INTEGRATED ECOLOGICAL PLANNING IN SINGAPORE: NEOTIEWPIA ECO-VILLAGE IN BUSTLING METROPOLITAN

ABSTRACT :The Neotiewpia Eco-Village is located within the Lim Chu Kang district at the north of Singapore. The Eco-Village only comprised of 3.5 sq km. Meanwhile the area was dominated by farms, chalets and Sungei Buloh Wetland Reserve. In 2006, National University of Singapore, School of Design and Environment (SDE), MSc. Environmental Management and Nature Society of Singapore initiated an ecological planning exercise within the Neotiewpia site to reduce the environmental impact from the development while providing Eco-friendly Tourism and R&D activities that feasible in the site. We did participate in the exercise and we tried explaining the ecological process, the limitation and potential development for integrated ecological planning framework in Developing Countries like Indonesia, Brazil, etc with high ecological-values ecosystems. The Vision of Neotiewpia was “A Model Eco-Village that Respects its Natural Heritage, Builds Strong Community Links and Promotes Economic Development on Nature’s Premises." And Neotiewpia was successfully planned and designed with integrated ecological planning approach. It embraced the land evaluation and impact assessment. Further the plan was found feasible by the Singapore Government by earmarking the Lim Chu Kang and Kranji for Agri-tainment development in 2008 (although partially implemented). The Neotiewpia or Lim Chu Kang area was found thriving with Green-Economy and Agro-Tourism. This integrated ecological planning could be translated to other areas in Developing Countries with agriculture potential and facing development pressures such as Neotiewpia. This concept would give alternate Green-Solution to the current economic crisis

Availability of phosphate for phytoplankton and bacteria and of labile organic carbon for bacteria at different pCO2 levels in a mesocosm study

Availability of phosphate for phytoplankton and bacteria and of glucose for bacteria at different pCO2 levels were studied in a mesocosm experiment (PeECE III). Using nutrient-depleted SW Norwegian fjord waters, three different levels of pCO2 (350 μatm: 1×CO2; 700 μatm: 2×CO2; 1050 μatm: 3×CO2) were set up, and nitrate and phosphate were added at the start of the experiment in order to induce a phytoplankton bloom. Despite similar responses of total particulate P concentration and phosphate turnover time at the three different pCO2 levels, the size distribution of particulate P and 33PO4 uptake suggested that phosphate transferred to the >10 μm fraction was greater in the 3×CO2 mesocosm during the first 6–10 days when phosphate concentration was high. During the period of phosphate depletion (after Day 12), specific phosphate affinity and specific alkaline phosphatase activity (APA) suggested a P-deficiency (i.e. suboptimal phosphate supply) rather than a P-limitation for the phytoplankton and bacterial community at the three different pCO2 levels. Specific phosphate affinity and specific APA tended to be higher in the 3×CO2 than in the 2×CO2 and 1×CO2 mesocosms during the phosphate depletion period, although no statistical differences were found. Glucose turnover time was correlated significantly and negatively with bacterial abundance and production but not with the bulk DOC concentration. This suggests that even though constituting a small fraction of the bulk DOC, glucose was an important component of labile DOC for bacteria. Specific glucose affinity of bacteria behaved similarly at the three different pCO2 levels with measured specific glucose affinities being consistently much lower than the theoretical maximum predicted from the diffusion-limited model. This suggests that bacterial growth was not severely limited by the glucose availability. Hence, it seems that the lower availability of inorganic nutrients after the phytoplankton bloom reduced the bacterial capacity to consume labile DOC in the upper mixed layer of the stratified mesocosms

