Development and Application of an Atomic Absorption Spectrometry-Based Method to Quantify Magnesium in Leaves of Dioscorea polystachya

The Chinese yam (Dioscorea polystachya, DP) is known for the nutritional value of its tuber. Nevertheless, DP also has promising pharmacological properties. Compared with the tuber, the leaves of DP are still very little studied. However, it may be possible to draw conclusions about the plant quality based on the coloration of the leaves. Magnesium, as a component of chlorophyll, seems to play a role. Therefore, the aim of this research work was to develop an atomic absorption spectrometry-based method for the analysis of magnesium (285.2125 nm) in leaf extracts of DP following the graphite furnace sub-technique. The optimization of the pyrolysis and atomization temperatures resulted in 1500 °C and 1800 °C, respectively. The general presence of flavonoids in the extracts was detected and could explain the high pyrolysis temperature due to the potential complexation of magnesium. The elaborated method had linearity in a range of 1–10 µg L−1 (R2 = 0.9975). The limits of detection and quantification amounted to 0.23 µg L−1 and 2.00 µg L−1, respectively. The characteristic mass was 0.027 pg, and the recovery was 96.7–102.0%. Finally, the method was applied to extracts prepared from differently colored leaves of DP. Similar magnesium contents were obtained for extracts made of dried and fresh leaves. It is often assumed that the yellowing of the leaves is associated with reduced magnesium content. However, the results indicated that yellow leaves are not due to lower magnesium levels. This stimulates the future analysis of DP leaves considering other essential minerals such as molybdenum or manganese

Spatio-Temporal Analysis of the Relationship Between WNV Dissemination and Environmental Variables in Indianapolis, USA.

Background: This study developed a multi-temporal analysis on the relationship between West Nile Virus (WNV) dissemination and environmental variables by using an integrated approach of remote sensing, GIS, and statistical techniques. WNV mosquito cases in seven months (April-October) of the six years (2002–2007) were collected in Indianapolis, USA. Epidemic curves were plotted to identify the temporal outbreaks of WNV. Spatial-temporal analysis and k-mean cluster analysis were further applied to determine the high-risk areas. Finally, the relationship between environmental variables and WNV outbreaks were examined by using Discriminant Analysis. Results: The results show that the WNV epidemic curve reached its peak in August for all years in the study area except in 2007, where the peak was reached in July. WNV dissemination started from the central longitudinal corridor of the city and spread out to the east and west. Different years and seasons had different high-risk areas, but the southwest and southeast corners show the highest risk for WNV infection due to their high percentages of agriculture and water sources. Conclusion: Major environmental factors contributing to the outbreak of WNV in Indianapolis were the percentages of agriculture and water, total length of streams, and total size of wetlands. This study provides important information for urban public health prevention and management. It also contributes to the optimization of mosquito control and arrangement of future sampling efforts

Threshold Concepts in Object-Oriented Modelling

Proponents of the object-oriented (OO) paradigm frequently claim that the OO paradigm is ‘more natural’ than the procedural paradigm because the world is filled with objects that have both attributes and behaviors. However students in higher education generally experience considerable difficulty in understanding OO concepts and acquiring the necessary skills in object-oriented analysis and design. This paper proposes OO modelling to be a set of threshold concepts and describes a study that sought to improve undergraduate students’ learning of OO modelling by adopting concept maps as ‘stepping stones’ to facilitate the development of analysis class and sequence diagrams

Practical aspects of modelling parameter uncertainty for risk capital calculation

“This is a post-peer-review, pre-copyedit version of an article published in Zeitschrift fur die gesamte Versicherungswissenschaft. The final authenticated version is available online at: http://dx.doi.org/10.1007/s12297-019-00428-xWe assume that an insurance undertaking models its risk by a random variable X=X(¿0) with a fixed parameter (vector) ¿0. If the undertaking does not know ¿0 and can only estimate it from historical data, it faces parameter uncertainty. Neglecting parameter uncertainty can lead to an underestimation of the true risk capital requirement (see e.g. Gerrard and Tsanakas 2011; Fröhlich and Weng 2015). In this contribution we address some practical questions. To illustrate the relevance of the parameter risk we determine the probability of solvency for a risk capital model not taking parameter uncertainty into account for different distributions and samples sizes. We then follow the “inversion method” introduced in Fröhlich and Weng (2015) known to model an appropriate risk capital requirement respecting parameter uncertainty for a wide class of distributions and common estimation methods. We extend the idea to distribution families and estimation methods that have not been considered so far in this context but are frequently used to model the losses of an insurance undertakingPeer ReviewedPostprint (author's final draft

A Review of the E-learning Resources on Building Physics for Architects

This paper discusses about e-learning resources for supporting the implementation of sustainable environmental design (SED) in the architecture discipline. The research has identified from the literature that organisation of learning materials, visualisation of information and enabling interdisciplinary communication are the key factors of designing an effective e-learning tool for this task. The review found the available e-learning resources being very limited in number with respect to building physics. The EDUCATE Portal and Autodesk Sustainability Workshop website can be considered good examples of the e-learning tools reviewed in this paper

