Physicochemical properties associated with the presence of <Emphasis Type="Italic">Burkholderia pseudomallei</Emphasis> in small ruminant farm water supplies in Peninsular Malaysia

Burkholderia pseudomallei causes melioidosis, a life-threatening infection in both humans and animals. Water is an important reservoir of the bacteria and may serve as a source of environmental contamination leading to infection. B. pseudomallei has an unusual ability to survive in water for a long period. This paper investigates physicochemical properties of water associated with the presence of B. pseudomallei in water supply in small ruminant farms in Peninsular Malaysia. Physicochemical properties of water samples taken from small ruminant farms that included temperature, pH, dissolved oxygen (DO₂), optical density (OD), and chemical oxygen demand (COD) were measured after which the samples were cultured for B. pseudomallei. Multivariable logistic regression model revealed that slightly acidic water pH and higher COD level were significantly associated with the likelihood of the B. pseudomallei presence in the water.     

Optimizing the flow adjustment of constituent concentrations via LOESS for trend analysis

Trend analysis of stream constituent concentrations requires adjustment for exogenous variables like discharge because concentrations often have variable relations with flow. To remove the influence of flow on stream water quality data, an accurate characterization of the relationship between the constituent and streamflow is needed. One popular method, locally weighted regression (LOESS), provides an effective means for flow-adjusting concentrations. The LOESS fit can be tailored to the data via the smoothing parameter (f), so that the user can avoid overfitting or oversmoothing the data. However, it is a common practice to use a single f value when flow-adjusting water quality data for trend analysis. This study provides a robust, automated method for determining the optimal f value (f_opt) for each dataset via an iterative K-fold cross-validation procedure that minimizes prediction error in LOESS. The method is developed by analyzing datasets of seven different constituents across 17 sites (119 datasets total) from a stream monitoring program in northwest Arkansas (USA). We recommend using 10 iterations of 10-fold cross-validation (10?×?10 CV) in order to select f_opt when flow-adjusting water quality data with LOESS. The use of a default f value did not produce different trend interpretations for the data used here; however, the proposed approach may be helpful in other water quality studies which employ similar statistical fitting methods. Additionally, we provide an implementation of the method in the R statistical computing environment.     

Estimation of underwater visibility in coastal and inland waters using remote sensing data

An optical method is developed to estimate water transparency (or underwater visibility) in terms of Secchi depth (Z _sd ), which follows the remote sensing and contrast transmittance theory. The major factors governing the variation in Z _sd , namely, turbidity and length attenuation coefficient (1/(c + K _d ), c = beam attenuation coefficient; K _d  = diffuse attenuation coefficient at 531 nm), are obtained based on band rationing techniques. It was found that the band ratio of remote sensing reflectance (expressed as (R _rs (443) + R _rs (490))/(R _rs (555) + R _rs (670)) contains essential information about the water column optical properties and thereby positively correlates to turbidity. The beam attenuation coefficient (c) at 531 nm is obtained by a linear relationship with turbidity. To derive the vertical diffuse attenuation coefficient (K _d ) at 531 nm, K _d (490) is estimated as a function of reflectance ratio (R _rs (670)/R _rs (490)), which provides the bio-optical link between chlorophyll concentration and K _d (531). The present algorithm was applied to MODIS-Aqua images, and the results were evaluated by matchup comparisons between the remotely estimated Z _sd and in situ Z _sd in coastal waters off Point Calimere and its adjoining regions on the southeast coast of India. The results showed the pattern of increasing Z _sd from shallow turbid waters to deep clear waters. The statistical evaluation of the results showed that the percent mean relative error between the MODIS-Aqua-derived Z _sd and in situ Z _sd values was within ±25%. A close agreement achieved in spatial contours of MODIS-Aqua-derived Z _sd and in situ Z _sd for the month of January 2014 and August 2013 promises the model capability to yield accurate estimates of Z _sd in coastal, estuarine, and inland waters. The spatial contours have been included to provide the best data visualization of the measured, modeled (in situ), and satellite-derived Z _sd products. The modeled and satellite-derived Z _sd values were compared with measurement data which yielded RMSE = 0.079, MRE = ?0.016, and R ²  = 0.95 for the modeled Z _sd and RMSE = 0.075, MRE = 0.020, and R ²  = 0.95 for the satellite-derived Z _sd products.     

