Analysis of pollution removal from wastewater by Ceratophyllum demersum

Water is one of the most stable and abundant complexes on nature that can be polluted with natural and human factors. Polluted water is harmful to human health and need to purify. One of the economic and rapid methods for elements removal is displacement of metals by biosorption. Two treatments in four replications for the purpose of purifying wastewater by Ceratophyllum demersum were designed. The treatments included raw municipal wastewater (RMW) and treated municipal wastewater (TMW). The experiment was performed at the open air of Khorasgan University area for 18 days without aeration. Result of the COD indicated that the COD of RMW and TMW were decreased from 664 to 152.75 mg/l and 260 to 64.5 mg/l, respectively. Also, this investigation demonstrated that the amount of ammonium in RMW and TMW decreased from135 to 15 meq/l and 90 to 10 meq/l, respectively. The amount of nitrate in RMW and TMW had a similar decreased from 60 to 30 meq/l as well as 4.48 to 0.53 meq/l, respectively and the amount of phosphorous in RMW and TMW declined from 13.68 to 1.15 meq/l and 4.48 to 0.53 meq/l, respectively. It could be concluded from these results that a significant amount of these macro elements were absorbed by C. demersum. The other factor that was measured in this study was the electrical conductivity (EC). Results of this factor indicated that the EC of treated municipal wastewater (from 1.34 to 0.95 ds/m) and the EC of raw municipal wastewater (from 2.68 to 2.12 ds/m) were reduced. The variation for NH4, NO3, COD and EC were < 5%. Therefore it was concluded that C. demersum can be used for refining wastewater

Subarachnoid haemorrhage secondary to traumatic intracranial aneurysm of the posterior cerebral circulation: case series and literature review

Background To identify the clinical features, rebleed risk, timing and method of diagnosis, complications and outcome for subarachnoid haemorrhage (SAH) from traumatic intracranial aneurysm (TICA) of the posterior circulation. Subjects included 26 patients aged 3–54 (mean 24.8). Methods Case series and literature search to identify all reported cases. Results In our series, two of three cases were fatal as a result of rebleed, and one case had a good outcome with no deficit, following prompt diagnosis and embolisation. Our key findings from the literature review were: 30.7 % of patients were age 16 and under; 88 % had an acute drop in consciousness, 46 % in a delayed manner; the mean time to diagnosis was 7.5 days; initial cerebrovascular imaging was normal in 23 %; the rebleed rate was 23 %; 61 % required emergency diversion of cerebrospinal fluid; 11 % developed vasospasm requiring treatment; 19.2 % had deficits that rendered them unable to live independently. The mortality rate was 27 %. Conclusions SAH from ruptured posterior circulation TICA is associated with significant morbidity and mortality. A high index of suspicion as well as prompt diagnosis, repeat imaging in selected cases, and treatment of any associated TICA can be crucial to a favourable outcome

Automatic Frame Selection Using MLP Neural Network in Ultrasound Elastography

Ultrasound elastography estimates the mechanical properties of the tissue from two Radio-Frequency (RF) frames collected before and after tissue deformation due to an external or internal force. This work focuses on strain imaging in quasi-static elastography, where the tissue undergoes slow deformations and strain images are estimated as a surrogate for elasticity modulus. The quality of the strain image depends heavily on the underlying deformation, and even the best strain estimation algorithms cannot estimate a good strain image if the underlying deformation is not suitable. Herein, we introduce a new method for tracking the RF frames and selecting automatically the best possible pair. We achieve this by decomposing the axial displacement image into a linear combination of principal components (which are calculated offline) multiplied by their corresponding weights. We then use the calculated weights as the input feature vector to a multi-layer perceptron (MLP) classifier. The output is a binary decision, either 1 which refers to good frames, or 0 which refers to bad frames. Our MLP model is trained on in-vivo dataset and tested on different datasets of both in-vivo and phantom data. Results show that by using our technique, we would be able to achieve higher quality strain images compared to the traditional methods of picking up pairs that are 1, 2 or 3 frames apart. The training phase of our algorithm is computationally expensive and takes few hours, but it is only done once. The testing phase chooses the optimal pair of frames in only 1.9 ms

Application of PLGA nano/microparticle delivery systems for immunomodulation and prevention of allotransplant rejection

Introduction: Allograft transplantation is an effective end-point therapy to replace the function of an impaired organ. The main problem associated with allotransplantation is the induction of immune responses that results in acute and chronic graft rejection. To modulate the response of the immune system, transplant recipients generally take high dose immunosuppressant drugs for life. These drugs are associated with serious side effects such as infection with opportunistic pathogens and the development of neoplasia. Areas covered: We reviewed the obstacles to successful transplantation and PLGA-based strategies to reduce immune-mediated allograft rejection. Expert opinion: Biomaterial-based approaches using micro- and nanoparticles such as poly (lactic-co-glycolic acid) (PLGA) can be used to achieve controlled release of drugs. This approach decreases the required effective dose of drugs and enables local delivery of these agents to specific tissues and cells, whilst decreasing systemic effects

