Estimating the uniaxial compressive strength of pyroclastic rocks from the slake durability index

Because the preparation of standard samples may not always be possible for weak or soft rocks, the prediction of uniaxial compressive strength (UCS) from indirect methods is widely used for preliminary investigations. In this study, the possibility of predicting UCS from the slake durability index (SDI) was investigated for pyroclastic rocks. For this purpose, pyroclastic rocks were collected from 31 different locations in the Cappadocian Volcanic Province of Turkey. The UCS and SDI tests were carried out on the samples in the laboratory. The UCS values were correlated with the SDI values and a very strong exponential relation was found between the two parameters. Since some data were scattered over the UCS values of 20 MPa, the correlation plot was redrawn for above and below the UCS values of 20 MPa, respectively. Very strong linear correlations were developed for two cases. Our concluding remark is that the UCS of pyroclastic rocks can be estimated from the SDI.

     

Triose Phosphate Isomerase as an Endogenous Time-temperature Integrator to Verify Adequacy of Roast Beef Processing

Bovine muscle type had a large influence on the initial activity and heat stability of triose phosphate isomerase (TPI). TPI activity in the round muscles was more heat labile than in the chuck muscles. Residual TPI activity in bovine semimembranosus muscle was determined after cooking using adequate and corresponding inadequate U.S. Department of Agriculture processing schedules. In both water bath and pilot oven studies, TPI activity was similar in adequately processed beef (about 2 U/g) and increased when inadequately processed by reducing the holding time by 0.5 and 1.0 log at each temperature. Taken together, these results suggested that TPI could be used as an endogenous time-temperature indicator to verify processing adequacy of roast beef if the muscle used in the product was known.     

Electrical resistivity measurements to predict abrasion resistance of rock aggregates

The prediction of Los Angeles (LA) abrasion loss from some indirect tests is useful for practical applications. For this purpose, LA abrasion, electrical resistivity, density and porosity tests were carried out on 27 different rock types. LA abrasion loss values were correlated with electrical resistivity and a good correlation between the two parameters was found. To see the effect of rock class on the correlation, regression analysis was repeated for igneous rocks, metamorphic rocks and sedimentary rocks, respectively. It was seen that correlation coefficients were increased for the rock classes. In addition, the data were divided into two groups according to porosity and density, respectively. After repeating regression analysis for these porosity and density groups, stronger correlations were obtained compared to the equation derived for all rocks. The validity of the derived equations was statistically tested and it was shown that all derived equations were significant. Finally, it can be said that all derived equations can alternatively be used for the estimation of LA abrasion loss from electrical resistivity.     

Determination of physical properties of carbonate rocks from P-wave velocity

Velocity, density, porosity, void ratio, water absorption by weight and P-wave velocity tests were conducted on 14 different carbonate rocks. Strong correlations between P-wave velocity and all the physical properties of the rock were found. The relations follow a linear function. The equations developed were compared with others in the literature. Although it appears that the physical properties of the tested carbonate rocks can be estimated from P-wave velocity, the validity of the derived equations must be checked for other carbonate rocks as the equations given are likely to be specific to the test method and vary with rock type, degree of saturation and presence of bedding planes.      

Human Enteric Viruses as Causes of Foodborne Disease

Recent epidemiological evidence indicates that enteric viruses are the leading cause of foodborne disease in the U.S.A. and, indeed, worldwide. Certainly, advances in epidemiology and molecular biology have improved the ability to study this previously elusive group of foodborne pathogens. The purpose of this article is to review the agents, transmission routes, epidemiology, persistence, diagnosis, and detection of foodborne viruses and their diseases, with specific reference to the role that contemporary technologies have had in improving our understanding of this important group of emerging foodborne pathogens.     

Mixed-Alkali Effect in Li2O–Na2O–K2O–B2O3 Glasses: Infrared and Optical Absorption Studies

The mixed-alkali effect (MAE) has been investigated in the glass system (40 ? x)Li₂O–xNa₂O–10K₂O–50B₂O₃ (0 mol% ≤ x ≤ 40 mol%) through density, modulated differential scanning calorimetry (DSC), and optical absorption studies. From the absorption studies, the values of the optical band gap (E _opt) for direct transition and Urbach energy (ΔE) have been evaluated. The values of E _opt and ΔE show nonlinear behavior with the compositional parameter. The density and glass-transition temperature of the present glasses also show nonlinear variation, supporting the existence of MAE. The infrared (IR) spectra of the glasses reveal the presence of three- and four-coordinated boron atoms. The specific vibrations of Li–O, Na–O, and K–O bonds were observed in the present IR study.     

Discovering and exploiting program phases

Understanding program behavior is at the foundation of computer architecture and program optimization. Many programs have wildly different behavior on even the largest of scales (that is, over the program's complete execution). During one part of the execution, a program can be completely memory bound; in another, it can repeatedly stall on branch mispredicts. Average statistics gathered about a program might not accurately picture where the real problems lie. This realization has ramifications for many architecture and compiler techniques, from how to best schedule threads on a multithreaded machine, to feedback-directed optimizations, power management, and the simulation and test of architectures. Taking advantage of time-varying behavior requires a set of automated analytic tools and hardware techniques that can discover similarities and changes in program behavior on the largest of time scales. The challenge in building such tools is that during a program's lifetime it can execute billions or trillions of instructions. How can high-level behavior be extracted from this sea of instructions? Some programs change behavior drastically, switching between periods of high and low performance, yet system design and optimization typically focus on average system behavior. It is argued that instead of assuming average behavior, it is now time to model and optimize phase-based program behavior.     

Prevalence of antibiotic and heavy metal resistance in Gram negative bacteria isolated from rivers in northern Pakistan

Antibiotic and metal resistance is a global occurring phenomenon and a universal threat. The release of antibiotics and metals into the environment like natural water bodies stimulates resistant microbes that could become a reservoir for a resistant gene pool for other pathogenic bacteria. The aim of the study was to determine microbial diversity, distribution of antibiotic and metal resistance bacteria from five rivers. The resistance of 168 Gram negative isolates was tested against 10 antibiotics and five metals. The study revealed a high incidence of bacterial isolates resistant to ampicillin (44.7%), streptomycin (37.3%) and chloramphenicol (33.9%). The highest level of antibiotic resistance was detected in the River Ravi. The multiple antibiotic resistance (MAR) index of the five rivers ranged from <0.2 to 0.6. Isolates displayed tolerance to different concentrations of heavy metals. High antibiotic and metal‐resistances in samples from the Rivers Ravi and Soan suggest co‐resistance amongst the bacterial populations.     

Empirical methods to predict the abrasion resistance of rock aggregates

The possibility of predicting the Los Angeles (L.A.) abrasion loss from the Schmidt hammer, point load and porosity tests was investigated using 9 igneous, 11 metamorphic and 15 sedimentary rocks with L.A. values ranging from 10 to 76%. Regression analysis indicated a strong correlation (r ² = 0.72) between L.A. abrasion loss and point load and a good correlation (r ² = 0.62) between L.A. abrasion loss and Schmidt hammer value. When the samples were divided according to porosity (n < 1% and n > 1%), stronger correlations were obtained, especially for the point load index. The predictions from the Schmidt hammer results were not as good but within acceptable limits.