Simultaneous adsorption and biodegradation of reactive dyes using jatropha deoiled cakes

© BEIESP. Endemic pollution problems due to discharge of wastewaters are affecting all the aspects of human life. The poor quality effluents coming from industries is destroying the fragile ecosystem, leading to various apprehensions amongst researchers and scientific communities. Treatment of wastewaters have become an urgent need of the society, which cannot be ignored. Incineration, absorption on solid matrices and biological treatment are some of the effluent treatment methods available. These methods, however, have their own disadvantages. This work explores the application of jatropha deoiled cakes on the concurrent adsorption and biological degradation of reactive dyes. Reactive blue, reactive yellow, reactive red were used for the experiments. The combined experiments were tested for effect of glucose concentrations as well as initial concentrations. Glucose concentrations of 1 g/l, 2 g/l and 3 g/l were taken. All the dyes were varied from 100 ppm to 600 ppm. It was observed that combined degradation yielded higher degradation compared to biological degradation alone. The degradation rate varied with the variation of glucose concentration and it also varied with the initial concentration

Comment on: "Estimating the Hartree-Fock limit from finite basis set calculations" [Jensen F (2005) Theor Chem Acc 113:267]

We demonstrate that a minor modification of the extrapolation proposed by Jensen [(2005): Theor Chem Acc 113:267] yields very reliable estimates of the Hartree-Fock limit in conjunction with correlation consistent basis sets. Specifically, a two-point extrapolation of the form $E_{HF,L}=E_{HF,\infty}+A(L+1)\exp(-9\sqrt{L})$ yields HF limits $E_{HF,\infty}$ with an RMS error of 0.1 millihartree using aug-cc-pVQZ and aug-cc-pV5Z basis sets, and of 0.01 millihartree using aug-cc-pV5Z and aug-cc-pV6Z basis sets.Comment: Theoretical Chemistry Accounts, in pres

Global hybrids from the semiclassical atom theory satisfying the local density linear response

We propose global hybrid approximations of the exchange-correlation (XC) energy functional which reproduce well the modified fourth-order gradient expansion of the exchange energy in the semiclassical limit of many-electron neutral atoms and recover the full local density approximation (LDA) linear response. These XC functionals represent the hybrid versions of the APBE functional [Phys. Rev. Lett. 106, 186406, (2011)] yet employing an additional correlation functional which uses the localization concept of the correlation energy density to improve the compatibility with the Hartree-Fock exchange as well as the coupling-constant-resolved XC potential energy. Broad energetical and structural testings, including thermochemistry and geometry, transition metal complexes, non-covalent interactions, gold clusters and small gold-molecule interfaces, as well as an analysis of the hybrid parameters, show that our construction is quite robust. In particular, our testing shows that the resulting hybrid, including 20\% of Hartree-Fock exchange and named hAPBE, performs remarkably well for a broad palette of systems and properties, being generally better than popular hybrids (PBE0 and B3LYP). Semi-empirical dispersion corrections are also provided.Comment: 12 pages, 4 figure

Inferring stabilizing mutations from protein phylogenies : application to influenza hemagglutinin

One selection pressure shaping sequence evolution is the requirement that a protein fold with sufficient stability to perform its biological functions. We present a conceptual framework that explains how this requirement causes the probability that a particular amino acid mutation is fixed during evolution to depend on its effect on protein stability. We mathematically formalize this framework to develop a Bayesian approach for inferring the stability effects of individual mutations from homologous protein sequences of known phylogeny. This approach is able to predict published experimentally measured mutational stability effects (ΔΔG values) with an accuracy that exceeds both a state-of-the-art physicochemical modeling program and the sequence-based consensus approach. As a further test, we use our phylogenetic inference approach to predict stabilizing mutations to influenza hemagglutinin. We introduce these mutations into a temperature-sensitive influenza virus with a defect in its hemagglutinin gene and experimentally demonstrate that some of the mutations allow the virus to grow at higher temperatures. Our work therefore describes a powerful new approach for predicting stabilizing mutations that can be successfully applied even to large, complex proteins such as hemagglutinin. This approach also makes a mathematical link between phylogenetics and experimentally measurable protein properties, potentially paving the way for more accurate analyses of molecular evolution

