Analysis of Nitrogen Loading Reductions for Wastewater Treatment Facilities and Non-Point Sources in the Great Bay Estuary Watershed

In 2009, the New Hampshire Department of Environmental Services (DES) published a proposal for numeric nutrient criteria for the Great Bay Estuary. The report found that total nitrogen concentrations in most of the estuary needed to be less than 0.3 mg N/L to prevent loss of eelgrass habitat and less than 0.45 mg N/L to prevent occurrences of low dissolved oxygen. Based on these criteria and an analysis of a compilation of data from at least seven different sources, DES concluded that 11 of the 18 subestuaries in the Great Bay Estuary were impaired for nitrogen. Under the Clean Water Act, if a water body is determined to be impaired, a study must be completed to determine the existing loads of the pollutant and the load reductions that would be needed to meet the water quality standard. Therefore, DES developed models to determine existing nitrogen loads and nitrogen loading thresholds for the subestuaries to comply with the numeric nutrient criteria. DES also evaluated the effects of different permitting scenarios for wastewater treatment facilities on nitrogen loads and the costs for wastewater treatment facility upgrades. This modeling exercise showed that: Nitrogen loads to the Great Bay, Little Bay, and the Upper Piscataqua River need to be reduced by 30 to 45 percent to attain the numeric nutrient criteria. Both wastewater treatment facilities and non-point sources will need to reduce nitrogen loads to attain the numeric nutrient criteria. The percent reduction targets for nitrogen loads only change minimally between wet and dry years. Wastewater treatment facility upgrades to remove nitrogen will be costly; however, the average cost per pound of nitrogen removed from the estuary due to wastewater facility upgrades is lower than for non-point source controls. The permitting options for some wastewater treatment facilities will be limited by requirements to not increase pollutant loads to impaired waterbodies. The numeric nutrient criteria and models used by DES are sufficiently accurate for calculating nitrogen loading thresholds for the Great Bay watershed. Additional monitoring and modeling is needed to better characterize conditions and nitrogen loading thresholds for the Lower Piscataqua River. This nitrogen loading analysis for Great Bay may provide a framework for setting nitrogen permit limits for wastewater treatment facilities and developing watershed implementation plans to reduce nitrogen loads

Great Bay Nitrogen Non-Point Source Study

The Great Bay Estuary is 21 square miles of tidal waters located in southeastern New Hampshire. It is one of 28 “estuaries of national significance” established under the Environmental Protection Agency’s National Estuary Program. The estuary is experiencing the signs of eutrophication, specifically, low dissolved oxygen, macroalgae blooms, and declining eelgrass habitat (DES, 2012). Sixty-eight percent of the nitrogen that ends up in the Great Bay Estuary originates from sources spread across the watershed; the remainder derives from direct discharges of municipal wastewater treatment facilities (DES, 2010; PREP, 2013). In this report, these sources of nitrogen are called non-point sources and consist of atmospheric deposition, fertilizers, human waste disposed into septic systems, and animal waste. The purpose of this study is to determine how much nitrogen each non-point source type contributes to the estuary. The nitrogen loads from municipal wastewater treatment facilities have been reported elsewhere (DES, 2010; PREP, 2012; PREP, 2013) and, therefore, are not included in this study except to provide context. The intended use of this study is for planning purposes, and is not meant for regulatory allocations or specific reduction requirements. The results of the model may be useful for towns or watershed groups for prioritizing nitrogen reduction efforts or as a starting point for more detailed studies of non-point sources. However, more detailed inventories of non-point sources will be needed to track the effects of nitrogen reduction efforts in smaller areas. In addition, the model makes no conclusions about the benefits of nitrogen reductions to receiving waters or overall estuarine health

Influence of Lipid Heterogeneity and Phase Behavior on Phospholipase A2 Action at the Single Molecule Level

We monitored the action of phospholipase A2 (PLA2) on L- and D-dipalmitoylphosphatidylcholine (DPPC) Langmuir monolayers by mounting a Langmuir-trough on a wide-field fluorescence microscope with single molecule sensitivity. This made it possible to directly visualize the activity and diffusion behavior of single PLA2 molecules in a heterogeneous lipid environment during active hydrolysis. The experiments showed that enzyme molecules adsorbed and interacted almost exclusively with the fluid region of the DPPC monolayers. Domains of gel state L-DPPC were degraded exclusively from the gel-fluid interface where the build-up of negatively charged hydrolysis products, fatty acid salts, led to changes in the mobility of PLA2. The mobility of individual enzymes on the monolayers was characterized by single particle tracking (SPT). Diffusion coefficients of enzymes adsorbed to the fluid interface were between 3 mu m^2/s on the L-DPPC and 4.6 mu m^/s on the D-DPPC monolayers. In regions enriched with hydrolysis products the diffusion dropped to approx. 0.2 mu m^2/s. In addition, slower normal and anomalous diffusion modes were seen at the L-DPPC gel domain boundaries where hydrolysis took place. The average residence times of the enzyme in the fluid regions of the monolayer and on the product domain were between approx. 30 and 220 ms. At the gel domains it was below the experimental time resolution, i.e. enzymes were simply reflected from the gel domains back into solution.Comment: 10 pages, 10 figure

A comparison of the development of audiovisual integration in children with autism spectrum disorders and typically developing children

This study aimed to investigate the development of audiovisual integration in children with Autism Spectrum Disorder (ASD). Audiovisual integration was measured using the McGurk effect in children with ASD aged 7–16 years and typically developing children (control group) matched approximately for age, sex, nonverbal ability and verbal ability. Results showed that the children with ASD were delayed in visual accuracy and audiovisual integration compared to the control group. However, in the audiovisual integration measure, children with ASD appeared to ‘catch-up’ with their typically developing peers at the older age ranges. The suggestion that children with ASD show a deficit in audiovisual integration which diminishes with age has clinical implications for those assessing and treating these children