Assessment of physicochemical parameters and prevalence of virulent and multiple-antibiotic-resistant <Emphasis Type="Italic">Escherichia coli</Emphasis> in treated effluent of two wastewater treatment plants and receiving aquatic <Emphasis Type="Italic">milieu</Emphasis> in Durban,South Africa

The poor operational status of some wastewater treatment plants often result in the discharge of inadequately treated effluent into receiving surface waters. This is of significant public health concern as there are many informal settlement dwellers (ISDs) that rely on these surface waters for their domestic use. This study investigated the treatment efficiency of two independent wastewater treatment plants (WWTPs) in Durban, South Africa and determined the impact of treated effluent discharge on the physicochemical and microbial quality of the receiving water bodies over a 6-month period. Presumptive Escherichia coli isolates were identified using biochemical tests and detection of the mdh gene via PCR. Six major virulence genes namely eae, hly, fliC, stx1, stx2, and rfbE were also detected via PCR while antibiotic resistance profiles of the isolates were determined using Kirby-Bauer disc diffusion assay. The physicochemical parameters of the wastewater samples ranged variously between 9 and 313.33 mg/L, 1.52 and 76.43 NTUs, and 6.30 and 7.87 for COD, turbidity, and pH respectively, while the E. coli counts ranged between 0 and 31.2?×?10³ CFU/ml. Of the 200 selected E. coli isolates, the hly gene was found in 28 %, fliC in 20 %, stx2 in 17 %, eae in 14 %, with stx1 and rfbE in only 4 % of the isolates. Notable resistance was observed toward trimethoprim (97 %), tetracycline (56 %), and ampicillin (52.5 %). These results further highlight the poor operational status of these WWTPs and outline the need for improved water quality monitoring and enforcement of stringent guidelines.     

Discriminant analysis for the prediction of sand mass distribution in an urban stormwater holding pond using simulated depth average flow velocity data

The approach of this paper is to predict the sand mass distribution in an urban stormwater holding pond at the Stormwater Management And Road Tunnel (SMART) Control Centre, Malaysia, using simulated depth average floodwater velocity diverted into the holding during storm events. Discriminant analysis (DA) was applied to derive the classification function to spatially distinguish areas of relatively high and low sand mass compositions based on the simulated water velocity variations at corresponding locations of gravimetrically measured sand mass composition of surface sediment samples. Three inflow parameter values, 16, 40 and 80 m³ s^?1, representing diverted floodwater discharge for three storm event conditions were fixed as input parameters of the hydrodynamic model. The sand (grain size?>?0.063 mm) mass composition of the surface sediment measured at 29 sampling locations ranges from 3.7 to 45.5 %. The sampling locations of the surface sediment were spatially clustered into two groups based on the sand mass composition. The sand mass composition of group 1 is relatively lower (3.69 to 12.20 %) compared to group 2 (16.90 to 45.55 %). Two Fisher’s linear discriminant functions, F ₁ and F ₂, were generated to predict areas; both consist of relatively higher and lower sand mass compositions based on the relationship between the simulated flow velocity and the measured surface sand composition at corresponding sampling locations. F ₁?=??9.405?+?4232.119?×?A???1795.805?×?B?+?281.224?×?C, and F ₂?=??2.842?+?2725.137?×?A???1307.688?×?B?+?231.353?×?C. A, B and C represent the simulated flow velocity generated by inflow parameter values of 16, 40 and 80 m³ s^?1, respectively. The model correctly predicts 88.9 and 100.0 % of sampling locations consisting of relatively high and low sand mass percentages, respectively, with the cross-validated classification showing that, overall, 82.8 % are correctly classified. The model predicts that 31.4 % of the model domain areas consist of high-sand mass composition areas and the remaining 68.6 % comprise low-sand mass composition areas.     

