Native and invasive inoculation sources modify fungal community assembly and biomass production of a chaparral shrub

Feedbacks between plants and surrounding soil microbes can contribute to the establishment and persistence of invasive annual grasses as well as limit the success of restoration efforts. In this study, we aim to understand how three sources of soil inocula – native, invasive (from under Bromus diandrus) and sterile – affect the growth response and fungal community composition in the roots of a chaparral shrub, Adenostoma fasciculatum. We grew A. fasciculatum from seed in a greenhouse with each inoculum source and harvested at six months. We measured above- and below-ground biomass, arbuscular mycorrhizal fungal (AMF) colonization and conducted targeted-amplicon sequencing of the 18S and ITS2 loci to characterize AMF and general fungal community composition, respectively. Native inoculum resulted in roots with richer communities of some groups of AMF and non-AMF symbionts, when compared to roots grown with invasive or sterile inoculum. Seedlings grown with invasive and native inoculum did not have different growth responses, but both produced more biomass than a sterile control. These findings suggest that inoculation with soil from native species can increase the diversity of multiple groups of fungal symbionts and inoculation with live soil (invasive or native) can increase seedling biomass. Moreover, future work would benefit from assessing if a more diverse community of fungal symbionts increases seedling survival when planted in field restoration sites

Ship machinery and equipment wireless condition monitoring system

Condition based maintenance (CBM) is a maintenance approach that has been proven to provide significant reduction in maintenance cost and associated risk. Several industries such as aerospace and power generation have incorporated CBM and have been driving the developments in progressively better diagnostic and prognostic maintenance management. Other benefits that can be linked with appropriate use of CBM include better management of the operational characteristics of the vessel, reduction of emissions and energy efficiency. However in the maritime industry this is not the case. Less than 2% of the global fleet of vessels is utilising CBM (Shorten, 2012). This can be associated with several factors that inhibit the implementation of CBM in vessels. The most important of those are the cost of installation, the capital investment in training staff and the lack of trust in the prediction capabilities of the technology. This paper presents a novel method based on wireless data transmission which can demonstrate reduced installation costs. Moreover, as part of the INCASS (Inspection Capabilities for Enhanced Ship Safety) EU FP7 project, this paper presents a novel decision support system (DSS) solution that can be used onboard a ship with minimal initial training. The reliable user friendly graphical interface (GUI) developed in Java language provides relevant and on-time information for maintenance decision support. The combination of the developed hardware and software give a complete solution that can be applied to vessels while minimising investment costs and training

Predictive maintenance decision support system for enhanced energy efficiency of ship machinery

A decision support system (DSS) is an application that analyses data and presents results to users. DSS rapidly shift through huge amount of available data and thus allowing for faster analysis of condition monitoring data early detection of faults and improved allocation of resources. DSS can also predict and plan for future ship operators’ needs in order to optimize ship machinery operations. Such a system can provide substantial benefits to the maritime industry in terms of energy efficiency as the operation of the vessel can be optimised towards this end. As part of the INCASS (Inspection Capabilities for Enhanced Ship Safety) EU FP7 project, this paper presents a novel DSS solution which interrogates data from dynamic condition monitoring and compares them with historic data to present decision support information onboard a ship. To provide for Condition Based inspection and criticality based maintenance for ship machinery, data is acquired and stored for analysis through the DSS. Moreover surveys involving off-line and real time on-line measurement approaches are combined to provide a more complete monitoring method. The result is a reliable user friendly graphical interface (GUI) developed in Java language that can be employed onboard any vessel and can provide relevant and on-time information. The proposed actions from the DSS target energy efficient operation and reduction of fuel consumption and ship emissions. Moreover, a major factor taken into account through the prediction mechanism of the DSS is to assist in better spare parts scheduling and prioritizing ship inspection, maintenance and repairs towards enhanced and efficient ship operations

Dynamic risk and reliability assessment for ship machinery decision making

The proposed research, through INCASS (Inspection Capabilities for Enhanced Ship Safety) FP7 EU funded research project tackles the issue of predictive ship machinery inspection by enhancing reliability and safety, avoiding accidents, and protecting the environment. This paper presents the development of Machinery Risk/Reliability Analysis (MRA). The innovation of this model is the consideration and assessment of components’risk of failure and reliability degradation by utilizing raw input data. MRA takes into account the system’s dynamic state change, concerning failure rate variation over time. The presented methodology involves the generation of Markov Chains integrated with the advantages of Bayesian Belief Networks (BBNs). INCASS project developed a measurement campaign, where real time sensor data is recorded onboard a tanker, bulk carrier and container ship. The gathered data is utilized for MRA DSS tool validation and testing. Following research involves components and systems interdependencies and feed the continuous dynamic probabilistic condition monitoring algorithm

