Yield and Economic Performance of Organic and Conventional Cotton-Based Farming Systems – Results from a Field Trial in India

The debate on the relative benefits of conventional and organic farming systems has in recent time gained significant interest. So far, global agricultural development has focused on increased productivity rather than on a holistic natural resource management for food security. Thus, developing more sustainable farming practices on a large scale is of utmost importance. However, information concerning the performance of farming systems under organic and conventional management in tropical and subtropical regions is scarce. This study presents agronomic and economic data from the conversion phase (2007–2010) of a farming systems comparison trial on a Vertisol soil in Madhya Pradesh, central India. A cotton-soybean-wheat crop rotation under biodynamic, organic and conventional (with and without Bt cotton) management was investigated. We observed a significant yield gap between organic and conventional farming systems in the 1st crop cycle (cycle 1: 2007–2008) for cotton (229%) and wheat (227%), whereas in the 2nd crop cycle (cycle 2: 2009–2010) cotton and wheat yields were similar in all farming systems due to lower yields in the conventional systems. In contrast, organic soybean (a nitrogen fixing leguminous plant) yields were marginally lower than conventional yields (21% in cycle 1, 211% in cycle 2). Averaged across all crops, conventional farming systems achieved significantly higher gross margins in cycle 1 (+29%), whereas in cycle 2 gross margins in organic farming systems were significantly higher (+25%) due to lower variable production costs but similar yields. Soybean gross margin was significantly higher in the organic system (+11%) across the four harvest years compared to the conventional systems. Our results suggest that organic soybean production is a viable option for smallholder farmers under the prevailing semi-arid conditions in India. Future research needs to elucidate the long-term productivity and profitability, particularly of cotton and wheat, and the ecological impact of the different farming systems

Cardiac renewing: interstitial Cajal-like cells nurse cardiomyocyte progenitors in epicardial stem cell niches

Recent studies suggested that various cell lineages exist within the subepicardium and we supposed that this area could host cardiac stem cell niches (CSCNs). Using transmission electron microscopy, we have found at least 10 types of cells coexisting in the subepicardium of normal adult mice: adipocytes, fibroblasts, Schwann cells and nerve fibres, isolated smooth muscle cells, mast cells, macrophages, lymphocytes, interstitial Cajal-like cells (ICLCs) and cardiomyocytes progenitors (CMPs). The latter cells, sited in the area of origin of coronary arteries and aorta, showed typical features of either very immature or developing cardiomyocytes. Some of these cells were connected to each other to form columns surrounded by a basal lamina and embedded in a cellular network made by ICLCs. Complex intercellular communication occurs between the ICLCs and CMPs through electron-dense nanostructures or through shed vesicles. We provide here for the first time the ultrastructural description of CSCN in the adult mice myocardium, mainly containing ICLCs and CMPs. The existence of resident CMPs in different developmental stages proves that cardiac renewing is a continuous process. We suggest that ICLCs might act as supporting nurse cells of the cardiac niches and may be responsible for activation, commitment and migration of the stem cells out of the niches. Briefly, not only resident cardiac stem cells but also ICLCs regulate myocyte turnover and contribute to both cardiac cellular homeostasis and endogenous repair/remodelling after injuries

SPORK: A SUMMARIZATION PIPELINE FOR ONLINE REPOSITORIES OF KNOWLEDGE

The web 2.0 era has ushered an unprecedented amount of interactivity on the Internet resulting in a flood of user-generated content. This content is often unstructured and comes in the form of blog posts and comment discussions. Users can no longer keep up with the amount of content available, which causes developers to start relying on natural language techniques to help mitigate the problem. Although many natural language processing techniques have been employed for years, automatic text summarization, in particular, has recently gained traction. This research proposes a graph-based, extractive text summarization system called SPORK (Summarization Pipeline for Online Repositories of Knowledge). The goal of SPORK is to be able to identify important key topics presented in multi-document texts, such as online comment threads. While most other automatic summarization systems simply focus on finding the top sentences represented in the text, SPORK separates the text into clusters, and identifies different topics and opinions presented in the text. SPORK has shown results of managing to identify 72\% of key topics present in any discussion and up to 80\% of key topics in a well-structured discussion

Organic coffee production A comparative study of organic and conventional smallholdings in Costa Rica

Available from British Library Document Supply Centre-DSC:DXN040296 / BLDSC - British Library Document Supply CentreSIGLEGBUnited Kingdo

Nonblocking Distributed State-Tree-Structures

Discrete-event systems encompass a wide variety of today’s systems including manufacturing cells and networking protocols. To prevent a system from entering a forbidden state and to ensure nonblockingness, it is desirable to control, or restrict, the behavior of such a system. The supervisory control paradigm allows for the synthesis of a supervisor which produces the necessary feedback to appropriately restrict the behavior of the system. When discrete-event systems are described modularly, the number of states grows exponentially with the number of components; this is known as the state-space explosion problem and is one of the central challenges of supervisory control. State-tree-structures and modular approaches are strategies which address issues of complexity in supervisory control. However, both still suffer from heavy computations when ensuring nonblockingness. In this thesis we introduce a novel procedure for a more efficient check for nonblockingness of state-tree-structures. This is accomplished using the structural properties of state-tree-structures to separate the shared events from the unshared events of a system. We build a recursive two-layer hierarchy in which the bottom level contains the parallel components, and the top level is an abstracted view containing the shared events between these components. To maintain reachability properties in the top level, the components of the system must be clustered such that in each cluster one can reach every outgoing transition from each incoming transition. This is formalized as a uni- versally reachable cluster. We introduce an algorithm which optimally clusters system components in such a manner. This clustering allows us to reformulate the conditions of nonblockingness in a hierarchical manner; the system is nonblocking if and only if both the top level and each component in the bottom level are nonblocking. Given a small top level and that the bottom level has no shared events, the components can be analyzed independently and in parallel, thus drastically reducing computation times. To verify performance, the universally reachable clustering algorithm was implemented and analyzed for a set of random automata and was found to reduce the number of states on average by 95%. Additionally, our entire procedure to verify nonblockingness was applied to a practical production cell example in which we achieved a 99.99% reduction in the number of states to be examined.Computer EngineeringSoftware TechnologyElectrical Engineering, Mathematics and Computer Scienc