Assessing spatio-temporal trend of vector breeding and dengue fever incidence in association with meteorological conditions

Th aim of this study is to investigate spatio-temporal trends of dengue vector breeding and epidemic (disease incidence) influenced by climatic factors. The spatio-temporal (low-, medium-, and high-intensity periods) evaluation of entomological and epidemiological investigations along with climatic factors like rainfall (RF), temperature (T_max), relative humidity (RH), and larval indexing was conducted to develop correlations in the area of Lahore, Pakistan. The vector abundance and disease transmission trend was geo-tagged for spatial insight. The sufficient rainfall events and optimum temperature and relative humidity supported dengue vector breeding with high larval indices for water-related containers (27–37%). Among temporal analysis, the high-intensity period exponentially projected disease incidence followed by post-rainfall impacts. The high larval incidence that was observed in early high-intensity periods effected the dengue incidence. The disease incidence had a strong association with RF (r = 0.940, α = 0.01). The vector larva occurrence (r = 0.017, α = 0.05) influenced the disease incidence. Similarly, RH (r = 0.674, α = 0.05) and average T_max (r = 0.307, α = 0.05) also induced impact on the disease incidence. In this study, the vulnerability to dengue fever highly correlates with meteorological factors during high-intensity period. It provides area-specific understanding of vector behavior, key containers, and seasonal patterns of dengue vector breeding and disease transmission which is essential for preparing an effective prevention plan against the vector.     

Genotoxic effects and gene expression in <Emphasis Type="Italic">Danio rerio</Emphasis> (Hamilton 1822) (Cypriniformes: Cyprinidae) exposed to mining-impacted tributaries in Manizales,Colombia

The zebrafish (Danio rerio) is one of the most studied aquatic organisms for water biomonitoring, due to its sensitivity to environmental degradation and resistance to toxic substances. This study determined the presence of micronuclei and nuclear abnormalities in peripheral blood erythrocytes, and assessed the gene expression of caspase-3 (CASP-3) and metallothionein 1 (MT-1) in the gills and liver of D. rerio. The study fish (n = 45) were exposed to water collected from two stations with mining impact (E2 and E3) and a reference station without evident mining contamination (E1), all located in La Elvira stream (Manizales-Colombia). In addition, a positive control (PC) with HgCl₂ (50 μg/L) and negative control (NC) with tap water were included. The fish from the PC and E2 and E3 treatments displayed genotoxic effects and changes in gene expression, with significant differences in micronuclei formation and the presence of blebbed nuclei. The cytochrome oxidase subunit I (COI) gene was used as reference and proved to be stable compared to the β-actin and 28S ribosomal RNA (28S) genes. In gills, CASP-3 expression was higher in the PC, and MT-1 expression was higher in the PC and E3 treatment. In liver, CASP-3 was expressed in the E2 treatment, and MT-1 expression was low. These results show that the genotoxic effects and differential gene expression observed in fish exposed to water from La Elvira stream could also be affecting the organisms present in this habitat.     

Seasonal variations and source profile of <Emphasis Type="Italic">n</Emphasis>-alkanes in particulate matter (PM<Subscript>10</Subscript>) at a heavy traffic site,Delhi

Delhi is one of the most polluted cities in the world. The generation of aerosols in the lower atmosphere of the city is mainly due to a large amount of natural dust advection and sizable anthropogenic activities. The compositions of organic compounds in aerosols are highly variable in this region and need to be investigated thoroughly. Twenty-four-hour sampling to assess concentrations of n-alkanes (ng/m³) in PM₁₀ was carried out during January 2015 to June 2015 at Indira Gandhi Delhi Technical University for Women (IGDTUW) Campus, Delhi, India. The total average concentration of n-alkanes, 243.7 ± 5.5 ng/m³, along with the diagnostic tools has been calculated. The values of CPI₁, CPI₂, and CPI₃ for the whole range of n-alkanes series, petrogenic n-alkanes, and biogenic n-alkanes were 1.00, 1.02, and 1.04, respectively, and C _max were at C₂₅ and C₂₇. Diagnostic indices and curves indicated that the dominant inputs of n-alkanes are from petrogenic emissions, with lower contribution from biogenic emissions. Significant seasonal variations were observed in average concentrations of n-alkanes, which is comparatively higher in winter (187.4 ± 4.3 ng/m³) than during the summer season (56.3 ± 1.1 ng/m³).     

Carbon and nitrogen mineralization in Vertisol as mediated by type and placement method of residue

Selection of appropriate residue application method is essential for better use of biomass for soil and environmental health improvement. A laboratory incubation experiment was conducted for 75 days to investigate C and N mineralization of residues of soybean (Glycine max L.), chickpea (Cicer arietinum L.), maize (Zea mays L.), and wheat (Triticum aestivum L.) placed on the soil surface and incorporated into the soil. The residue of soybean and chickpea had a greater decomposition rate than that of maize and wheat, despite of their placements. Higher rate of decomposition of the residue of soybean and chickpea was recorded when it was kept on the soil surface while soil incorporation of residue of wheat and maize resulted in faster decomposition. Therefore, these findings could be used as guidelines for management of crop residue application in farmland to improve soil and environmental quality.     

