Biochar: pyrogenic carbon for agricultural use: a critical review.

O biocarvão (biomassa carbonizada para uso agrícola) tem sido usado como condicionador do solo em todo o mundo, e essa tecnologia é de especial interesse para o Brasil, uma vez que tanto a ?inspiração?, que veio das Terras Pretas de Índios da Amazônia, como o fato de o Brasil ser o maior produtor mundial de carvão vegetal, com a geração de importante quantidade de resíduos na forma de finos de carvão e diversas biomassas residuais, principalmente da agroindústria, como bagaço de cana, resíduos das indústrias de madeira, papel e celulose, biocombustíveis, lodo de esgoto etc. Na última década, diversos estudos com biocarvão têm sido realizados e atualmente uma vasta literatura e excelentes revisões estão disponíveis. Objetivou-se aqui não fazer uma revisão bibliográfica exaustiva, mas sim uma revisão crítica para apontar alguns destaques na pesquisa sobre biochar. Para isso, foram selecionados alguns temaschave considerados críticos e relevantes e fez-se um ?condensado? da literatura pertinente, mais para orientar as pesquisas e tendências do que um mero olhar para o passad

Drug utilization patterns in the global context: A systematic review

Objectives Standard drug use indicators have been developed by the World Health Organization/International Network for Rational Use of Drugs (WHO/INRUD). The purpose of this systematic review was to examine and report the current status of health facilities in different regions of the world in terms of drug use based on WHO/INRUD core drug use indicators. Design Systematic review of the literature following PRISMA guidelines. Methods The INRUD bibliography, WHO archives, Google Scholar, Medline, PubMed, SpringerLink, ScienceDirect and Management Sciences for Health (MSH) resource databases were searched between 1985 and 2015 for studies -containing 12 WHO/INRUD core drug use indicators. Secondary data sources were also searched. Results Four hundred and sixty three studies were retrieved and 398 were excluded as they did not provide relevant information or fulfill the selection criteria. Sixty articles met the criteria and were selected for final review. With respect to prescribing indicators, studies of “drug use” showed mixed patterns across geographic regions. Overall trends in “patient-care” and “facility-specific” indicators were similar across most of the World Bank regions. However, based on the Index of Rational Drug Use (IRDU) values, East Asia and the Pacific region demonstrated relatively better drug use practices compared with other regions. Conclusions This systematic review revealed that the drug use practices in all regions of the world are suboptimal. A regulated, multi-disciplinary, national body with adequate funding provided by governments throughout the world are a basic requirement for coordination of activities and services, to improve the rational use of drugs at a local level

Multi-sensor fusion based on multiple classifier systems for human activity identification

Multimodal sensors in healthcare applications have been increasingly researched because it facilitates automatic and comprehensive monitoring of human behaviors, high-intensity sports management, energy expenditure estimation, and postural detection. Recent studies have shown the importance of multi-sensor fusion to achieve robustness, high-performance generalization, provide diversity and tackle challenging issue that maybe difficult with single sensor values. The aim of this study is to propose an innovative multi-sensor fusion framework to improve human activity detection performances and reduce misrecognition rate. The study proposes a multi-view ensemble algorithm to integrate predicted values of different motion sensors. To this end, computationally efficient classification algorithms such as decision tree, logistic regression and k-Nearest Neighbors were used to implement diverse, flexible and dynamic human activity detection systems. To provide compact feature vector representation, we studied hybrid bio-inspired evolutionary search algorithm and correlation-based feature selection method and evaluate their impact on extracted feature vectors from individual sensor modality. Furthermore, we utilized Synthetic Over-sampling minority Techniques (SMOTE) algorithm to reduce the impact of class imbalance and improve performance results. With the above methods, this paper provides unified framework to resolve major challenges in human activity identification. The performance results obtained using two publicly available datasets showed significant improvement over baseline methods in the detection of specific activity details and reduced error rate. The performance results of our evaluation showed 3% to 24% improvement in accuracy, recall, precision, F-measure and detection ability (AUC) compared to single sensors and feature-level fusion. The benefit of the proposed multi-sensor fusion is the ability to utilize distinct feature characteristics of individual sensor and multiple classifier systems to improve recognition accuracy. In addition, the study suggests a promising potential of hybrid feature selection approach, diversity-based multiple classifier systems to improve mobile and wearable sensor-based human activity detection and health monitoring system. © 2019, The Author(s)

Development of Interior and Exterior Automotive Plastics Parts Using Kenaf Fiber Reinforced Polymer Composite

The integration of sustainable components in automotive parts is in growing demand. This study involves the entire process, from the extraction of kenaf cellulosic fibers to the fabrication of automotive parts by applying injection molding (sample only) and Resin Transfer Molding (RTM) techniques. Fibers were pretreated, followed by moisture content analysis before composite fabrication. The composite was fabricated by integrating the fibers with polypropylene, maleic anhydride polypropylene (MAPP), unsaturated polyester, and epoxy resin. Mechanical tests were done following ASTM D5083, ASTM D256, and ASTM D5229 standards. The RTM technique was applied for the fabrication of parts with reinforced kenaf long bast fibers. RTM indicated a higher tensile strength of 55 MPa at an optimal fiber content of 40%. Fiber content from 10% to 40% was found to be compatible with or better than the control sample in mechanical tests. Scanning Electron Microscope (SEM) images showed both fiber-epoxy-PE bonding along with normal irregularities in the matrix. The finite element simulations for the theoretical analysis of the mechanical performance characteristics showed higher stiffness and strength in the direction parallel to the fiber orientation. This study justifies the competitiveness of sustainable textile fibers as a reinforcement for plastics to use in composite materials for automotive industries