Soil quality response to land-use change for sugarcane expansion in Brazil

Globally, increasing demands for biofuels have intensified the rate of land-use change (LUC) for expansion of bioenergy crops. In Brazil, the world\'s largest sugarcane-ethanol producer, sugarcane area has expanded by 35% (3.2 Mha) in the last decade. Sugarcane expansion has resulted in extensive pastures being subjected to intensive mechanization and large inputs of agrochemicals, which have direct implications on soil quality (SQ). We hypothesized that LUC to support sugarcane expansion leads to overall SQ degradation. To test this hypothesis we conducted a field-study at three sites in the central-southern region, to assess the SQ response to the primary LUC sequence (i.e., native vegetation to pasture to sugarcane) associated to sugarcane expansion in Brazil. At each land use site undisturbed and disturbed soil samples were collected from the 0-10, 10-20 and 20-30 cm depths. Soil chemical and physical attributes were measured through on-farm and laboratory analyses. A dataset of soil biological attributes was also included in this study. Initially, the LUC effects on each individual soil indicator were quantified. Afterward, the LUC effects on overall SQ were assessed using the Soil Management Assessment Framework (SMAF). Furthermore, six SQ indexes (SQI) were developed using approaches with increasing complexity. Our results showed that long-term conversion from native vegetation to extensive pasture led to soil acidification, significant depletion of soil organic carbon (SOC) and macronutrients [especially phosphorus (P)] and severe soil compaction, which creates an unbalanced ratio between water- and air-filled pore space within the soil and increases mechanical resistance to root growth. Conversion from pasture to sugarcane improved soil chemical quality by correcting for acidity and increasing macronutrient levels. Despite those improvements, most of the P added by fertilizer accumulated in less plant-available P forms, confirming the key role of organic P has in providing available P to plants in Brazilian soils. Long-term sugarcane production subsequently led to further SOC depletions. Sugarcane production had slight negative impacts on soil physical attributes compared to pasture land. Although tillage performed for sugarcane planting and replanting alleviates soil compaction, our data suggested that the effects are short-term with persistent, reoccurring soil consolidation that increases erosion risk over time. These soil physical changes, induced by LUC, were detected by quantitative soil physical properties as well as by visual evaluation of soil structure (VESS), an on-farm and user-friendly method for evaluating SQ. The SMAF efficiently detected overall SQ response to LUC and it could be reliably used under Brazilian soil conditions. Furthermore, since all of the SQI values developed in this study were able to rank SQ among land uses. We recommend that simpler and more cost-effective SQI strategies using a small number of carefully chosen soil indicators, such as: pH, P, K, VESS and SOC, and proportional weighting within of each soil sectors (chemical, physical and biological) be used as a protocol for SQ assessments in Brazilian sugarcane areas. The SMAF and SQI scores suggested that long-term conversion from native vegetation to extensive pasture depleted overall SQ, driven by decreases in chemical, physical and biological indicators. In contrast, conversion from pasture to sugarcane had no negative impacts on overall SQ, mainly because chemical improvements offset negative impacts on biological and physical indicators. Therefore, our findings can be used as scientific base by farmers, extension agents and public policy makers to adopt and develop management strategies that sustain and/or improving SQ and the sustainability of sugarcane production in Brazil.

A high-efficiency solar rankine engine with isothermal expansion

Though the principle of the solar Rankine cycle is well known, with several examples reported in the literature, there is yet a scarcity of engines that could be efficiently applied in small-scale (<100 KW) applications. Hence, this paper presents a variant of the engine that uses an isothermal expansion to achieve a theoretical efficiency close to the Carnot limit. Generation of steam inside the power cylinder obviates the need for an external boiler. The device is suitable for slow-moving applications and is of particular interest for driving a batch-desalination process. Preliminary experiments have shown cycle efficiency of 16%, and a high work ratio of 0.997. ©The Author 2013. Published by Oxford University Press. All rights reserved.