A regional algorithm to model mesozooplankton biomass along the southwestern Bay of Bengal

A three-dimensional regression analysis attempted to model mesozooplankton (MSP) biomass using sea surface temperature (SST) and chlorophyll-a (Chl-a). The study was carried out from January 2014 to July 2015 in the southwestern Bay of Bengal (BoB) and sampling was carried out on board Sagar Manjusha and Sagar Purvi. SST ranged from 26.2 to 33.1 °C while Chl-a varied from 0.04 to 6.09 μg L^?1. During the course of the study period, there was a weak correlation (r?= 0.32) between SST and Chl-a statistically. MSP biomass varied from 0.42 to 9.63 mg C m^?3 and inversely related with SST. Two kinds of approaches were adopted to develop the model by grouping seasonal datasets (four seasonal algorithms) and comprising all datasets (one annual algorithm). Among the four functions used (linear, paraboloid, the Lorentzian and the Gaussian functions), paraboloid model was best suited. The best seasonal and annual algorithms were applied in the synchronous MODIS-derived SST and Chl-a data to estimate the MSP biomass in the southwestern BoB. The modelled MSP biomass was validated with field MSP biomass and the result was statistically significant, showing maximum regression coefficient for the seasonal algorithms (R²?=?0.60; p?=?0.627; α?= 0.05), than the annual algorithm (R²?=?0.52; p?=?0.015, α?=?0.05).     

Soil tillage erosion estimated by using magnetism of soils—a case study from Bulgaria

A detailed field and laboratory study on small 0.84-ha test site of agricultural land near Sofia (Bulgaria) has been carried out in order to test the applicability of magnetic methods in soil erosion estimation in the particular case of strongly magnetic parent material. Field measurements of magnetic susceptibility were carried out with grid size of 6 m, resulting in 258 data points. Bulk soil material was gathered from 78 grid points. Natural, non-disturbed soil section was sampled near the agricultural field for reference profile of complete undisturbed soil. Surface susceptibility measurements reveal well-defined maxima down slope which, however, cannot be assigned directly to a certain depth interval, corresponding with susceptibilities along the non-disturbed soil profile. This is caused by the high magnetic susceptibility of the lithogenic coarse-grained magnetic fraction. Non-uniqueness is resolved by using magnetic susceptibility of coarse (1 mm >?d?> 63 μm) and fine (d < 63 μm) mechanical fractions and the parameter Δχ = 100*(χ _coarse???χ _fine)/χ _bulk (%). It shows increased values in the C-horizon of undisturbed soil profile, which corresponds to a certain part of the studied area. After the application of an empirical model to predict the values of magnetic parameter after tillage homogenization and removal of soil material from the surface, the amount of soil loss is estimated.     

<Emphasis Type="Italic">Synechococcus</Emphasis> production and grazing loss rates in nearshore tropical waters

Temporal variation of Synechococcus, its production (μ) and grazing loss (g) rates were studied for 2 years at nearshore stations, i.e. Port Dickson and Port Klang along the Straits of Malacca. Synechococcus abundance at Port Dickson (0.3–2.3 × 10⁵ cell ml^?1) was always higher than at Port Klang (0.3–7.1 × 10⁴ cell ml^?1) (p < 0.001). μ ranged up to 0.98 day^?1 (0.51 ± 0.29 day^?1), while g ranged from 0.02 to 0.31 day^?1 (0.15 ± 0.07 day^?1) at Port Klang. At Port Dickson, μ and g averaged 0.47 ± 0.13 day^?1 (0.29–0.82 day^?1) and 0.31 ± 0.14 day^?1 (0.13–0.63 day^?1), respectively. Synechococcus abundance did not correlate with temperature (p > 0.25), but nutrient and light availability were important factors for their distribution. The relationship was modelled as log Synechococcus = 0.37Secchi ? 0.01DIN + 4.52 where light availability (as Secchi disc depth) was a more important determinant. From a two-factorial experiment, nutrients were not significant for Synechococcus growth as in situ nutrient concentrations exceeded the threshold for saturated growth. However, light availability was important and elevated Synechococcus growth rates especially at Port Dickson (F = 5.94, p < 0.05). As for grazing loss rates, they were independent of either nutrients or light intensity (p > 0.30). In nearshore tropical waters, an estimated 69 % of Synechococcus production could be grazed.     

