Atomic force microscopy shows that vaccinia topoisomerase IB generates filaments on DNA in a cooperative fashion

Type IB DNA topoisomerases cleave and rejoin one strand of the DNA duplex, allowing for the removal of supercoils generated during replication and transcription. In addition, electron microscopy of cellular and viral TopIB–DNA complexes has suggested that the enzyme promotes long-range DNA–DNA crossovers and synapses. Here, we have used the atomic force microscope to visualize and quantify the interaction between vaccinia topoisomerase IB (vTopIB) and DNA. vTopIB was found to form filaments on nicked-circular DNA by intramolecular synapsis of two segments of a single DNA molecule. Measuring the filament length as a function of protein concentration showed that synapsis is a highly cooperative process. At high protein:DNA ratios, synapses between distinct DNA molecules were observed, which led to the formation of large vTopIB-induced DNA clusters. These clusters were observed in the presence of Mg(2+), Ca(2+) or Mn(2+), suggesting that the formation of intermolecular vTopIB-mediated DNA synapsis is favored by screening of the DNA charge

Key Dimension 4: Environmental Waste Security

Asia and the Pacific shows a positive trend in strengthening water security with the number of water insecure countries dropping to 29 from 38 in 2013, according to this latest edition of the Asian Water Development Outlook (AWDO). Despite this progress, enormous challenges in water security remain. Asia is home to half of the world’s poorest people. Water for agriculture continues to consume 80% of water resources. A staggering 1.7 billion people lack access to basic sanitation. With a predicted population of 5.2 billion by 2050 and 22 megacities by 2030, the region’s finite water resources will be under enormous pressure—especially with increasing climate variability. Recent estimates indicate up to 3.4 billion people could be living in water-stressed areas of Asia by 2050. With a Sustainable Development Goal dedicated to water and sanitation for all, AWDO 2016 is a tool to help assess the region’s progress in meeting this ambitious target

Applications of Bayesian Networks as Decision Support Tools for Water Resource Management under Climate Change and Socio-Economic Stressors: A Critical Appraisal

Bayesian networks (BNs) are widely implemented as graphical decision support tools which use probability inferences to generate “what if?” and “which is best?” analyses of potential management options for water resource management, under climate change and socio-economic stressors. This paper presents a systematic quantitative literature review of applications of BNs for decision support in water resource management. The review quantifies to what extent different types of data (quantitative and/or qualitative) are used, to what extent optimization-based and/or scenario-based approaches are adopted for decision support, and to what extent different categories of adaptation measures are evaluated. Most reviewed publications applied scenario-based approaches (68%) to evaluate the performance of management measures, whilst relatively few studies (18%) applied optimization-based approaches to optimize management measures. Institutional and social measures (62%) were mostly applied to the management of water-related concerns, followed by technological and engineered measures (47%), and ecosystem-based measures (37%). There was no significant difference in the use of quantitative and/or qualitative data across different decision support approaches (p = 0.54), or in the evaluation of different categories of management measures (p = 0.25). However, there was significant dependence (p = 0.076) between the types of management measure(s) evaluated, and the decision support approaches used for that evaluation. The potential and limitations of BN applications as decision support systems are discussed along with solutions and recommendations, thereby further facilitating the application of this promising decision support tool for future research priorities and challenges surrounding uncertain and complex water resource systems driven by multiple interactions amongst climatic and non-climatic changes. View Full-Tex

Clients’ Experiences of a Community Based Lifestyle Modification Program: A Qualitative Study

There is little information about how clients attending lifestyle modification programs view the outcomes. This qualitative study examined the clients’ experience of a community based lifestyle modification program in Hong Kong. Semi-structured interviews were conducted with 25 clients attending the program. Clients perceived the program had positive impacts on their health and nutrition knowledge. They experienced frustration, negative emotion, lack of motivation, and pressure from others during the program. Working environment and lack of healthy food choices in restaurants were the major perceived environmental barriers for lifestyle modification. Clients valued nutritionists’ capability of providing professional information and psychological support in the program. Our results suggest that nutritionist’s capability of providing quality consultations and patient-centered care are important for empowering clients achieve lifestyle modification