Injury Prediction in Competitive Runners with Machine Learning

Purpose: Staying injury-free is a major factor for success in sports. Although injuries are difficult to forecast, novel technologies and data science applications could provide important insights. Our purpose is to use machine learning for the prediction of injuries in runners, based on detailed training logs. Methods: Prediction of injuries was evaluated on a new data set of 77 high-level middle and long distance runners, over a period of seven years. Two analytic approaches were applied. First, the training load from the previous seven days were expressed as a time series, with each day’s training being described by ten features. These features were a combination of objective data from a GPS watch (e.g., duration, distance), together with subjective data about the exertion and success of the training. Second, a training week was summarized by 22 aggregate features, and a time window of three weeks before the injury was considered. Results: A predictive system based on bagged XGBoost machine learning models, resulted in Receiver Operating Characteristic curves with average Areas Under the Curves of 0.724 and 0.678 for the day and week approach, respectively. Especially the results of the day approach reflect a reasonably high probability that our system makes correct injury predictions. Conclusions: Our machine learning-based approach predicts a sizable portion of the injuries, in particular when the model is based on training load-data in the days preceding an injury. Overall, these results demonstrate the possible merits of using machine learning to predict injuries and tailor training programs for athletes

Environmental outcomes of landscape-scale agricultural transitions in the Upper Midwestern U.S.

The United States (U.S.) Corn Belt leads North America in row crop production, yet this high productivity comes at an environmental cost in terms of nitrate loss, soil erosion, and greenhouse gas emissions. In this study, we focus on the Upper Mississippi River basin within the U.S. Corn Belt, which represents a landscape scale for agricultural transformation. We outline a methodology to assess a suite of environmental outcomes associated with the transition from summer annual maize/soybean systems to incorporation of continuous living cover systems. We use and expand publicly available tools alongside empirical data to assess nitrate loss, soil erosion, and greenhouse gas emissions for four potential agricultural transition scenarios in the region, on an annual basis compared to a business-as-usual maize/soybean rotation. We consider the following four scenarios: incorporating (1) winter annual cover crops or (2) winter annual oilseeds into 50% of maize and soybean hectares in the region, or converting 50% of marginally productive maize and soybean hectares to (3) agroforestry or (4) pastured livestock systems. Our results indicate that all four systems are likely to reduce topsoil loss when compared to maize and soybean systems, and that the more transformative systems—agroforestry and pastured livestock—have the greatest potential to reduce nitrate loss. Yet, our results suggest that among these transitions, there are tradeoffs in environmental outcomes. For example, pastured livestock and winter annual oilseeds could potentially increase greenhouse gas emissions relative to maize/soybean systems. Our results illustrate that continuous living cover could improve environmental outcomes in the Upper Midwest, but there is tremendous uncertainty and variability surrounding those outcomes

A COMPARISON OF THE EFFECTIVENESS OF THE “TOOTHKEEPER’ AND A TRADITIONAL DENTAL HEALTH EDUCATION PROGRAM

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/66303/1/j.1752-7325.1975.tb04031.x.pd

Regulation of angiopoietin-like protein 4 Production during and after exercise

© 2014 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of the American Physiological Society and The Physiological Society. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.Angiopoietin-like protein 4 (ANGPTL4) may regulate lipoprotein lipase-dependent plasma clearance of triacylglycerol from skeletal muscle during exercise. The aim of this study was to examine the importance of muscle in regulating ANGPTL4 in response to exercise. We sampled muscle biopsies and serum before, immediately after, and 2 h after 45 min of ergometer cycling. Sampling was done before and after a 12-week training intervention in controls and dysglycemic subjects. Moreover, fat biopsies were taken before and after the training intervention. The regulation of ANGPTL4 was also investigated in several tissues of exercising mice, and in cultured myotubes. ANGPTL4 levels in serum and expression in muscle were highest 2 h after exercise in both groups. Whereas ANGPTL4 was higher in muscle of exercising controls as compared to dysglycemic subjects, the opposite was observed in serum. In exercising mice, Angptl4 mRNA showed both higher basal expression and induction in liver compared to muscle. Angptl4 mRNA was much higher in adipose tissue than muscle and was also induced by exercise. We observed two mRNA isoforms of ANGPTL4 in muscle and fat in humans. Both were induced by exercise in muscle; one isoform was expressed 5- to 10-fold higher than the other. Studies in mice and cultured myotubes showed that both fatty acids and cortisol have the potential to increase ANGPTL4 expression in muscle during exercise. In conclusion, ANGPTL4 is markedly induced in muscle in response to exercise. However, liver and adipose tissue may contribute more than muscle to the exercise-induced increase in circulating ANGPTL4.Seksjon for fysisk prestasjonsevne / Department of Physical Performanc

