Use of Landsat data for automatic classification and area estimation of sugar-cane plantation in Sao Paulo state,Brazil

Sugar-cane (saccharum spp.) plantations in São Paulo State were classified automatically using an lmage-100 system and Landsat digital data. Ten segments of size 10 × 20 km were aerially photographed and used as training areas for automatic classification. The study area was covered by four Landsat paths, 235, 236, 237 and 238. The percentages of overall correct classification for these paths range from 79·56 per cent for path 238 to 95·59 per cent for path 237.     

Electrochemical Regeneration of Activated Carbon Saturated with Toluene

The electrochemical regeneration of an activated carbon, previously saturated with toluene by gas phase adsorption, was studied. Cathodic and anodic regeneration methods were analyzed using a small batch electrochemical cell. In both cases, a stripping efficiency close to 100% was obtained under appropriate conditions of potential, current, and time of electrolysis. Successive loading and regeneration cycles of the activated carbon were performed under cathodic conditions without loss of the adsorption properties of the activated carbon, thus achieving a high regeneration efficiency (close to 99%). This electrochemical method is very effective for regeneration of activated carbon compared to conventional thermal regeneration as it does not modify the porous texture of the material.     

A GENERALIZATION OF ENTROPY USING DEMPSTER-SHAFER THEORY

This paper considers a “body of evidence” on a finite set X, determined by a “basic probability assignment” (BPA) on X. This land of information on the set AT is ambiguous and so, in the applications, it is important to measure the degree of uncertainty involved in each BPA. In fact, several measures of uncertainty and entropy have been formulated and investigated in the setting of Dempster-Shafer Theory of Evidence. In this paper, we use the formal analogy underlying many of those measures of uncertainty. This moves us to define a family of fuzzy measures associated with each BPA. Thus, we propose a general formulation of the entropy of a BPA. Several known measures of entropy (including measures of imprecision and of randomness), as well as other new measures, are subsumed under our general scheme as particular cases. The basic properties of all those measures of entropy are also studied.     

FUZZY REASONING IN A MULTIAGENT SYSTEM OF SURVEILLANCE SENSORS TO MANAGE COOPERATIVELY THE SENSOR-TO-TASK ASSIGNMENT PROBLEM

In this work, a surveillance network composed of a set of sensors and a fusion center is designed as a multiagent system. Negotiation among sensors (agents) is proposed to solve the task-to-sensor assignment problem (the allocation of tasks to sensors), addressing several aspects. First, the fusion center determines the tasks (system tasks) to be performed by the network at each management cycle. To do that, a fuzzy reasoning system determines the priorities of these system tasks by means of a symbolic inference process using the fused data received from all sensors. In addition, a fuzzy reasoning process, similar to that performed in the fusion center, is proposed to evaluate the priority of local tasks (sensor tasks) now executed by each sensor. The network coordination procedure will be based on the system-task priorities, computed in the fusion center, and on the local priorities evaluated in each sensor. Priority values for system and sensor tasks will be the basis to guide a negotiation process among sensors in the multiagent system. The validity of the fuzzy reasoning approach is supported by the fact that it has been able to manage environmental situations in a similar way as experienced human operators do. Included results illustrate how the negotiation scheme, based on task priority and measured through their time-variant priority, allows the adaption of sensor operation to changing situations.     

MULTI-AGENT SYSTEMS FOR DECISION SUPPORT: A CASE STUDY IN THE TRANSPORTATION MANAGEMENT DOMAIN

This article describes how agent and knowledge technology can be used to build advanced software systems that support operational decision making in complex domains. In particular, we present an abstract architecture and design guidelines for agent-based decision support systems. We illustrate our approach with a case study in the transportation management domain.     

Improvement of transfection with reprogramming factors in urinederived cells

Human-induced pluripotent stem cells (iPSCs) are an accessible source of adult-derived, patient-specific pluripotent stem cells for use in basic research, drug discovery, disease modeling, and stem cell therapy. Improving the accessibility of methods to obtain iPSCs regardless of the cell source can enhance their clinical application. Therefore, our purpose is to report a simple protocol to obtain iPS-like cells from urine-derived renal epithelial cells (RECs) using different extracellular matrices and transfection reagents. In this study, we began by culturing urine-derived cells from healthy donors to establish a primary culture of renal epithelial cells, followed by their characterization. Subsequently, we generated iPS-like cells by transfecting renal epithelial cells (RECs) with vectors expressing Oct4, Sox2, L-Myc, Lin-28, and Klf4, and we compared the efficacy of different extracellular matrices and transfection reagents. The resultant iPS-like cells showed a human embryonic stem cell-like morphology and expressed the specific pluripotency markers Oct3/4, Nanog, Lin28, and Klf4. We concluded that Lipofectamine Stem Cell transfection reagent is more effective than FuGENE in obtaining iPS-like cells under the conditions tested. Moreover, the three matrices are similar in their efficiency of obtaining iPS-like cells. This report provides an experimental protocol for obtaining and generating iPS-like cells from urine samples for further cell therapy research on different human diseases.