The Effect of Near-Spark-Plug Flow Field on Spark Discharge Characteristics

Advanced spark ignition (SI) engines can operate under lean conditions in order to improve the efficiency and reduce the emissions. Under extensive lean conditions, the ignition and complete combustion of the charge mixture is a challenge, because of the reduced cylinder charge reactivity. The enhancement of the in-cylinder global motion and local turbulence is an effective way to increase the flame velocity, and consequently shorten the combustion duration. The role of air motion in improving air-fuel mixing and combustion has been researched extensively. However, during the ignition process, the excessive charge motion can hinder the spark discharge, the resulting flame kernel formation, and propagation. Therefore, a combined empirical and simulation study is undertaken to elucidate the flow field around the spark gap, and its effect on the spark discharge. The flow field generated by a steady flow of air across the spark gap of a conventional J-type spark plug is studied under ambient conditions. Optical particle image velocimetry (PIV) measurements and computational fluid dynamics (CFD) simulations are performed alongside the high-speed direct imaging. Voltage and current waveforms of the spark channel have been measured, in order to correlate the spark behavior to the local flow velocity. The flow field near the spark gap in an SI engine under motoring conditions is simulated. The results are compared to the empirical current and voltage measurements taken during engine operation. The results show that the turbulence is generated in the wake of the spark plug and flow velocity in the spark gap is higher than the free stream velocity. The optical and electrical measurements show the spark stretching and restrikes increase, and the discharge duration decreases with an increase in flow velocity. Similar behavior is observed during engine operation as well

Measuring the meltdown: drivers of global amphibian extinction and decline

Journal ArticleHabitat loss, climate change, over-exploitation, disease and other factors have been hypothesised in the global decline of amphibian biodiversity. However, the relative importance of and synergies among different drivers are still poorly understood. We present the largest global analysis of roughly 45% of known amphibians (2,583 species) to quantify the influences of life history, climate, human density and habitat loss on declines and extinction risk. Multi-model Bayesian inference reveals that large amphibian species with small geographic range and pronounced seasonality in temperature and precipitation are most likely to be Red-Listed by IUCN. Elevated habitat loss and human densities are also correlated with high threat risk. Range size, habitat loss and more extreme seasonality in precipitation contributed to decline risk in the 2,454 species that declined between 1980 and 2004, compared to species that were stable (n = 1,545) or had increased (n = 28). These empirical results show that amphibian species with restricted ranges should be urgently targeted for conservation

Impact of Vermicompost on Growth, Yield and Quality of Tomato Plant (Lycopersicum Esculentum)

The main objective of the study was to prepare vermicompost from the waste and to determine its effect on the qualitative and quantitative yield of tomato plant. The treatment groups consisted of VC (15, 30, 45 and control). The parameters like pH 7.2, Electrical Conductivity (10.70mmhos/cm), Total Hardness (360mg/l), Calcium (160mg/l) and Magnesium (200mg/l) were determined. The present results show that vermicompost treatment has significant growth impact on plant height, number of leaves, fruits, flowers and stem diameter as compared to control

Evaluation of air pollution tolerance index of certain plant species grown alongside Parwanoo to Solan National Highway-22 in Himachal Pradesh, India

The study examined the Air Pollution Tolerance Index (APTI) of selected plant species growing along national highway-22 from Parwanoo to Solan, falling in Solan district of Himachal Pradesh, India. Four species namely Grewiaoptiva, Toonaciliata, Melia azedarach and Woodfordia floribunda of uniform size, age, spread and common in occurrence on both sides of the highway are selected. Leaf samples were collected from selected spe-cies and used to estimate four physiological and biochemical parameters, namely; leaf relative water content (RWC), ascorbic acid content (AA), total leaf chlorophyll (TChl) and leaf extract pH were used to compute the APTI values. The trend of APTI recorded for various species was Melia azedarach (18.37) >Grewiaoptiva(8.77) >Woodfordia floribunda (7.43) >Toonaciliata(6.82). The APTI also varied with seasons of the year. The highest APTI was noticed in rainy followed by winter and summer season. The study indicated Melia azedarach as most tolerant and Toonaciliataas most sensitive species to air pollution

BhairPred: prediction of β-hairpins in a protein from multiple alignment information using ANN and SVM techniques

This paper describes a method for predicting a supersecondary structural motif, β-hairpins, in a protein sequence. The method was trained and tested on a set of 5102 hairpins and 5131 non-hairpins, obtained from a non-redundant dataset of 2880 proteins using the DSSP and PROMOTIF programs. Two machine-learning techniques, an artificial neural network (ANN) and a support vector machine (SVM), were used to predict β-hairpins. An accuracy of 65.5% was achieved using ANN when an amino acid sequence was used as the input. The accuracy improved from 65.5 to 69.1% when evolutionary information (PSI-BLAST profile), observed secondary structure and surface accessibility were used as the inputs. The accuracy of the method further improved from 69.1 to 79.2% when the SVM was used for classification instead of the ANN. The performances of the methods developed were assessed in a test case, where predicted secondary structure and surface accessibility were used instead of the observed structure. The highest accuracy achieved by the SVM based method in the test case was 77.9%. A maximum accuracy of 71.1% with Matthew's correlation coefficient of 0.41 in the test case was obtained on a dataset previously used by X. Cruz, E. G. Hutchinson, A. Shephard and J. M. Thornton (2002) Proc. Natl Acad. Sci. USA, 99, 11157–11162. The performance of the method was also evaluated on proteins used in the ‘6th community-wide experiment on the critical assessment of techniques for protein structure prediction (CASP6)’. Based on the algorithm described, a web server, BhairPred (), has been developed, which can be used to predict β-hairpins in a protein using the SVM approach