Dynamic extreme values modeling and monitoring by means of sea shores water quality biomarkers and valvometry

Water quality can be evaluated using biomarkers such as tissular enzymatic activities of endemic species. Measurement of molluscs bivalves activity at high frequency (e.g., valvometry) during a long time period is another way to record the animal behavior and to evaluate perturbations of the water quality in real time. As the pollution affects the activity of oysters, we consider the valves opening and closing velocities to monitor the water quality assessment. We propose to model the huge volume of velocity data collected in the framework of valvometry using a new nonparametric extreme values statistical model. The objective is to estimate the tail probabilities and the extreme quantiles of the distribution of valve closing velocity. The tail of the distribution function of valve closing velocity is modeled by a Pareto distribution with parameter ??_t,τ, beyond a threshold τ according to the time t of the experiment. Our modeling approach reveals the dependence between the specific activity of two enzymatic biomarkers (Glutathione-S-transferase and acetylcholinesterase) and the continuous recording of oyster valve velocity, proving the suitability of this tool for water quality assessment. Thus, valvometry allows in real-time in situ analysis of the bivalves behavior and appears as an effective early warning tool in ecological risk assessment and marine environment monitoring.     

Assessment of multi-contaminant exposure in a cancer treatment center: a 2-year monitoring of molds,mycotoxins, endotoxins,and glucans in bioaerosols

Indoor air quality in health care facilities is a major public health concern, particularly for immunocompromised patients who may be exposed to microbiological contaminants such as molds, mycotoxins, endotoxins, and (1,3)-ß-D-glucans. Over 2 years, bioaerosols were collected on a monthly basis in a cancer treatment center (Centre F. Baclesse, Normandy, France), characterized from areas where there was no any particular air treatment. Results showed the complexity of mycoflora in bioaerosols with more than 100 fungal species identified. A list of major strains in hospital environments could be put forward due to the frequency, the concentration level, and/or the capacity to produce mycotoxins in vitro: Aspergillus fumigatus, Aspergillus melleus, Aspergillus niger, Aspergillus versicolor, Cladosporium herbarum, Purpureocillium lilacinum, and Penicillium brevicompactum. The mean levels of viable airborne fungal particles were less than 30.530 CFU per m³ of air and were correlated to the total number of 0.30 to 20 μm particles. Seasonal variations were observed with fungal particle peaks during the summer and autumn. Statistical analysis showed that airborne fungal particle levels depended on the relative humidity level which could be a useful indicator of fungal contamination. Finally, the exposure to airborne mycotoxins was very low (only 3 positive samples), and no mutagenic activity was found in bioaerosols. Nevertheless, some fungal strains such as Aspergillus versicolor or Penicillium brevicompactum showed toxigenic potential in vitro.     

Relative proportions of <Emphasis Type="Italic">E. coli</Emphasis> and <Emphasis Type="Italic">Enterococcus spp.</Emphasis> may be a good indicator of potential health risks associated with the use of roof harvested rainwater stored in tanks

A total of 285 water samples were collected from 71 roof harvested rainwater tanks from four villages in different provinces over a two-year (2013–2014) period during the early (October to December) and late (January to March) rainy season. Water quality was evaluated based on Escherichia coli, faecal coliforms and Enterococcus spp. prevalence using the IDEXX Quanti-Tray quantification system. Real-Time PCR was used to analyse a subset of 168 samples for the presence of Shigella spp., Salmonella spp. and E. coli virulence genes (stx1, stx2 and eaeA). Escherichia coli were detected in 44.1% of the samples, Enterococcus spp. in 57.9% and faecal coliforms in 95.7%. The most prevalent E. coli concentrations in harvested rainwater were observed in 29.1% of samples and 22.5% for Enterococcus spp. and, were within 1–10 cfu/100 ml and 10–100 cfu/100 ml, respectively, whereas those for faecal coliforms (36.6%) were within 100–1000 cfu/100 ml. On average 16.8% of the samples had neither E. coli nor Enterococcus spp. detected, while 33.9% had only Enterococcus spp. and 23.7% had only E. coli. E. coli and Enterococcus spp. were detected together in 25.5% of the samples. Evaluation of samples for potential pathogenic bacteria showed all tested samples to be negative for the Shigella spp. ipaH gene, while five tested positive for Salmonella ipaB gene. None of the samples tested positive for the stx1 and stx2 genes, and only two tested positive for the eaeA gene. These findings are potentially useful in the development of a simplified risk assessment strategy based on the concentrations of indicator bacteria.     