Carbon payment strategies in coffee agroforests shape climate and biodiversity outcomes

Agricultural supply chains increasingly mitigate climate change and biodiversity loss through initiatives that either plant trees or protect threatened carbon stocks on farmlands. We conducted a global meta-analysis to evaluate how these programs may impact carbon and biodiversity outcomes across coffee agriculture, which spans a vegetation complexity gradient from monoculture to biodiverse agroforestry. For aboveground carbon, we estimated coffee farms currently hold 481.59 TgC globally and could sequester an additional 81.53-86.50 TgC under different agroforestry adoption scenarios. However, more than twice as much aboveground carbon could be lost under intensification scenarios (174.23-221.45 TgC). While tree diversity supports overall biodiversity in agroforestry, we found it does not independently increase carbon, indicating carbon and biodiversity outcomes may be decoupled. Ultimately, tree planting programs in coffee can sequester meaningful carbon volumes but may fail to achieve global carbon and biodiversity goals if they do not also protect existing agroforestry and diversify planting efforts

Impact of Temporary Nitrogen Deprivation on Tomato Leaf Phenolics

Reducing the use of pesticides represents a major challenge of modern agriculture. Plants synthesize secondary metabolites such as polyphenols that participate in the resistance to parasites. The aim of this study was to test: (1) the impact of nitrogen deficiency on tomato (Solanum lycopersicum) leaf composition and more particularly on two phenolic molecules (chlorogenic acid and rutin) as well as on the general plant biomass; and (2) whether this effect continued after a return to normal nitrogen nutrition. Our results showed that plants deprived of nitrogen for 10 or 19 days contained higher levels of chlorogenic acid and rutin than control plants. In addition, this difference persisted when the plants were once again cultivated on a nitrogen-rich medium. These findings offer interesting perspectives on the use of a short period of deprivation to modulate the levels of compounds of interest in a plant

High-pressure processing-induced transcriptome response during recovery of Listeria monocytogenes

Background High-pressure processing (HPP) is a commonly used technique in the food industry to inactivate pathogens, including L. monocytogenes. It has been shown that L. monocytogenes is able to recover from HPP injuries and can start to grow again during long-term cold storage. To date, the gene expression profiling of L. monocytogenes during HPP damage recovery at cooling temperature has not been studied. In order identify key genes that play a role in recovery of the damage caused by HPP treatment, we performed RNA-sequencing (RNA-seq) for two L. monocytogenes strains (barotolerant RO15 and barosensitive ScottA) at nine selected time points (up to 48 h) after treatment with two pressure levels (200 and 400 MPa). Results The results showed that a general stress response was activated by SigB after HPP treatment. In addition, the phosphotransferase system (PTS; mostly fructose-, mannose-, galactitol-, cellobiose-, and ascorbate-specific PTS systems), protein folding, and cobalamin biosynthesis were the most upregulated genes during HPP damage recovery. We observed that cell-division-related genes (divIC, dicIVA, ftsE, and ftsX) were downregulated. By contrast, peptidoglycan-synthesis genes (murG, murC, and pbp2A) were upregulated. This indicates that cell-wall repair occurs as a part of HPP damage recovery. We also observed that prophage genes, including anti-CRISPR genes, were induced by HPP. Interestingly, a large amount of RNA-seq data (up to 85%) was mapped to Rli47, which is a non-coding RNA that is upregulated after HPP. Thus, we predicted that Rli47 plays a role in HPP damage recovery in L. monocytogenes. Moreover, gene-deletion experiments showed that amongst peptidoglycan biosynthesis genes, pbp2A mutants are more sensitive to HPP. Conclusions We identified several genes and mechanisms that may play a role in recovery from HPP damage of L. monocytogenes. Our study contributes to new information on pathogen inactivation by HPP.Peer reviewe