Estimation of mechanical property degradation of poly(lactic acid) and flax fibre reinforced poly(lactic acid) bio-composites during thermal processing

Thermal degradation and chemical degradation are among the key issues affecting mechanical properties and ultimately utilization of natural fibre reinforced polymer (NFRP) bio-composites. In our previous work, mathematical models were used to identify thermal processing boundaries and to recognize an optimized window for NFRP bio-composites. In this study, a correlation relating the tensile strength of flax/PLA bio-composite to the processing temperature history is proposed. For the first time, an existing linear model, which corresponds to the tensile strength of natural polymers and their degree of polymerization, has been combined with reaction kinetics to predict the tensile strength of NFRP bio-composites as a function of processing temperature history. In addition, a non-linear model has been proposed which shows a significant improvement for longer periods of time, compared with the linear model. The model is based on the underlying thermo-chemical degradation processes occurring during manufacture of NFRP bio-composites. The model is capable of predicting the tensile strength of the bio-composite within 10% error

Polarimetry of 16Ngs produced in mu --capture on 16O nuclei

A polarimetry technique based on stack targets and /3-'/-coincidences has been applied to the 16N nuclei produced in the ground state capture of negative muons on lb0 nuclei. The performance of the polarimeter and the first measurements of /3-asymmetry due to the longitudinal nuclear polarization are discussed

Treatment of fecal impaction in children using combined polyethylene glycol and sodium picosulphate

Background and Aim: Polyethylene glycol (PEG) is the gold standard for fecal disimpaction in constipation. A regimen of PEG combined with the stimulant laxative sodium picosulphate (SPS) produced fecal disimpaction in chronically constipated children in the community, but it is unknown if it is effective for more severe constipation. To determine the stool output and effect of a combined PEG and SPS regimen on fecaloma in children with severe constipation and impaction. Methods: Children with symptoms for a duration of >= 2 years, a palpable fecaloma, and enlarged rectum on X-ray (rectal: pelvic ratio > 0.6) were recruited from a tertiary hospital. Daily diaries recorded laxative dose, stool frequency, volume, and consistency (Bristol stool scale, BSS). Abdominal X-rays were taken on day 1 and day 8, and stool loading was assessed using the Leech score. Laxative doses were based on the child's age. The dose of PEG with electrolytes taken was 2-8 sachets (14.7 g/sachet) on days 1-2, reducing to 2-6 sachets on day 3. The SPS dose was 15-20 drops on days 2-3. Results: Eighty-nine children (4-18 years) produced a large volume of soft stool (median/inter-quartile-range: 2.2/1.6-3.1 L) over 7 days. Stool volume on X-rays decreased significantly in the colon (P <0.001). Fecalomas resolved in 40 of 89 children, while 49 needed a second high dose. Rectal: pelvic ratios did not change. Conclusions: A combined high dose of PEG and SPS on days 1 and 2 was effective in removing the fecaloma in half of the children. Administering high doses for a longer period should be tested to provide outpatient disimpaction for severe fecalomas. Rectums remained flaccid after emptying

Detection of regulator genes and eQTLs in gene networks

Genetic differences between individuals associated to quantitative phenotypic traits, including disease states, are usually found in non-coding genomic regions. These genetic variants are often also associated to differences in expression levels of nearby genes (they are "expression quantitative trait loci" or eQTLs for short) and presumably play a gene regulatory role, affecting the status of molecular networks of interacting genes, proteins and metabolites. Computational systems biology approaches to reconstruct causal gene networks from large-scale omics data have therefore become essential to understand the structure of networks controlled by eQTLs together with other regulatory genes, and to generate detailed hypotheses about the molecular mechanisms that lead from genotype to phenotype. Here we review the main analytical methods and softwares to identify eQTLs and their associated genes, to reconstruct co-expression networks and modules, to reconstruct causal Bayesian gene and module networks, and to validate predicted networks in silico.Comment: minor revision with typos corrected; review article; 24 pages, 2 figure

Electric field-modulated non-ohmic behavior of carbon nanotube fibers in polar liquids.

We report a previously unseen non-ohmic effect in which the resistivity of carbon nanotube fibers immersed in polar liquids is modulated by the applied electric field. This behavior depends on the surface energy, dielectric constant, and viscosity of the immersion media. Supported by synchrotron SAXS and impedance spectroscopy, we propose a model in which the gap distance, and thus the conductance, of capacitive interbundle junctions is controlled by the applied field.JT acknowledges generous financial support from: The Cambridge Commonwealth European and International Trust, CONACyT (Mexico), Dyson Ltd, and Pembroke College Cambridge. JJV acknowledges support from MINECO (Spain) and FP7-People-Marie Curie Action-CIG.This is the accepted manuscript. The final version is available from ACS at http://pubs.acs.org/doi/abs/10.1021/nn5030835