Acoustic and petrophysical relationships in low-shale sandstone reservoir rocks

This paper describes the measurements of the acoustic and petrophysical properties of two suites of low-shale sandstone samples from North Sea hydrocarbon reservoirs, under simulated reservoir conditions. The acoustic velocities and quality factors of the samples, saturated with different pore fluids (brine, dead oil and kerosene), were measured at a frequency of about 0.8 MHz and over a range of pressures from 5 MPa to 40 MPa. The compressional-wave velocity is strongly correlated with the shear-wave velocity in this suite of rocks. The ratio V-P/V-S varies significantly with change of both pore-fluid type and differential pressure, confirming the usefulness of this parameter for seismic monitoring of producing reservoirs. The results of quality factor measurements were compared with predictions from Biot-flow and squirt-flow loss mechanisms. The results suggested that the dominating loss in these samples is due to squirt-flow of fluid between the pores of various geometries. The contribution of the Biot-flow loss mechanism to the total loss is negligible. The compressional-wave quality factor was shown to be inversely correlated with rock permeability, suggesting the possibility of using attenuation as a permeability indicator tool in low-shale, high-porosity sandstone reservoirs.

Carbon dioxide induced stomatal closure increases radiative forcing of climate via a rapid reduction in low cloud

We performed an ensemble of twelve five-year experiments using a coupled climate-carbon-cycle model with scenarios of prescribed atmospheric carbon dioxide concentration; CO2 was instantaneously doubled or quadrupled at the start of the experiments. Within these five years, climate feedback is not significantly influenced by the effects of climate change on the carbon system. However, rapid changes take place, within much less than a year, due to the physiological effect of CO2 on plant stomatal conductance, leading to adjustment in the shortwave cloud radiative effect over land, due to a reduction in low cloud cover. This causes a 10% enhancement to the radiative forcing due to CO2, which leads to an increase in the equilibrium warming of 0.4 and 0.7 K for doubling and quadrupling. The implications for calibration of energy-balance models are discussed.

Role of temperature, moisture and Trichoderma species on the survival of Fusarium oxysporum ciceri in the rainfed areas of Pakistan

It has been observed in the present study that when spores of Trichoderma harzianum (Th-2) isolate were applied in the sandy clay loam soil and continuously incubated for 4 months at 25 degrees C and 35 degrees C and at three water potentials, -0.03 MPa, -0.3 MPa and <-50 MPa, it has resulted in significantly reduced (P<0.05), growth of Fusarium oxysporum ciceri (Foc) on branches of chickpea plant. The pathogen population was greatly reduced in the moist soil (43 MPa) when compared with the wet soil (-0.03 MPa) at both temperatures which was indicated by greater colonization and growth of T. harzanum-2 on the branch pieces of chickpea plants. The pathogen was completely eradicated from the chickpea branch pieces, after 6 months at 35 degrees C in the moist soil. In air-dry soil (<-50 MPa), Foc survived in 100% of the branch pieces even after 6 months at both temperatures. When chickpea plant branch pieces having pathogen was sprayed with Th-2 antagonistic isolates of Trichoderma spp., the Th-2 isolate killed the pathogen up to minimum level (10-12%) after 5 months at 35 degrees C in the sandy clay loam soil. It can be concluded that in chickpea growing rainfed areas of Pakistan having sandy clay loam soil, Foc can be controlled by using specific Trichoderma spp., especially in the summer season as after harvest of the crop the temperature increased up and there is rainfall during this period which makes the soil moist. This practice will be able to reduce the inoculum of Foc during this hot period as field remain fallow till next crop is sown in most of the chickpea growing rainfed areas of Pakistan.

Enhancing change detection in low-quality surveillance footage using markov random fields

Urban surveillance footage can be of poor quality, partly due to the low quality of the camera and partly due to harsh lighting and heavily reflective scenes. For some computer surveillance tasks very simple change detection is adequate, but sometimes a more detailed change detection mask is desirable, eg, for accurately tracking identity when faced with multiple interacting individuals and in pose-based behaviour recognition. We present a novel technique for enhancing a low-quality change detection into a better segmentation using an image combing estimator in an MRF based model.

Objective detection of sting jets in low-resolution datasets

Sting jets are transient coherent mesoscale strong wind features that can cause damaging surface wind gusts in extratropical cyclones. Currently, we have only limited knowledge of their climatological characteristics. Numerical weather prediction models require enough resolution to represent slantwise motions with horizontal scales of tens of kilometres and vertical scales of just a few hundred metres to represent sting jets. Hence, the climatological characteristics of sting jets and the associated extratropical cyclones can not be determined by searching for sting jets in low-resolution datasets such as reanalyses. A diagnostic is presented and evaluated for the detection in low-resolution datasets of atmospheric regions from which sting jets may originate. Previous studies have shown that conditional symmetric instability (CSI) is present in all storms studied with sting jets, while other, rapidly developing storms of a similar character but no CSI do not develop sting jets. Therefore, we assume that the release of CSI is needed for sting jets to develop. While this instability will not be released in a physically realistic way in low-resolution models (and hence sting jets are unlikely to occur), it is hypothesized that the signature of this instability (combined with other criteria that restrict analysis to moist mid-tropospheric regions in the neighbourhood of a secondary cold front) can be used to identify cyclones in which sting jets occurred in reality. The diagnostic is evaluated, and appropriate parameter thresholds defined, by applying it to three case studies simulated using two resolutions (with CSI-release resolved in only the higher-resolution simulation).

Screening human intestinal Bifidobacterium strains for growth, acidification, EPS production and viscosity potential in low-fat milk

Bifidobacterium strains of human origin were screened for their ability to grow in milk and produce exopolysaccharides (EPS). Bifidobacterium strains were grown in low-fat UHT milk and were evaluated for their growth, acidification properties, EPS production and ability to increase the viscosity of fermented milk. The strains that grew well in milk were strains of Bifidobacterium breve and Bifidobacterium longum and B. longum subsp. longum. Among the 22 strains, EPS was produced by Bifidobacterium bifidum ALM 35, B. breve NCIMB 8807 (UCC 2003), B. longum subsp. infantis CCUG 52486 and Bifidobacterium infantis NCIMB 702205 at concentrations ranging from 25 to 140 . The molecular mass and the composition varied considerably, depending on the strain. Analysis of the correlation between the apparent viscosity of the fermented milk and pH indicated that the EPS produced during the acidification of milk possibly contributed to the viscosity of the milk products.

Predicting metal-binding site residues in low-resolution structural models

The accurate prediction of the biochemical function of a protein is becoming increasingly important, given the unprecedented growth of both structural and sequence databanks. Consequently, computational methods are required to analyse such data in an automated manner to ensure genomes are annotated accurately. Protein structure prediction methods, for example, are capable of generating approximate structural models on a genome-wide scale. However, the detection of functionally important regions in such crude models, as well as structural genomics targets, remains an extremely important problem. The method described in the current study, MetSite, represents a fully automatic approach for the detection of metal-binding residue clusters applicable to protein models of moderate quality. The method involves using sequence profile information in combination with approximate structural data. Several neural network classifiers are shown to be able to distinguish metal sites from non-sites with a mean accuracy of 94.5%. The method was demonstrated to identify metal-binding sites correctly in LiveBench targets where no obvious metal-binding sequence motifs were detectable using InterPro. Accurate detection of metal sites was shown to be feasible for low-resolution predicted structures generated using mGenTHREADER where no side-chain information was available. High-scoring predictions were observed for a recently solved hypothetical protein from Haemophilus influenzae, indicating a putative metal-binding site.