1,928 research outputs found

    Laboratory protocols for testing the efficacy of commercial pit latrine additives

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    There is considerable national interest in the use of commercial microbially derived products for controlling the rate of accumulation of the contents of pit latrines. Manufacturers claim that some of these products can reduce accumulation rates, prevent the pit from ever filling up, or even result in decreases in pit contents volume. Prior to this research, there have been no scientific publications that have conclusively supported or refuted these claims.This project undertook to perform reproducible laboratory tests that would quantify the effect of commercial pit latrine additive products. Protocols were developed and tested on a range of different commercial products sold for their ability to control the rate of accumulation of pit latrine contents. The effect of commercial additives on mass loss from VIP sludge in 300 g honey jars was compared to mass loss from similar units subjected to no treatment and treatment with water.The purpose of these experiments was to separate and quantify the effect of micro-organisms or enzymes originating from commercial pit latrine additives from the effect of natural processes within the pit latrine sludge (including digestion by micro-organisms in the VIP sludge and dehydration) and the effects of other actions associated with treatment, such as the addition of water.Results indicated that insignificant mass loss occurred in all anaerobic test units, while significant mass loss occurred in all other test units. However, there was no statistically significant difference between any of the different treatments in the aerobic units. Investigation of analytical data from the test units indicated that mass loss in aerobic units was due to a combination of dehydration through evaporation of moisture and biological stabilisation processes, and that the latter were not significantly enhanced by the addition of commercial pit latrine products. It was concluded that there was no evidence to support claims that pit latrine additives could extend the life of a pit latrine

    An investigation of the effect of pit latrine additives on VIP latrine sludge content under laboratory and field trials

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    Sludge content in VIP latrines is degraded mainly under anaerobic conditions and the process is relatively slow. At varying stages of digestion within pit latrines, sludge accumulates and odour and fly nuisance may occur which could pose risks to public health and the environment. Management of accumulated sludge in pit latrines has been a major problem facing a number of municipalities in South Africa and is also a global issue. Manufacturers of various commercial pit latrine additives claim that by addition of this product to pit content, accumulation rate and pit content volume can be reduced, thereby preventing the pit from ever reaching capacity. This paper presents a comprehensive study conducted to determine the effects of additives on pit contents under laboratory and field conditions. By conducting both laboratory and field trials, it was possible to identify whether there is any acceleration of mass or volume stabilisation as a result of additive addition, and whether any apparent effect is a result of biodegradation or of compaction. The results indicated that neither laboratory trials nor field trials provided any evidence that the use of pit additives has any beneficial effect on pit contents. The reasons why additives seem to not have any beneficial effects are also discussed.Keywords: additives, digestion, pit content, sludge, public health, VIP latrin

    Variation in VIP latrine sludge contents

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    This study investigated variations in the characteristics of the sludge content from different ventilated improved pit (VIP) latrines and variation in these characteristics at specific depths within each pit. Faecal sludge from 16 VIP latrines within the eThekwini Municipality was collected and laboratory characterisation including moisture content, total and volatile solids, chemical oxygen demand, and aerobic biodegradability was performed. Sludge samples were collected from 4 specific depths within each pit investigated. The laboratory characterisation performed showed that none of the VIP latrines investigated had the same sludge characteristics, and that within a pit sludge characteristics varied with increasing depth in the pit. This supports the motivating hypothesis that, depending on household habits and local environmental conditions, there should be considerable variation in the organic contents, moisture content, non-biodegradable content and microbial population between different pits. This variation with increasing depth within a pit is expected, since fresh material is constantly being added to the pit overlaying older material which might have undergone a certain degree of stabilisation

    Simulation of a wastewater treatment plant receiving industrial effluents

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    A process model simulating the Mariannridge Wastewater Treatment Plant, located in the eThekwini Municipality, has been developed in the WEST (Worldwide Engine for Simulation, Training and Automation) modelling environment, based on the IWA Activated Sludge Model No. 3 (ASM3). The treatment plant receives a high proportion of industrial effluents.The development of the model involves the characterisation of the influent wastewater and determining model parameters (kinetic and stoichiometric coefficients) by undertaking batch respirometric tests on the wastewater and activated sludge, flocculation filtration and simulation of the batch respirometric experiment. To account for equipment-specific factors, thesimulation model was calibrated against plant data covering a year’s operation. The model is intended to be used as part of a system to evaluate the ability of a receiving wastewater treatment works to adequately treat a particular industrial effluent before granting a permit for it to be discharged to sewer

    The Maximal U(1)LU(1)_L Inverse Seesaw from d=5d=5 Operator and Oscillating Asymmetric Sneutrino Dark Matter

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    The maximal U(1)LU(1)_L supersymmetric inverse seesaw mechanism (MLLSIS) provides a natural way to relate asymmetric dark matter (ADM) with neutrino physics. In this paper we point out that, MLLSIS is a natural outcome if one dynamically realizes the inverse seesaw mechanism in the next-to minimal supersymmetric standard model (NMSSM) via the dimension-five operator (N)2S2/M(N)^2S^2/M_*, with SS the NMSSM singlet developing TeV scale VEV; it slightly violates lepton number due to the suppression by the fundamental scale MM_*, thus preserving U(1)LU(1)_L maximally. The resulting sneutrino is a distinguishable ADM candidate, oscillating and favored to have weak scale mass. A fairly large annihilating cross section of such a heavy ADM is available due to the presence of singlet.Comment: journal versio