Calculation of mutual information for nonlinear communication channel at large signal-to-noise ratio

Using the path-integral technique we examine the mutual information for the communication channel modeled by the nonlinear Schrödinger equation with additive Gaussian noise. The nonlinear Schrödinger equation is one of the fundamental models in nonlinear physics, and it has a broad range of applications, including fiber optical communications - the backbone of the internet. At large signal-to-noise ratio we present the mutual information through the path-integral, which is convenient for the perturbative expansion in nonlinearity. In the limit of small noise and small nonlinearity we derive analytically the first nonzero nonlinear correction to the mutual information for the channel.

Mixing colours: An ICT tool based on a semiotic framework for mathematical meaning-makng about ratio and fractions

This paper reports on the research and development of an ICT tool to facilitate the learning of ratio and fractions by adult prisoners. The design of the ICT tool was informed by a semiotic framework for mathematical meaning-making. The ICT tool thus employed multiple semiotic resources including topological, typological, and social-actional resources. The results showed that individual semiotic resource could only represent part of the mathematical concept, while at the same time it might signify something else to create a misconception. When multiple semiotic resources were utilised the mathematical ideas could be better learnt.

Mixing colours : an ICT tool based on a semiotic framework for mathematical meaning-making about ratio and fractions

This paper reports on the research and development of an ICT tool to facilitate the learning of ratio and fractions by adult prisoners. The design of the ICT tool was informed by a semiotic framework for mathematical meaning-making. The ICT tool thus employed multiple semiotic resources including topological, typological, and social-actional resources. The results showed that individual semiotic resource could only represent part of the mathematical concept, while at the same time it might signify something else to create a misconception. When multiple semiotic resources were utilised the mathematical ideas could be better learnt.

Improvement to Chinese information retrieval by incorporating word segmentation and query expansion

The increasing diversity of the Internet has created a vast number of multilingual resources on the Web. A huge number of these documents are written in various languages other than English. Consequently, the demand for searching in non-English languages is growing exponentially. It is desirable that a search engine can search for information over collections of documents in other languages. This research investigates the techniques for developing high-quality Chinese information retrieval systems. A distinctive feature of Chinese text is that a Chinese document is a sequence of Chinese characters with no space or boundary between Chinese words. This feature makes Chinese information retrieval more difficult since a retrieved document which contains the query term as a sequence of Chinese characters may not be really relevant to the query since the query term (as a sequence Chinese characters) may not be a valid Chinese word in that documents. On the other hand, a document that is actually relevant may not be retrieved because it does not contain the query sequence but contains other relevant words. In this research, we propose two approaches to deal with the problems. In the first approach, we propose a hybrid Chinese information retrieval model by incorporating word-based techniques with the traditional character-based techniques. The aim of this approach is to investigate the influence of Chinese segmentation on the performance of Chinese information retrieval. Two ranking methods are proposed to rank retrieved documents based on the relevancy to the query calculated by combining character-based ranking and word-based ranking. Our experimental results show that Chinese segmentation can improve the performance of Chinese information retrieval, but the improvement is not significant if it incorporates only Chinese segmentation with the traditional character-based approach. In the second approach, we propose a novel query expansion method which applies text mining techniques in order to find the most relevant words to extend the query. Unlike most existing query expansion methods, which generally select the highly frequent indexing terms from the retrieved documents to expand the query. In our approach, we utilize text mining techniques to find patterns from the retrieved documents that highly correlate with the query term and then use the relevant words in the patterns to expand the original query. This research project develops and implements a Chinese information retrieval system for evaluating the proposed approaches. There are two stages in the experiments. The first stage is to investigate if high accuracy segmentation can make an improvement to Chinese information retrieval. In the second stage, a text mining based query expansion approach is implemented and a further experiment has been done to compare its performance with the standard Rocchio approach with the proposed text mining based query expansion method. The NTCIR5 Chinese collections are used in the experiments. The experiment results show that by incorporating the text mining based query expansion with the hybrid model, significant improvement has been achieved in both precision and recall assessments.