HPLC-FLD determination of 4-nonylphenol and 4-<Emphasis Type="Italic">tert</Emphasis>-octylphenol in surface water samples

A simple, sensitive and reliable HPLC-FLD method for the routine determination of 4-nonylphenol, 4-NP and 4-tert-octylphenol, 4-t-OP content in water samples was developed. The method consists in a liquid–liquid extraction of the target analytes with dichloromethane at pH  3.0–3.5 followed by the HPLC-FLD analysis of the organic extract using a Zorbax Eclipse XDB C8 column, isocratic elution with a mixed solvent acetonitrile/water 65:35, at a flow rate of 1.0 mL/min and applying a column temperature of 40°C. The method was validated and then applied with good results for the determination of 4-NP and 4-t-OP in Ialomi?a River water samples collected each month during 2006. The concentration levels of 4-NP and 4-t-OP vary between 0.08–0.17 μg/L with higher values of 0.24–0.37 μg/L in the summer months for 4-NP, and frequently <0.05 μg/L but also between 0.06–0.09 μg/L with higher values of 0.12–0.16 μg/L in July and August for 4-t-OP and were strongly influenced by sesonial and anthropic factors. The method was also applied on samples collected over 2 years 2007 and 2008 from urban wastewaters discharged into sewage or directly into the rivers by economic agents located in 30 Romanian towns. Good results were obtained when the method was used for analysis of effluents discharged into surface waters by 16 municipal wastewater treatment plants, during the year 2008.     

<Emphasis Type="Italic">Mazzaella laminarioides</Emphasis> and <Emphasis Type="Italic">Sarcothalia crispata</Emphasis> as possible bioindicators of heavy metal contamination in the marine coastal zone of Chile

The suitability of Mazzaella laminarioides and Sarcothalia crispata as heavy metal biomonitors of Cd, Cu, Hg, Pb, and Zn was assessed by comparing bioaccumulation of these elements in different life stages and frond sizes in samples from three locations, San Vicente Bay (industrial area), Coliumo, and Quidico (the latter as a reference station), where different degrees of heavy metal pollution are recorded. Bioaccumulation and bioconcentration factors of Cd, Cu, Hg, Pb, and Zn were evaluated. The two macroalgae species showed similar patterns, with higher values of Cu, Hg, Pb, and Zn in polluted areas. M. laminarioides bioaccumulated higher concentrations of all metals assessed than S. crispata, independent of life stage and frond size. The results also showed significantly higher Cu, Hg, Pb, and Zn concentrations (p < 0.05) in water samples from San Vicente Bay than those measured in Coliumo and Quidico. Concentrations of Cd, Hg, Pb, and Zn in San Vicente Bay and Cd, Hg, and Pb in Coliumo and Quidico exceed the mean values considered to represent natural concentrations (Cu = 3.00 μg L^?1; Zn = 5.00 μg L^?1; Pb = 0.03 μg L^?1; Cd = 0.05 μg L^?1; Hg = 0.05 μg L^?1); however, the concentrations recorded do not cause negative effects on the growth and survival of macroalgae. The assessment of heavy metals bioaccumulated in M. laminarioides and S. crispata, particularly Hg, Pb, and Zn, offers a reliable approach for pollution assessment in rocky intertidal environments. Cu and Cd concentrations in seawater samples from San Vicente and Coliumo Bays were significantly higher than in those from Quidico (p value < 0.05); no significant differences in Cd concentrations were observed between San Vicente and Coliumo Bays (p < 0.05). Exceptionally, Cd is bioaccumulated at high levels independent of its availability in the water, thus reaching high concentrations in control areas. High concentrations of metals like Cu and Zn may limit or inhibit Cd uptake in macroalgae, since the transport channels are saturated by some metals, reducing the accumulation of others. These macroalgae species offer good potential for the development of suitable heavy metal pollution survey tools in rocky intertidal environments.     