The evaluation of the Australian office market forecast accuracy

Purpose: Property market models have the overriding aim of predicting reasonable estimates of key dependent variables (demand, supply, rent, yield, vacancy and net absorption rate). These can be based on independent drivers of core property and economic activities. Accurate predictions can only be conducted when ample quantitative data are available with fewer uncertainties. However, a broad-fronted social, technical and ecological evolution can throw up sudden, unexpected shocks that result in the econometric outputs sceptical to unknown risk factors. Therefore, this paper aims at evaluating Australian office market forecast accuracy and to determine whether the forecasts capture extreme downside risk events. Design/methodology/approach: This study follows a quantitative research approach, using secondary data analysis to test the accuracy of economists’ forecasts. The forecast accuracy evaluation encompasses the measurement of economic and property forecasts under the following phases: (i) testing for the forecast accuracy, (ii) analysing outliers of forecast errors and (iii) testing of causal relationships. Forecast accuracy measurement incorporates scale independent metrics that include Theil’s U values (U1 and U2) and mean absolute scaled error (MASE). Inter Quartile Range (IQR) rule is used for the outlier analysis. To find the causal relationships among variables, the time series regression methodology is utilised, including multiple regression analysis and Granger causality developed under the vector auto regression (VAR). Findings: The credibility of economic and property forecasts was questionable around the period of the Global Financial Crisis (GFC); a significant man-made Black Swan event. The forecast accuracy measurement highlighted rental movement and net absorption forecast errors as the critical inaccurate predictions. These key property variables are explained by historic information and independent economic variables. However, these do not explain the changes when error time series of the variables were concerned. According to VAR estimates, all property variables have a significant causality derived from the lagged values of Australian S&P/ASX 200 (ASX) forecast errors. Therefore, lagged ASX forecast errors could be used as a warning signal to adjust property forecasts. Research Limitations: Secondary data were obtained from the premier Australian property markets: Canberra, Sydney, Brisbane, Adelaide, Melbourne and Perth. A limited 10-year timeframe (2001 – 2011) was used in the ex-post analysis for the comparison of economic and property variables. Forecasts ceased from 2011, due to the discontinuity of the Australian Financial Review (AFR) quarterly survey of economists; the main source of economic forecast data. Practical implications: The research strongly recommended naïve forecasts for the property variables, as an input determinant in each office market forecast equation. Further, lagged forecast errors in the ASX could be used as a warning signal for the successive property forecast errors. Hence, data adjustments can be made to ensure the accuracy of the Australian office market forecasts. Originality/value: The paper highlights the critical inaccuracy of the Australian office market forecasts around the GFC. In an environment of increasing incidence of unknown events, these types of risk events should not be dismissed as statistical outliers in real estate modelling. As a proactive strategy to improve office market forecasts, lagged ASX forecast errors could be used as a warning signal. This causality was mirrored in rental movements and total vacancy forecast errors. The close interdependency between rents and vacancy rates in the forecasting process and the volatility in rental cash flows reflects on direct property investment and subsequently on the ASX, is therefore justified

Neural Grasp Distance Fields for Robot Manipulation

We formulate grasp learning as a neural field and present Neural Grasp Distance Fields (NGDF). Here, the input is a 6D pose of a robot end effector and output is a distance to a continuous manifold of valid grasps for an object. In contrast to current approaches that predict a set of discrete candidate grasps, the distance-based NGDF representation is easily interpreted as a cost, and minimizing this cost produces a successful grasp pose. This grasp distance cost can be incorporated directly into a trajectory optimizer for joint optimization with other costs such as trajectory smoothness and collision avoidance. During optimization, as the various costs are balanced and minimized, the grasp target is allowed to smoothly vary, as the learned grasp field is continuous. In simulation benchmarks with a Franka arm, we find that joint grasping and planning with NGDF outperforms baselines by 63% execution success while generalizing to unseen query poses and unseen object shapes. Project page: https://sites.google.com/view/neural-grasp-distance-fields

RdgB2 is required for dim-light input into intrinsically photosensitive retinal ganglion cells.

A subset of retinal ganglion cells is intrinsically photosensitive (ipRGCs) and contributes directly to the pupillary light reflex and circadian photoentrainment under bright-light conditions. ipRGCs are also indirectly activated by light through cellular circuits initiated in rods and cones. A mammalian homologue (RdgB2) of a phosphoinositide transfer/exchange protein that functions in Drosophila phototransduction is expressed in the retinal ganglion cell layer. This raised the possibility that RdgB2 might function in the intrinsic light response in ipRGCs, which depends on a cascade reminiscent of Drosophila phototransduction. Here we found that under high light intensities, RdgB2(-/-) mutant mice showed normal pupillary light responses and circadian photoentrainment. Consistent with this behavioral phenotype, the intrinsic light responses of ipRGCs in RdgB2(-/-) were indistinguishable from wild-type. In contrast, under low-light conditions, RdgB2(-/-) mutants displayed defects in both circadian photoentrainment and the pupillary light response. The RdgB2 protein was not expressed in ipRGCs but was in GABAergic amacrine cells, which provided inhibitory feedback onto bipolar cells. We propose that RdgB2 is required in a cellular circuit that transduces light input from rods to bipolar cells that are coupled to GABAergic amacrine cells and ultimately to ipRGCs, thereby enabling ipRGCs to respond to dim light