    Integrating physiological threshold experiments with climate modeling to project mangrove species’ range expansion

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    Predictions of climate-related shifts in species ranges have largely been based on correlative models. Due to limitations of these models, there is a need for more integration of experimental approaches when studying impacts of climate change on species distributions. Here, we used controlled experiments to identify physiological thresholds that control poleward range limits of three species of mangroves found in North America. We found that all three species exhibited a threshold response to extreme cold, but freeze tolerance thresholds varied among species. From these experiments, we developed a climate metric, freeze degree days (FDD), which incorporates both the intensity and the frequency of freezes. When included in distribution models, FDD accurately predicted mangrove presence/absence. Using 28 years of satellite imagery, we linked FDD to observed changes in mangrove abundance in Florida, further exemplifying the importance of extreme cold. We then used downscaled climate projections of FDD to project that these range limits will move northward by 2.2–3.2 km yr⁻¹ over the next 50 years

    Shannon and Renyi Entropies to Classify Effects of Mild Traumatic Brain Injury on Postural Sway

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    Background: Mild Traumatic Brain Injury (mTBI) has been identified as a major public and military health concern both in the United States and worldwide. Characterizing the effects of mTBI on postural sway could be an important tool for assessing recovery from the injury. Methodology/Principal Findings: We assess postural sway by motion of the center of pressure (COP). Methods for data reduction include calculation of area of COP and fractal analysis of COP motion time courses. We found that fractal scaling appears applicable to sway power above about 0.5 Hz, thus fractal characterization is only quantifying the secondary effects (a small fraction of total power) in the sway time series, and is not effective in quantifying long-term effects of mTBI on postural sway. We also found that the area of COP sensitively depends on the length of data series over which the COP is obtained. These weaknesses motivated us to use instead Shannon and Renyi entropies to assess postural instability following mTBI. These entropy measures have a number of appealing properties, including capacity for determination of the optimal length of the time series for analysis and a new interpretation of the area of COP. Conclusions: Entropy analysis can readily detect postural instability in athletes at least 10 days post-concussion so that it appears promising as a sensitive measure of effects of mTBI on postural sway

    A two-phase flow model to simulate mold filling and saturation in Resin Transfer Molding

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    The final publication is available at Springer via http://dx.doi.org/10.1007/s12289-015-1225-zThis paper addresses the numerical simulation of void formation and transport during mold filling in Resin Transfer Molding (RTM). The saturation equation, based on a two-phase flow model resin/air, is coupled with Darcy s law and mass conservation to simulate the unsaturated filling flow that takes place in a RTM mold when resin is injected through the fiber bed. These equations lead to a system composed of an advection diffusion equation for saturation including capillary effects and an elliptic equation for pressure taking into account the effect of air residual saturation. The model introduces the relative permeability as a function of resin saturation. When capillary effects are omitted, the hyperbolic nature of the saturation equation and its strong coupling with Darcy equation through relative permeability represent a challenging numerical issue. The combination of the constitutive physical laws relating permeability to saturation with the coupled system of the pressure and saturation equations allows predicting the saturation profiles. The model was validated by comparison with experimental data obtained for a fiberglass reinforcement injected in a RTM mold at constant flow rate. The saturation measured as a function of time during the resin impregnation of the fiber bed compared very well with numerical predictions.The authors acknowledge financial support of the Spanish Government (Projects DPI2010-20333 and DPI2013-44903-R-AR), of the National Science and Research Council of Canada (NSERC) and of the Canada Reseach Chair (CRC) program.Gascón Martínez, ML.; García Manrique, JA.; Lebel, F.; Ruiz, E.; Trochu, F. (2016). A two-phase flow model to simulate mold filling and saturation in Resin Transfer Molding. 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    Semi-automated non-target processing in GC × GC–MS metabolomics analysis: applicability for biomedical studies

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    Due to the complexity of typical metabolomics samples and the many steps required to obtain quantitative data in GC × GC–MS consisting of deconvolution, peak picking, peak merging, and integration, the unbiased non-target quantification of GC × GC–MS data still poses a major challenge in metabolomics analysis. The feasibility of using commercially available software for non-target processing of GC × GC–MS data was assessed. For this purpose a set of mouse liver samples (24 study samples and five quality control (QC) samples prepared from the study samples) were measured with GC × GC–MS and GC–MS to study the development and progression of insulin resistance, a primary characteristic of diabetes type 2. A total of 170 and 691 peaks were quantified in, respectively, the GC–MS and GC × GC–MS data for all study and QC samples. The quantitative results for the QC samples were compared to assess the quality of semi-automated GC × GC–MS processing compared to targeted GC–MS processing which involved time-consuming manual correction of all wrongly integrated metabolites and was considered as golden standard. The relative standard deviations (RSDs) obtained with GC × GC–MS were somewhat higher than with GC–MS, due to less accurate processing. Still, the biological information in the study samples was preserved and the added value of GC × GC–MS was demonstrated; many additional candidate biomarkers were found with GC × GC–MS compared to GC–MS
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