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Polyethylene terephthalate (PET) is one of the highly produced synthetic polymers worldwide and had acquired attention due to its impact resistance, high clarity, and light weight. PET has become the first choice in making disposable bottles, leading to massive scales of production resulting in very high utilization across various facets of our daily life. Unfortunately, PET accumulates as waste and is highly resistant to biodegradation, thus presenting a serious threat to the ecosystem. Degradation of PET by enzymatic hydrolysis is a promising strategy to depolymerize the PET into its monomers. In recent studies, a plastic-degrading enzyme known as PETase ( Is PETase) from the Ideonella sakaiensis has been identified to hydrolyze PET. The wild-type enzyme from Ideonella sp., has been engineered to improve the catalytic activity. While the Is PETase and its variants have been the subject of extensive structural and biochemical studies, the corresponding computational studies to support the improved activity of the mutant enzyme is not fully understood. In this work, we employed all-atom classical molecular dynamics simulations of the wild-type and double mutant Is PETase enzymes to investigate the underlying reason for the improved catalytic activity in the double mutant by means of structure-dynamics-function relationship. Our results show that the engineered mutations reshape the active site structure, volume, and dynamics of the protein loops which is crucial for substrate binding. We also demonstrate that addition of aromatic and hydrogen bond-forming residues near catalytic site improves binding affinity. This work will enable the rational design of mutants for enhanced PET degrading activity.Communicated by Ramaswamy H. Sarma.

In this research study, we developed a new rapid and simple HPLC quantitative approach for comprehensively measuring related substance impurities (LNGN N formyl; LNGN acetamide; LNGN N Boc; LNGN amino) in Linagliptin. The related substance impurities were studied by PDA detection at 225 nm after being separated on the Kromasil C18 column stationary phase. The isocratic mode elution and a flow velocity of 1.0 mL/min were performed with the 0.1% phosphoric acid having pH 2.5 and acetonitrile. The proposed approach was appropriately verified in agreement with the "International Conference on Harmonization". Linearity was demonstrated for values ranging from LOQ quantity ppm to 150% quantity ppm, with variance coefficients 0.99. The precision varied from 0.128 to 0.969% RSD and accuracy varied from 99.13% to 101.76% for four related substance impurities. The proposed approach was appropriately implemented in the quality control analysis of the linagliptin API. Stress testing on the linagliptin API is also part of this investigation. One degradant with a 10.273 min Rt was found during oxidative stress testing on linagliptin. Using LC-MS this peak was discovered to be an adduct. [ABSTRACT FROM AUTHOR]

Toward achieving control over the kerfing through macro abrasive waterjet submerged milling, there is a need (i) to understand the influence of the water column height on the kerf quality and (ii) to develop a model for the prediction of the kerf characteristics. This study performs detailed experimentation to assess the kerf quality enhancement in submerged milling relative to the in-air milling on Al-6061 alloy. From the modeling perspective, there are very limited efforts in developing a comprehensive model that includes both the jet flow dynamics and material removal models-this is the missing link. Toward this, a comprehensive model is proposed and validated for the prediction of kerf in in-air and submerged conditions by considering (i) jet dynamics and (ii) jet-material interaction. From the experimental results, it is observed that by adopting the submerged milling, the damaged region, top kerf width and edge radius got reduced by 20.3%, 13.53%, and 22.7%, respectively. However, this enhancement in the kerf quality is associated with a reduction in the centerline erosion depth (hmax) by 12.33% and a material removal rate by 24.52%. The material removal mechanism is more uniform and directed in the submerged milling, whereas in-air is random. The proposed model predicted the kerf cross-sectional profile in submerged milling and in-air with a mean absolute error of 60 µm and 57 µm, squared Pearson correlation coefficient of 0.97 and 0.99, and the hmax with a maximum error of 1.3% and 1.4%. [ABSTRACT FROM AUTHOR]

Underwater sensor networks (USNs) play a key role for applications such as underwater defense, underwater imaging, internet of underwater things, underwater navigation and so on. In USNs, acoustic waves have been referred over the radio frequency (RF) waves or optical waves to communicate between sensor nodes, buoys, and autonomous underwater vehicles (AUVs). The acoustic waves in underwater acoustic sensor networks (UASNs) have a much lower bandwidth of up to a few kHz, resulting in a lower achievable data rate. Generally, the sensor nodes have been deployed on the beds of the oceans. So, it is very difficult to recharge or replace them, once the batteries of the sensor nodes are drain off. Hence, achievable data rate and energy efficiency (EE) has to be improved simultaneously in UASNs. In this paper, we have presented different non-orthogonal multiple access techniques to improve data rate and various energy harvesting techniques proposed for UASNs to improve the EE. [ABSTRACT FROM AUTHOR]