HotMobile 2008: Postconference Report

HotMobile 2008 presented a two-day program on mobile computing systems and applications. The authors focuses on the sessions on sensors, modularity, wireless, security, systems, and screens. The mobile device is the most amazing invention in history and that it has had the largest impact on human kind. Because mobile phones combine mobile devices with ongoing developments in software and communication technologies, they have the potential to change the way people think and act

A Study on Ajuga bracteosa wall ex. Benth for analgesic activity

Ethnopharmacological relevance: Ajuga bracteosa wall ex. Benth (Labiatae) is traditionally used medicine in the treatment of malaria and gout. The plant is substitute of cinchona. Its allied species Ajuga Parviflora is also found sporadically. In Ayurvedic prepration the aqueous extract of the leaves part showed diuretic activity. Aim of the study: The present study was carried out to investigate analgesic activity of Ajuga bracteosa wall ex. Benth aerial part extracts. Materials and methods: A. bracteosa, a widespread medicinal plant traditionally used in the disease, was collected from Hamirpur district of Himachal Pradesh. Aerial part was extracted with petroleum ether, chloroform, methanol, ethanol and water. Analgesic activity of these extracts was assessed in swiss albino mice with acetic acid-induced writhing test and tail immersion test. Results: At the doses used (200 and 400 mg/kg, i.p.) chloroform and water extracts showed significant and dose-dependent analgesic effects.\ud Conclusion: Our results indicate that extracts Ajuga bracteosa wall ex. Benth obtained from demonstrate an analgesic effect probably mediated by opioid receptors.\u

Improving the process performance of magnetic abrasive finishing of SS304 material using multi-objective artificial bee colony algorithm

Magnetic abrasive finishing is a super finishing process in which the magnetic field is applied in the finishing area and the material is removed from the workpiece by magnetic abrasive particles in the form of microchips. The performance of this process is decided by its two important quality characteristics, material removal rate and surface roughness. Significant process variables affecting these two characteristics are rotational speed of tool, working gap, weight of abrasive, and feed rate. However, material removal rate and surface roughness being conflicting in nature, a compromise has to be made between these two objective to improve the overall performance of the process. Hence, a multi-objective optimization using an artificial bee colony algorithm coupled with response surface methodology for mathematical modeling is attempted in this work. The set of Pareto-optimal solutions obtained by multi-objective optimization offers a ready reference to process planners to decide appropriate process parameters for a particular scenario

Quantitatively evaluating greenhouse gas leakage from CO2 enhanced oil recovery fields

Greenhouse gas (mainly CO2 and CH4) leakage from abandoned wells in CO2 enhanced oil recovery sites is a long-standing environmental concern and health hazard. Although multiple CO2 capture, utilization, and storage programs, e.g., CarbonSAFE and Regional Carbon Storage Partnerships, have been developed in the U.S. to reach the net-zero emission target by 2050, one cannot neglect the significant amount of CO2 and CH4 leakage from abandoned wells. This study will investigate the potential of CO2 and oil components leakages from the abandoned wellbore and develop the first-ever quantitative approach to evaluating CO2 and oil component leakage from a CO2 enhanced oil recovery field. Results show that in addition to a large amount of CO2 leakage, a significant amount of light and intermediate oil components leaked through the wellbore. In contrast, a minimal amount of heavy oil component leaked. Oil components’ leakage is mainly through the gas phase rather than the liquid phase. CO2 leakage is positively correlated to reservoir depth, wellbore pressure, and permeability through sensitivity analysis. In contrast, it is negatively related to net-to-gross ratio, residual oil saturation, and mole fraction of CH4. On the other hand, oil component leakages are positively correlated to all uncertain parameters, except the net-to-gross ratio. Lastly, the reduced-order models generated using the machine learning technique have a relatively high fidelity.Cited as: Chen, B., Mehana, M. Z., Pawar, R. J. Quantitatively evaluating greenhouse gas leakage from CO2 enhanced oil recovery fields. Advances in Geo-Energy Research, 2023, 7(1): 20-27. https://doi.org/10.46690/ager.2023.01.0