This paper proposes a floating-interest-rate infrastructure bond, where the interest of a government bond is paid to investors during the period of construction and the early period of operation. Unlike the usual government bond, which provides a fixed interest rate, the proposed floating-interest-rate infrastructure bond pays a floating interest, the rate of which depends on spillover tax revenues. Effective infrastructure projects have a positive effect on the economic growth of a region, known as the spillover effect. When user charges and the return from spillover tax revenues are below the fixed rate of the government bond, the interest rate will equal to the fixed rate of the government bond. In this case, investors in the infrastructure will receive interest on the government bond at the minimum rate. As the spillover effect of the infrastructure increases, the rate of return for infrastructure investment will become greater than the fixed rate of the government bond. The success of the floating-interest-rate infrastructure bond depends on the spillover effect and on transparency and accountability. Policy recommendations are provided in this paper on how to increase the spillover effect and improve transparency and accountability.
In this study, daily averages of air quality parameters were measured in two stations (S1 and S2) of the organized industrial district in Samsun. The meteorological variables were measured at only one station (S1), such as temperature, relative humidity, wind speed, solar radiation, and ambient pressure in 2007, and the daily promised limit for nitrogen dioxide has been especially exceeded at 206 times for 1st station. However, exceeds of the limit value in 2006 for 1st station was reduced by approximately 3.5 times. The daily nitrogen dioxide concentration did not exceed the daily limit of WHO[1] as for 2nd station. The results obtained showed that under the influence of dominant wind direction, the second station measurement results are higher than that of the first station. To determine all of the possible environmental effects, the measurements should be analyzed from a multi-point perspective.
Knowledge of the state of fragmentation and transformation of a forested landscape is crucial for proper planning and biodiversity conservation. Chile is one of the world’s biodiversity hotspots; within it is the Nahuelbuta mountain range, which is considered an area of high biodiversity value and intense anthropic pressure. Despite this, there is no precise information on the degree of transformation of its landscape and its conservation status. The objective of this work was to evaluate the state of the landscape and the spatio-temporal changes of the native forests in this mountain range. Using Landsat images from 1986 and 2011, thematic maps of land use were generated. A 33% loss of native forest in 25 years was observed, mainly associated to the substitution by forest plantations. Changes in the spatial patterns of land cover and land use reveal a profound transformation of the landscape and advanced fragmentation of forests. We discuss how these patterns of change threaten the persistence of several endemic species at high risk of extinction. If these anthropogenic processes continue, these species could face an increased risk of extinction.
In order to seek management alternatives for anthracnose caused by the fungus Colletotrichum gloeosporioides in blackberry (Rubus glaucus Benth.), at the Tibaitatá Research Center of the Colombian Agricultural Research Corporation AGROSAVIA (formerly CORPOICA), an experiment was conducted to evaluate the effect of the application of the major elements nitrogen (N), phosphorus (P), potassium (K) and calcium (Ca) on infections of the fungus C. gloeosporioides strain-52. For this purpose, a randomized complete block design was used with an arrangement of treatments in an orthogonal central composite design. To evaluate the relationship of fertilization levels and disease severity, an artificial inoculation was made on thorny blackberry stems using 0.5 cm mycelial discs at a concentration of 9.53 × 104 conidia. Observations consisted of: disease severity (S), incubation period (IP) and rate of development (r). Data analysis was done by the cluster method on the severity variable, a Pearson correlation analysis between variables, as well as a regression to estimate the effect of nutrients applied on the severity of C. gloeosporioides strain-52. The treatments were concentrated in four groups with the ranges (in parentheses) S (15.9% and 91.8%), PI (9 and 15.3) and Tr (0.0254 and 0.0468). A positive and significant correlation was observed between S and r (P < 0.001) and a negative correlation between PI with S and r (P < 0.001). By means of regression analysis, a linear model was generated that showed a reduction in disease severity with increasing N dose and an increase with the levels of P and Ca applied.
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