An intelligent system for vessels structural reliability evaluation

An intelligent system is proposed within INCASS (Inspection Capabilities for Enhanced Ship Safety) project for evaluating ship structural reliability and assisting in fatigue damage and structure response assessment. The system combines hydrodynamic, finite element and structural reliability models.. The hydrodynamic analysis model is not discussed in this paper. The finite element model input is a mesh for the mid-ship part of the vessel. Finally, the in-house structural reliability model input is the calculated output of the previous model as well as models for estimating crack development and propagation, corrosion growth and fatigue loading. The output includes the probability of failure for all the investigated components versus time which can be used to assess safe operation through the developed decision support software. The database can receive information from various sources including inspection and robotic systems data. The case study of a capsize bulk carrier the presents structural evaluation process

Air Quality Monitoring in the Southeast Community in the City of Newport News, VA

Purpose: The objective of this study was to assess air quality in the Southeast Community of Newport News, VA by monitoring air pollutants, including PM2.5, PM10, VOCs, NO2, and SO2. Currently, there is a lack of community specified air quality data in Newport News despite observed environmental degradation and public health problems. Methods: Three air sampling sites were located within residential areas of the Southeast Community, while four industrial air sampling sites were chosen based on proximity to potential pollution sources, including traffic emissions, the coal pier, and industrial activities. All of the industrial sites were located on the boundaries of the community. Each site was continuously monitored for eight hours per day and was sampled at least twice for data accuracy. A GRIMM PM monitor was used to measure PM2.5 and PM10 and a MultiRae PRO (model PGM-6248) was used to continuously quantify VOCs, NO2, and SO2. Results: While average PM2.5 and PM10 from all sample sites were within the acceptable range of EPA air quality criteria, averaged VOCs in the industrial and highway areas were higher than those in the community. Conclusion: The findings of this research suggest a need for long-term monitoring air quality with a series of air pollutants in the community

Childhood surgery for ambiguous genitalia: glimpses of practice changes or more of the same?

The Chicago consensus statement of 2005 was created at the point of cumulative criticisms and debates around the clinical practice of childhood genital surgery. It was drawn up at a time when it had become clearer that medically non-essential paediatric genital operations were associated with poor adult cosmetic outcomes and sexual functioning. However, data were not available for non-intervention. Therefore, parents and clinicians had no reliable information on how a child growing up with atypical genitalia might fare. The most positive recommendation in the consensus statement was the strong recommendation for decisions to be reached by a multidisciplinary team in collaboration with affected families. Importantly, the value of user groups was likewise formally acknowledged. For many services, there has been a sea change in the way surgeons work. Whilst some surgeons may continue with the standard practice of childhood genital surgery, it is becoming clearer that with adequate support, more individuals and families choose to postpone elective interventions. However, these are our observations only. Authoritative evidence must be based on high-quality multi-centre multidisciplinary research to prospectively monitor the long-term multiple outcomes of surgery and no surgery. There is as yet no obvious move towards such an endeavour. © Taylor & Francis

Challenges of Loss to Follow-up in Tuberculosis Research.

In studies evaluating methods for diagnosing tuberculosis (TB), follow-up to verify the presence or absence of active TB is crucial and high dropout rates may significantly affect the validity of the results. In a study assessing the diagnostic performance of the QuantiFERON®-TB Gold In-Tube test in TB suspect children in Tanzania, factors influencing patient adherence to attend follow-up examinations and reasons for not attending were examined. In 160 children who attended and 102 children who did not attend scheduled 2-month follow-up baseline health characteristics, demographic data and risk factors for not attending follow-up were determined. Qualitative interviews were used to understand patient and caretakers reasons for not returning for scheduled follow-up. Being treated for active tb in the dots program (OR: 4.14; 95% CI:1.99-8.62;p-value<0.001) and receiving money for the bus fare (OR:129; 95% CI 16->100;P-value<0.001) were positive predictors for attending follow-up at 2 months, and 21/85(25%) of children not attending scheduled follow-up had died. Interviews revealed that limited financial resources, i.e. lack of money for transportation and poor communication, were related to non-adherence. Patients lost to follow-up is a potential problem for TB research. Receiving money for transportation to the hospital and communication is crucial for adherence to follow-up conducted at a study facility. Strategies to ensure follow-up should be part of any study protocol