Organismic-level acute toxicology profiling of reactive azo dyes

In the present study, organismic-level acute toxicology profile of three reactive azo dyes, viz. Reactive Blue 221, Reactive Red 195, and Reactive Yellow 145, was investigated, by using bacterial (Pseudomonas aeruginosa, Escherichia coli, Klebsiella pneumoniae, Staphylococcus aureus, Listeria monocytogenes, and Bacillus subtilis), fungal (Trichoderma asperellum, Aspergillus flavus, Fusarium fujikuroi, and Rhizoctonia solani), plant (Raphanus sativus, Triticum aestivum, Sorghum bicolor, and Phaseolus mungo), and aquatic (Artemia salina and Daphnia magna) specimens. Microbial test organisms (all the six bacteria and two fungi, i.e., T. asperellum and A. flavus) and D. magna were found to be relatively more sensitive towards the reactive azo dyes and their mixture, as the EC50 values were in the range of 80–330, 135–360, and 108–242 ppm for bacteria, fungi, and D. magna, respectively (but the effect was not acutely toxic). Moreover, the effect of dye mixture was comparable tothe individual dyes in almost all the tested microbial specimens. For plant seeds, the dye mixture was found to be relatively more inhibitory towards T. aestivum and R. sativus than the individual dyes. For S. bicolor and P. mungo seeds, the effect of the dye mixture was almost identical to the individual dyes. However, in all cases, EC50 values were in the range of 950–3500 ppm, which indicates a non-toxic effect on plant seed germination potential. Likewise, the dyes and their mixture were not acutely toxic for Artemia salina larvae (more sensitive to the dye mixture) and Daphnia magna neonates (EC50, 516–950 and 108–242 ppm, respectively).     

Diversity of crude oil-degrading bacteria and alkane hydroxylase (<Emphasis Type="Italic">alkB</Emphasis>) genes from the Qinghai-Tibet Plateau

The aim of this study was to survey the response of the microbial community to crude oil and the diversity of alkane hydroxylase (alkB) genes in soil samples from the Qinghai-Tibet Plateau (QTP). The enrichment cultures and clone libraries were used. Finally, 53 isolates and 94 alkB sequences were obtained from 10 pristine soil samples after enrichment at 10 °C with crude oil as sole carbon source. The isolates fell into the phyla Proteobacteria, Actinobacteria, and Bacteroidetes, with the dominance of Pseudomonas and Acinetobacter. The composition of degraders was different from polar habitats where Acinetobacter sp. is not a predominant responder of alkane degradative microbial communities. Phylogenetic analysis showed that the alkB genes from isolates and enrichment communities formed eight clusters and mainly related with alkB genes of Pseudomonas, Rhodococcus, and Acinetobacter. The alkB gene diversity in the QTP was lower than marine environments and polar soil samples. In particular, a total of 10 isolates exhibiting vigorous growth with crude oil could detect no crude oil degradation-related gene sequences, such as alkB, P450, almA, ndoB, and xylE genes. The Shannon-Wiener index of the alkB clone libraries from the QTP ranged from 1.00 to 2.24 which is similar with polar pristine soil samples but lower than that of contaminated soils. These results indicated that the Pseudomonas, Acinetobacter, and Rhodococcus genera are the candidate for in situ bioremediation, and the environment of QTP may be still relatively uncontaminated by crude oil.     

Stochastic modeling approaches based on neural network and linear–nonlinear regression techniques for the determination of single droplet collection efficiency of countercurrent spray towers

This paper presents a new mathematical model and a two-layer neural network approach to predict the single droplet collection efficiency (SDCE), η _d, of countercurrent spray towers. SDCE values were calculated using MATLAB^® algorithm for 205 different artificial scenarios given in a large range of operating conditions. Theoretical results were compared with outputs obtained from a two-layer neural network and DataFit^® scientific software. The predicted model developed from linear–nonlinear regression analysis and network outputs agreed with the theoretical data, and all predictions proved to be satisfactory with a correlation coefficient of about 0.921 and 0.99, respectively. By using the proposed model, iterations between Reynolds number (Re), drag coefficient (C _D) and terminal velocity values (v _T) were neglected for a large range of operating conditions. SDCE values were also obtained speedily and practically for five main operating inputs used in the model.