Biomonitoring of Trace Metals in the Coastal Waters Using Bivalve Molluscs

Several environmental contaminants including toxic trace metals are being discharged into the coastal environment causing serious threat to marine organisms and posing public health risk. Marine bivalves (mussel, oyster, and clam) have been successfully used as sentinel organisms for monitoring contaminant levels, including trace metals, in coastal waters around the globe. Chemical analyses measure the contaminants present in the biota but do not necessarily reveal potential biological effects. Therefore, the need to detect and assess the effects of contaminants, especially at low concentrations, has led to the development of molecular markers of contaminant effects called biomarkers. Owing to their short time of response, biomarkers in marine bivalves are used as early warning signals of biological effects caused by environmental pollutants. Research into the development and application of accurate biomarker-based monitoring tools for the environmental contaminants has been intensified in several developed countries

Ecology, life history, and fisheries potential of the flathead lobster (Thenus orientalis) in the Arabian Gulf

This study, which included examination of the distribution and life history and a stock assessment of the flathead lobster (Thenus orientalis), is the first of its kind in the waters of Saudi Arabia in the Arabian Gulf, also known as the Persian Gulf. The flathead lobster is widely distributed in this region, although it is more abundant in the central and northern Arabian Gulf. Carapace lengths at 50% and 95% maturity are 59 and 65 mm for females and 58 and 71 mm for males. The fecundity of 4 berried females ranged from 26,000 to 76,000 eggs per spawning, and the fertilization rate exceeded 97%. Length-frequency data were consistent with just 2 cohorts, indicating that this species has a short life span and high growth coefficient (K=0.846 year(-1)). Large fishing boats (called dhows) accounted for more than 98% of the total landings. Estimates of natural mortality rates from use of generalized depletion models have high statistical precision and a magnitude compatible with short life history. In addition, abundance levels estimated with the depletion model are sufficient to support a sustainable small-scale fishery either as bycatch of shrimp trawlers or as a resource targeted with specialized gear. A targeted fishery for flathead lobster could be set during the off months of the shrimp trawl fishery (February-July), reducing interference with the reproduction cycle.info:eu-repo/semantics/publishedVersio

Morphological lodge of desi cotton (Gossypium arboreum L.) genotypes and stage-manage by planting log under dry tropical prospect

Planting log is the most considerable factor which directly manipulates the plant traits under naturally prevailing environment. The aim of the trial was to ensure the influence of planting hiatus on the morphological cabin of Desi cotton (Gossypium arboreum L.) varieties under dry tropical coast. The research was carried out during 2016 on three desi cotton genotypes C1 (FDH-512), C2 (FDH-502), C3 (FDH-170) under three-fortnightsowing regimes (S1 = 15. March, S2 = 1. April and S3 = 15. April) at agronomy research area in the Lasbela University of Agriculture, Water and Marine Science, Uthal, Lasbela, Pakistan. Momentous results were originated for different morphological traits according to the arid environments. Significant results were observed for traits i.e.; number of monopodial branches, number of sympodial branches, number of capsule per plant, number of seeds per capsule, number of locules per capsule, number of seeds per locules, weight of seed per capsule, seed colour, seed yield per plant, lint percentage, root shoot ratio (%), root depth (cm) for various sowing dates and desi cotton varieties. Results of the traits like i.e. the number of locules and per capsule, a number of seeds per locules was yielded completely non-significant outcomes both for the diverse sowing period and desi cotton genotypes. The interaction between the both factors was found to be non-significant in all traits. The correlation amongst cotton individual characteristics was observed, it was found that capsules per plant and lint percentage, monopodial branches per plant, root shoot ratio, root depth, seed weight per capsule and seed yield per plant were significantly and positively correlated. The seed yield and lint percentage was also significantly correlated, which showed that selection may be positive responsive in sense of lint percentage, monopodial branches, seed yield per plant, capsules per plant and seed weight per capsule to get a superior yield of cotton. Under the existing dry climatic condition, it was found that the finest planting window of 15. April for the desi cotton FDH-170 is most suitable for its cultivation

Cluster Analysis of Patients’ Clinical Information for Medical Practitioners and Insurance Companies

A number of approaches have been proposed in literature to collect and classify patient related information for purpose of better clinical diagnosis and thus safer treatment and administration of related activities. This type of data collection and classification benefits doctors and the corresponding hospitals. However, no effort is made, as to our knowledge, to classify accumulated data within insurance company databases to facilitate doctors as well as insurance companies for better analysis and cost-effective treatment of patients suffering from chronic (and expensive to treat) diseases such as related to oncology. In this study, a customized self-organized data classification model is applied to an insurance company database to build clusters based on age, patient condition, tests done, etc. These clusters provide integrated analysis to doctors in providing patient-specific, disease-specific, etc., and thus cost-effective treatment. On the other side, it saves on costs to be incurred on repeated tests to be done on the patient. An experimental setup is developed to train such a network, and testing results are presented. The practical constraints are also discussed