A cognitive framework for object recognition with application to autonomous vehicles

Autonomous vehicles or self-driving cars are capable of sensing the surrounding environment so they can navigate roads without human input. Decisions are constantly made on sensing, mapping and driving policy using machine learning techniques. Deep Learning – massive neural networks that utilize the power of parallel processing – has become a popular choice for addressing the complexities of real time decision making. This method of machine learning has been shown to outperform alternative solutions in multiple domains, and has an architecture that can be adapted to new problems with relative ease. To harness the power of Deep Learning, it is necessary to have large amounts of training data that are representative of all possible situations the system will face. To successfully implement situational awareness in driverless vehicles, it is not possible to exhaust all possible training examples. An alternative method is to apply cognitive approaches to perception, for situations the autonomous vehicles will face. Cognitive approaches to perception work by mimicking the process of human intelligence – thereby permitting a machine to react to situations it has not previously experienced. This paper proposes a novel cognitive approach for object recognition. The proposed cognitive object recognition algorithm, referred to as Recognition by Components, is inspired by the psychological studies pertaining to early childhood development. The algorithm works by breaking down images into a series of primitive forms such as square, triangle, circle or rectangle and memory based aggregation to identify objects. Experimental results suggest that Recognition by Component algorithm performs significantly better than algorithms that require large amounts of training data

The relationship between organisational characteristics and the effects of clinical guidelines on medical performance in hospitals, a meta-analysis

We are grateful to our colleagues involved in the systematic review of guideline dissemination and implementation strategies across all settings especially Cynthia Fraser, Graeme MacLennan, Craig Ramsay, Paula Whitty, Martin Eccles, Lloyd Matowe, Liz Shirran. The systematic review of guideline dissemination and implementation strategies across all settings was funded by the UK NHS Health Technology Assessment Program. Dr Ruth Thomas is funded by a Wellcome Training Fellowship in Health Services Research. (Grant number GR063790MA). The Health Services Research Unit is funded by the Chief Scientists Office of the Scottish Executive Department of Health. Dr Jeremy Grimshaw holds a Canada Research Chair in Health Knowledge Transfer and Uptake. However the views expressed are those of the authors and not necessarily the funders.Peer reviewedPublisher PD

The association between alcohol use, alcohol use disorders and tuberculosis (TB). A systematic review

<p>Abstract</p> <p>Background</p> <p>In 2004, tuberculosis (TB) was responsible for 2.5% of global mortality (among men 3.1%; among women 1.8%) and 2.2% of global burden of disease (men 2.7%; women 1.7%). The present work portrays accumulated evidence on the association between alcohol consumption and TB with the aim to clarify the nature of the relationship.</p> <p>Methods</p> <p>A systematic review of existing scientific data on the association between alcohol consumption and TB, and on studies relevant for clarification of causality was undertaken.</p> <p>Results</p> <p>There is a strong association between heavy alcohol use/alcohol use disorders (AUD) and TB. A meta-analysis on the risk of TB for these factors yielded a pooled relative risk of 2.94 (95% CI: 1.89-4.59). Numerous studies show pathogenic impact of alcohol on the immune system causing susceptibility to TB among heavy drinkers. In addition, there are potential social pathways linking AUD and TB. Heavy alcohol use strongly influences both the incidence and the outcome of the disease and was found to be linked to altered pharmacokinetics of medicines used in treatment of TB, social marginalization and drift, higher rate of re-infection, higher rate of treatment defaults and development of drug-resistant forms of TB. Based on the available data, about 10% of the TB cases globally were estimated to be attributable to alcohol.</p> <p>Conclusion</p> <p>The epidemiological and other evidence presented indicates that heavy alcohol use/AUD constitute a risk factor for incidence and re-infection of TB. Consequences for prevention and clinical interventions are discussed.</p

Evaluation of adherence measures of antiretroviral prophylaxis in HIV exposed infants in the first 6 weeks of life.

CAPRISA, 2015.Abstract available in pdf

Compassion: a scoping review of the healthcare literature

BACKGROUND: Recent concerns about suboptimal patient care and a lack of compassion have prompted policymakers to question the preparedness of clinicians for the challenging environment in which they practice. Compassionate care is expected by patients and is a professional obligation of clinicians; however, little is known about the state of research on clinical compassion. The purpose of this scoping review was to map the literature on compassion in clinical healthcare. METHODS: Searches of eight electronic databases and the grey literature were conducted to identify empirical studies published over the last 25 years. Eligible studies explored perceptions or interventions of compassionate care in clinical populations, healthcare professionals, and healthcare students. Following the title and abstract review, two reviewers independently screened full-texts articles, and extracted study data. A narrative approach to synthesizing and mapping the literature was used. RESULTS AND DISCUSSION: Of 36,637 records, 648 studies were retrieved and 44 studies were included in the review. Less than one third of studies included patients. Six themes emerged from studies that explored perceptions of compassionate care: nature of compassion, development of compassion, interpersonal factors related to compassion, action and practical compassion, barriers and enablers of compassion, and outcomes of compassion. Intervention studies included two compassionate care trials with patients and eight educational programs that aimed to improve compassionate care in clinicians and students. CONCLUSIONS: This review identifies the limited empirical understanding of compassion in healthcare, highlighting the lack of patient and family voices in compassion research. A deeper understanding of the key behaviors and attitudes that lead to improved patient-reported outcomes through compassionate care is necessary