A Review of Corrosion and Protection of Steel in Concrete

Corrosion of reinforcement is one of the major durability challenges which leads to a reduction in the design life of reinforced concrete. Due to an increasing demand for longer service lives of infrastructure (typically 100-120 years) and the high cost involved in building and maintaining it, the repair of concrete structures has become extremely important. This paper discusses mechanism of corrosion in reinforced concrete and its thermodynamic and kinetic behaviour. It also presents and compares different corrosion prevention and protection techniques available and recommended by BS 1504-9:2008; including the use of corrosion inhibitors, alternative reinforcement, steel and concrete coating and electrochemical techniques. It is concluded that the electrochemical techniques are more effective than conventional methods

Evaluating urban traffic dynamics: a study of mobility in Vellore city

Urban mobility is a significantly increasing challenge in fast-growing cities, where efficient traffic management is crucial to ensure smooth movement and enhance the overall quality of life. The research consists of an in-depth analysis of urban mobility for the city under study using a data-driven approach to address day-to-day traffic challenges. It includes a fusion of traffic flow analysis and vehicle count data with weekend and weekday indicators to develop predictive models. The study evaluates the city’s traffic data by examining peak and off-peak periods. We focus on simple contextual variables – specifically, temporal indicators – our models provide an efficient framework for traffic forecasting in complex environments. The findings underscore that meaningful traffic forecasts can be used to provide practical and scalable solutions for urban planners and administrators to optimize traffic management in rapidly expanding cities

AI-IoT-graph synergy for smart waste management: a scalable framework for predictive, resilient, and sustainable urban systems

Effective waste management is essential for smart cities, but fixed collection schedules frequently result in missed pickups, overflow events, and inefficient fuel consumption. This study introduces a framework that integrates Artificial Intelligence (AI), Internet of Things (IoT) sensors, and graph-theoretic optimization. A simulated dataset of 500 bins across five zones was used to train an XGBoost classifier for overflow prediction, combined with spatial risk mapping and routing optimization on a weighted bin network. The AI model achieved high predictive accuracy (94.1%) and recall (95.8%), ensuring reliable identification of overflow-prone bins. Compared to a static collection model, the smart system reduced overflow events by 50%, missed pickups by 72.7%, and fuel usage by 15.5%, while improving bin utilization efficiency by 35.5%. These findings demonstrate that integrating AI, IoT, and graph-theoretic methods can significantly enhance operational efficiency and environmental sustainability in urban waste logistics. The framework provides a scalable solution that adheres to Industry 4.0 principles and serves as a foundation for future smart city infrastructures. The system’s modular architecture allows seamless integration with existing municipal platforms, enabling in real-time responsiveness and adaptive service delivery. By bridging operational decision-making with simulation-driven insights, the framework sets a precedent for data-driven governance in urban infrastructure

Antinociceptive effect of methanolic extract of Murraya koenigii leaves in swiss albino mice

Background: The objective of the study was to evaluate anti-nociceptive effect of methanolic extract of Murraya koenigii leaves on thermal and mechanical pain in swiss albino mice.Methods: Thirty adult male swiss albino mice weighing 25-30 grams were selected and allocated in to five groups. Each group consists of six animals. The control group received vehicle (10 ml/kg), standard group received morphine (10 mg/kg) and test groups received dried methanolic extract of Murraya koenigii leaves (100 mg/kg, 200 mg/kg, 400 mg/kg per oral respectively) 1 hour before placing the animal over the hot plate at temperature of 55⁰C . A cut off period of 10 sec was observed to avoid damage of the paw. The response in the form of withdrawal of paws or licking of the paws. The delay in the reaction time denotes analgesic activity. The latency was recorded before and after 15, 30, 60, 120 minutes administration of drug. After washout period of 1 month the same group of animals were utilized to evaluate the analgesic effect by tail clip method for better comparison.Results: All the doses of Murraya koenigii leaves significantly delayed reaction time in hot plate method and tail clip method. The results were comparable to that produced by standard drug morphine.Conclusions: Murraya koenigii leaves has analgesic activity which was comparable to morphine