaluation of Support Vector Machine (SVM), K Nearest Neighbour (KNN), Decision Tree (DT) and Artificial Neural Network (ANN) for predicting drug effectiveness of Aminophylline. The models were evaluated using 100 Aminophylline cases based on various metrics such as sensitivity, specificity, and accuracy. The data used for the analysis was collected from the population pharmacokinetic study conducted at Kasturba Medical College, Neonatal Intensive Care Unit (NICU). Results: The evaluation result seemed to favour Multi-Layer Perceptron (MLP) with accuracy of 0.92 Area Under the Curve (AUC) followed by 0.85 (AUC) for Support Vector Machine (SVM). The input parameters in particular maternal, pharmacokinetics, demographic and physiological that were identified in literature as predictor variable played an important role in estimating effectiveness of Aminophylline regimens. Conclusion: Artificial Intelligence approach was potentially helpful in analysing drug dosage of Aminophylline and its effectiveness in diagnosing neonatal Apnea.