A Bayesian belief data mining approach applied to rice and shrimp aquaculture

In many parts of the world, conditions for small scale agriculture are worsening, creating challenges in achieving consistent yields. The use of automated decision support tools, such as Bayesian Belief Networks (BBNs), can assist producers to respond to these factors. This paper describes a decision support system developed to assist farmers on the Mekong Delta, Vietnam, who grow both rice and shrimp crops in the same pond, based on an existing BBN. The BBN was previously developed in collaboration with local farmers and extension officers to represent their collective perceptions and understanding of their farming system and the risks to production that they face. This BBN can be used to provide insight into the probable consequences of farming decisions, given prevailing environmental conditions, however, it does not provide direct guidance on the optimal decision given those decisions. In this paper, the BBN is analysed using a novel, temporally-inspired data mining approach to systematically determine the agricultural decisions that farmers perceive as optimal at distinct periods in the growing and harvesting cycle, given the prevailing agricultural conditions. Using a novel form of data mining that combines with visual analytics, the results of this analysis allow the farmer to input the environmental conditions in a given growing period. They then receive recommendations that represent the collective view of the expert knowledge encoded in the BBN allowing them to maximise the probability of successful crops. Encoding the results of the data mining/inspection approach into the mobile Decision Support System helps farmers access explicit recommendations from the collective local farming community as to the optimal farming decisions, given the prevailing environmental conditions

Technical Report Series on Global Modeling and Data Assimilation, Volume 41 : GDIS Workshop Report

The workshop "An International Global Drought Information System Workshop: Next Steps" was held on 10-13 December 2014 in Pasadena, California. The more than 60 participants from 15 countries spanned the drought research community and included select representatives from applications communities as well as providers of regional and global drought information products. The workshop was sponsored and supported by the US National Integrated Drought Information System (NIDIS) program, the World Climate Research Program (WCRP: GEWEX, CLIVAR), the World Meteorological Organization (WMO), the Group on Earth Observations (GEO), the European Commission Joint Research Centre (JRC), the US Climate Variability and Predictability (CLIVAR) program, and the US National Oceanic and Atmospheric Administration (NOAA) programs on Modeling, Analysis, Predictions and Projections (MAPP) and Climate Variability & Predictability (CVP). NASA/JPL hosted the workshop with logistical support provided by the GEWEX program office. The goal of the workshop was to build on past Global Drought Information System (GDIS) progress toward developing an experimental global drought information system. Specific goals were threefold: (i) to review recent research results focused on understanding drought mechanisms and their predictability on a wide range of time scales and to identify gaps in understanding that could be addressed by coordinated research; (ii) to help ensure that WRCP research priorities mesh with efforts to build capacity to address drought at the regional level; and (iii) to produce an implementation plan for a short duration pilot project to demonstrate current GDIS capabilities. See http://www.wcrp-climate.org/gdis-wkshp-2014-objectives for more information

A Coupled Land-Atmosphere Simulation Program (CLASP): Calibration and validation

We present a model and application designed to study the coupled land-atmosphere hydrologic cycle, following water from its inflow into a region by horizontal atmospheric transport through surface-atmosphere exchange processes and aquifer recharge to outflow as runoff and river discharge. The model includes a two-way water flow among its major reservoirs (atmosphere, vadose zone, groundwater, surface water, river). A unique feature of the model is that phreatophytic interactions are included when the water table intersects the root zone. The model emulates a uniform grid box of an atmospheric general circulation model, but with finer horizontal resolution for the land processes, and forms a test bed for developing continental-scale simulation of the hydrologic cycle. The model is calibrated using the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) observations for 1987 and validated using FIFE observations for 1988 and 1989. Four physical factors emerge as important for simulating the FIFE water cycle: effective relative humidity for initiating stable (large scale) condensation, length of the growing season, amount of available soil water, and cloud cover parameterization. Further evaluation uses water table and river discharge measurements for years up to 1993. The model simulates multiyear behavior in the hydrologic cycle reasonably well. Average differences between FIFE observations and simulated fluxes during the calibration period are only a few percent, including fluxes not specifically calibrated. Model-observation differences in surface sensible and latent heat fluxes are larger during the 1988 drought but recover to relatively small values for 1989, suggesting some difficulty in simulating hydrologic extremes occurring outside the calibration conditions. A model sensitivity study using statistical disaggregation to allow precipitation to fall on only a portion of the landscape indicates that spatial disaggregation of precipitation can have strong impact on groundwater storage and surface discharge, potentially improving agreement between observed and simulated streamflow. Water redistributed through the model\u27s aquifer-river network can at times raise the water table high enough for water to seep back to the vegetation root zone and increase evapotranspiration. During relatively dry periods, up to 33% of monthly evapotranspiration was derived from groundwater-supported evapotranspiration, emphasizing the need to quantify better aquifer-atmosphere interaction. The work also demonstrates the feasibility and utility of fully coupled water budgeting schemes

Investigating the relationships between environmental stressors and stream condition using Bayesian belief networks

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/92037/1/j.1365-2427.2011.02683.x.pd