Macrobenthic Community Structure in the Northwestern Arabian Gulf, Twelve Years after the 1991 Oil Spill

The biota in the Arabian Gulf faces stress both from natural (i.e., hyper salinity and high sea surface temperature), and human (i.e., from oil-related activities) sources. The western Arabian Gulf was also impacted by world's largest oil spill (1991 Oil Spill). However, benthic research in this region is scarce and most of the studies have been conducted only in small areas. Here, we present data on macrobenthos collected during 2002–2003 from the open waters and inner bays in the northwestern Arabian Gulf aimed to assess the ecological status and also to evaluate the long-term impact, if any, of the 1991 Oil Spill. A total of 392 macrobenthic taxa with an average (±SE) species richness (S) of 71 ± 2, Shannon-Wiener species diversity (H′) of 4.9 ± 0.1, and density of 3,181 ± 359 ind. m−2 was recorded from the open water stations. The open waters have “slightly disturbed” (according to AZTI's Marine Biotic Index, AMBI) conditions, with “good-high” (according to multivariate-AMBI, M-AMBI) ecological status indicating the absence of long-term impacts of the oil spill. Overall, 162 taxa were recorded from inner bays with average (±SE) values of S 41 ± 9, H′ 3.48 ± 0.39, and density 4,203 ± 1,042 ind. m−2. The lower TPH (Total Petroleum Hydrocarbons) stations (LTS, TPH concentrations <70 mg kg−2) show relatively higher S, H' and density compared to the higher TPH stations (HTS, TPH concentrations ≥100 mg kg−2). In the inner bays, AMBI values indicate slightly disturbed conditions at all stations except one, which is moderately disturbed. M-AMBI values indicate good status at LTS, while, high, good, moderate, and poor status at HTS. The “moderately disturbed” conditions with “moderate-poor” ecological status in some locations of the inner bays specify a severe long-term impact of the oil spill

Cluster Analysis of Patients’ Clinical Information for Medical Practitioners and Insurance Companies

A number of approaches have been proposed in literature to collect and classify patient related information for purpose of better clinical diagnosis and thus safer treatment and administration of related activities. This type of data collection and classification benefits doctors and the corresponding hospitals. However, no effort is made, as to our knowledge, to classify accumulated data within insurance company databases to facilitate doctors as well as insurance companies for better analysis and cost-effective treatment of patients suffering from chronic (and expensive to treat) diseases such as related to oncology. In this study, a customized self-organized data classification model is applied to an insurance company database to build clusters based on age, patient condition, tests done, etc. These clusters provide integrated analysis to doctors in providing patient-specific, disease-specific, etc., and thus cost-effective treatment. On the other side, it saves on costs to be incurred on repeated tests to be done on the patient. An experimental setup is developed to train such a network, and testing results are presented. The practical constraints are also discussed.</span

Information technology substitution revisited

Taking advantage of the opportunities created by the price adjusted performance improvement in IT depends in part on the ability of IT capital to substitute for other inputs in production. Studies in the IS literature as well as most economics training that examine substitution of IT capital for other inputs use the Allen elasticity of substitution (AES). We present a less-well-known measure for the elasticity of substitution, the Morishima Elasticity of Substitution (MES). In contrast to the AES which is misleading when there are three or more inputs – such as non-IT capital, labor and IT capital – the MES provides a substitution measure where the scale is meaningful, and the measure differs depending upon which price is changing. This is particularly important for IT capital as prices have been declining and there is evidence that IT capital can substitute for non-IT capital or labor in a qualitatively different way than non-IT capital and labor substitute for each other. Methodologically we also show the impact of imposing local regularity – for example, monotonicity of output from increases in inputs – that we do through Bayesian methods employed to estimate the underlying functions that are used to calculate various measures of substitution. We demonstrate the importance of the MES as an under-recognized measure of substitution and the impact of imposing local regularity using an economy-wide industry-level dataset covering 1998-2009 at the three-digit NAICS level. Our MES results show that reductions in the price of IT capital increase the quantity of IT capital in use but are unlikely to change the input share of IT capital – the value of IT capital as a proportion of the value of all inputs, in contrast to major studies using the AES. In addition, estimates for both elasticities of substitution are more stable after imposing local regularity. Both of these advances – that is, the MES and imposing local regularity – have potential to impact future work on IT productivity, IT pricing, IT cost estimation and any type of analysis that posits the substitution of IT capital for non-IT capital or labor