Evaluating the Relative Environmental Impact of Countries

Environmental protection is critical to maintain ecosystem services essential for human well-being. It is important to be able to rank countries by their environmental impact so that poor performers as well as policy ‘models’ can be identified. We provide novel metrics of country-specific environmental impact ranks – one proportional to total resource availability per country and an absolute (total) measure of impact – that explicitly avoid incorporating confounding human health or economic indicators. Our rankings are based on natural forest loss, habitat conversion, marine captures, fertilizer use, water pollution, carbon emissions and species threat, although many other variables were excluded due to a lack of country-specific data. Of 228 countries considered, 179 (proportional) and 171 (absolute) had sufficient data for correlations. The proportional index ranked Singapore, Korea, Qatar, Kuwait, Japan, Thailand, Bahrain, Malaysia, Philippines and Netherlands as having the highest proportional environmental impact, whereas Brazil, USA, China, Indonesia, Japan, Mexico, India, Russia, Australia and Peru had the highest absolute impact (i.e., total resource use, emissions and species threatened). Proportional and absolute environmental impact ranks were correlated, with mainly Asian countries having both high proportional and absolute impact. Despite weak concordance among the drivers of environmental impact, countries often perform poorly for different reasons. We found no evidence to support the environmental Kuznets curve hypothesis of a non-linear relationship between impact and per capita wealth, although there was a weak reduction in environmental impact as per capita wealth increases. Using structural equation models to account for cross-correlation, we found that increasing wealth was the most important driver of environmental impact. Our results show that the global community not only has to encourage better environmental performance in less-developed countries, especially those in Asia, there is also a requirement to focus on the development of environmentally friendly practices in wealthier countries

An in-depth study of drugs prescribing pattern in the Surgery Department of a Tertiary Care Teaching Institute in Northern India

Background: In surgical patients, a number of drugs are prescribed to prevent post-operative infections and to relieve pain. Therefore, prescription audit should be periodically performed in Department of Surgery to analyze the present scenario of drugs prescribed for the surgical/post-operative patients. This will help us to use the medicines rationally and decrease the adverse effects in surgical patients. The main aim of the study was to evaluate the drugs prescribing pattern in the Surgery Department in Tertiary Care Teaching Institute.Methods: Patients’prescriptions or case record forms were randomly collected over a period of 1 year from the Department of Surgery at GGS Medical College and Hospital, Faridkot, Punjab (India) for analysis and rationalization.Results: A total of 900 prescriptions was collected and analyzed for drugs used in surgical patients. Average number of drugs prescribed is 4.26. The most commonly prescribed drugs were anti-microbial agents (AMAs), gastrointestinal tract (GIT) related, non-steroidal anti-inflammatory drugs (NSAIDs) and multivitamins and trace elements, and their percentages were 37.90%, 23.36%, 14.14 %, and 9.11% respectively. About 95% drugs were prescribed by non-generic (Trade) names. Drugs prescribed from National Essential Medicines List (EML) and World Health Organization EML were 69.25% and 45.31% respectively. Average cost per prescription per day was Rs. 610/- (INR) or $10.34 USD in a surgical patient.Conclusions: There is a high tendency and frequency to prescribe four and more than four drugs to post-operative patients. Most drugs prescribed were AMAs, GIT related, NSAIDs and Multivitamins and trace elements. There is an urgent need to develop proper prescription writing skills in budding doctors regarding the use of EML/drugs list and generic medicines to reduce the cost of treatment

In vitro comparative evaluation of microleakage of newly introduced Dyad Flow and total and self etch adhesives in class V resin composite restorations

Introduction The aim of this study was to evaluate marginal sealing ability of newly introduced Dyad Flow flowable composite and compare to total-etch and self-etch adhesive system at the coronal and apical margins of class V resin composite restorations. Material and Methods A standard class V cavity (3 mm mesiodistal width, 3 mm occlusogingival height and 1.5 mm axial depth) was prepared on the buccal surface of freshly extracted sound human teeth. Occlusal and gingival margins of the cavities were located in enamel and cementum/dentin, respectively. Teeth were randomly assigned into the three groups (n=10) and restored with different composite materials following the manufacturer's instructions: group I was restored with nanohybrid resin composite using total-etch bonding agent ; group II was restored with nanohybrid resin composite using self-etch technique; group III was restored with flowable composite (Dyad Flow), respectively. After finishing and polishing, the teeth were coated with nail varnish and immersed in rhodamine B dye and sectioned longitudinally. Dye penetration was examined under stereomicroscope and scored separately for occlusal and gingival margins on a 0-3 ordinal scale. Data were analyzed with Kruskal-Wallis, Mann-Whitney and Wilcoxon tests (a=0.05). Result Statistical analysis showed that specimens restored with the total-etch and self-etch adhesive systems revealed reduced leakage at the coronal margin. At the apical margin, Dyad Flow showed greater leakage than other groups. Conclusion Newly introduced flowable composite Dyad Flow showed inferior adhesive bond with enamel and dentin compared to total-etch and self-etch techniques