Phosphorus Magnetic Resonance Spectroscopy In The Investigation Of Temporal Lobe Epilepsy: 'reading Between The Lines' Of Metabolic Abnormalities

742899

A Comparative Analysis of Phytovolume Estimation Methods Based on UAV-Photogrammetry and Multispectral Imagery in a Mediterranean Forest

Management and control operations are crucial for preventing forest fires, especially in Mediterranean forest areas with dry climatic periods. One of them is prescribed fires, in which the biomass fuel present in the controlled plot area must be accurately estimated. The most used methods for estimating biomass are time-consuming and demand too much manpower. Unmanned aerial vehicles (UAVs) carrying multispectral sensors can be used to carry out accurate indirect measurements of terrain and vegetation morphology and their radiometric characteristics. Based on the UAV-photogrammetric project products, four estimators of phytovolume were compared in a Mediterranean forest area, all obtained using the difference between a digital surface model (DSM) and a digital terrain model (DTM). The DSM was derived from a UAV-photogrammetric project based on the structure from a motion algorithm. Four different methods for obtaining a DTM were used based on an unclassified dense point cloud produced through a UAV-photogrammetric project (FFU), an unsupervised classified dense point cloud (FFC), a multispectral vegetation index (FMI), and a cloth simulation filter (FCS). Qualitative and quantitative comparisons determined the ability of the phytovolume estimators for vegetation detection and occupied volume. The results show that there are no significant differences in surface vegetation detection between all the pairwise possible comparisons of the four estimators at a 95% confidence level, but FMI presented the best kappa value (0.678) in an error matrix analysis with reference data obtained from photointerpretation and supervised classification. Concerning the accuracy of phytovolume estimation, only FFU and FFC presented differences higher than two standard deviations in a pairwise comparison, and FMI presented the best RMSE (12.3 m) when the estimators were compared to 768 observed data points grouped in four 500 m2 sample plots. The FMI was the best phytovolume estimator of the four compared for low vegetation height in a Mediterranean forest. The use of FMI based on UAV data provides accurate phytovolume estimations that can be applied on several environment management activities, including wildfire prevention. Multitemporal phytovolume estimations based on FMI could help to model the forest resources evolution in a very realistic way

Chronic liver disease staging classification based on ultrasound, clinical and laboratorial data

In this work the identification and diagnosis of various stages of chronic liver disease is addressed. The classification results of a support vector machine, a decision tree and a k-nearest neighbor classifier are compared. Ultrasound image intensity and textural features are jointly used with clinical and laboratorial data in the staging process. The classifiers training is performed by using a population of 97 patients at six different stages of chronic liver disease and a leave-one-out cross-validation strategy. The best results are obtained using the support vector machine with a radial-basis kernel, with 73.20% of overall accuracy. The good performance of the method is a promising indicator that it can be used, in a non invasive way, to provide reliable information about the chronic liver disease staging

Efeitos locais de políticas públicas federais: observações a partir da Lei de Informática no desenvolvimento do setor de software de Campina Grande, PB

Fundamentado na observação de estudo de caso da dinâmica interativa entre agentes do proto-sistema local de inovação em software de Campina Grande, Paraíba, estimulada pela Lei de Informática, o presente artigo objetiva chamar atenção para a importância da interferência de políticas públicas nacionais sobre o espaço local. Como pano de fundo, está a noção de aprendizado por interação, apontada como importante aspecto do processo de inovação e de estratégias recentes de desenvolvimento regional. Neste contexto, Campina Grande apresentaria elementos objetivos para implementar estratégia de desenvolvimento baseada em inovação, guardadas as peculiaridades do retardatário desenvolvimento brasileiro. Observam-se ali instituições de produção de conhecimento e suporte à inovação em software que têm estimulado a criação de um aglomerado de pequenas e micro empresas do setor. Em função da existência na cidade de reconhecidas competências de pesquisa, particularmente na UFCG, estas vêm recebendo aportes expressivos de grandes empresas estimuladas pela Lei de Informática, cujo objetivo é ampliar a capacidade inovativa da indústria nacional de bens de informática, tanto aquela realizada dentro das firmas como em parceria entre estas e instituições de pesquisa. A lei prevê também que parte dos investimentos em P&D seja aplicada nas regiões Norte, Nordeste e Centro-oeste. Embora contemple, assim, objetivos de redução de disparidades regionais e o crescimento do software nacional, o argumento aqui defendido é que a Lei de Informática não propicia os efeitos esperados de adensamento da estrutura produtiva nacional, especialmente em regiões menos desenvolvidas. O estudo das interações de P&D observadas em Campina Grande mostra que o atual formato da Lei pode propiciar drenagem de recursos locais e barreiras às interações entre competências de pesquisa e estrutura produtiva locais. O estudo sugere que o marco regulatório seja aperfeiçoado, considerando-se a importância da inovação tanto para o desenvolvimento do setor, caracterizado por grande dinamismo inovativo, como para o desenvolvimento regional.

3D electrical structure definition of aquifer systems in the Kalahari basin in Southern Angola based on legacy data reprocessing

ABSTRACT: The Kalahari-Ohangwena transboundary aquifer system, recently identified in Northern Namibia, comprises 3 major aquifers with very different characteristics. The shallowest is discontinuous and with limited reserves, but it has local importance in water supply for the population, since it is easy to reach, and often presents good hydrochemical quality. An intermediate deeper aquifer is characterized by high salinity while the deepest aquifer, also mostly saline, can present zones with fresh water. However, the latter is located at considerable depths and is shaped by the bottom of the basin basement. There hasn't been a systematic hydrogeological data acquisition for decades in this area of Angola, but legacy electrical resistivity data reprocessing from geophysical surveys conducted >50 years ago in the Cunene Province allowed the construction of a quasi-3D geoelectrical model for the Angolan side of KOH aquifer system in the Cuvelai-Etosha basin. This model is based on 482 vertical electrical soundings carried out in 1966-67, using the Schlumberger array, that contribute to confirming the presence of the Kalahari-Ohangwena aquifer system in Angola. The obtained quasi-3D model highlights the geoelectrical features of hard bedrock and is validated with other hydrogeological and geophysical information. The quasi-3D electrical resistivity data is interpreted using selected boreholes and two time-domain electro-magnetics transects carried out in Namibia, in the 2000s. Although both geophysical data acquisitions were >40 years apart, the results show a very good correlation between the deeper aquifer and the aquitard separating the intermediate aquifer from the deeper aquifer either with the results from Namibia or the borehole data. This is a direct result of the lack of alteration in the hydraulic conditions over these decades, without significant anthropogenic activity and negligible extraction from deep wells. Based on this analysis, the original dataset was considered a reliable source and this quasi-3D model was validated. Furthermore, the model can be considered in the future as an important tool for groundwater resources management, as well as a good starting point for further hydrogeological research in the province of Cunene.info:eu-repo/semantics/publishedVersio

Characterising the agriculture 4.0 landscape - Emerging trends, challenges and opportunities

ReviewInvestment in technological research is imperative to stimulate the development of sustainable solutions for the agricultural sector. Advances in Internet of Things, sensors and sensor networks, robotics, artificial intelligence, big data, cloud computing, etc. foster the transition towards the Agriculture 4.0 era. This fourth revolution is currently seen as a possible solution for improving agricultural growth, ensuring the future needs of the global population in a fair, resilient and sustainable way. In this context, this article aims at characterising the current Agriculture 4.0 landscape. Emerging trends were compiled using a semi-automated process by analysing relevant scientific publications published in the past ten years. Subsequently, a literature review focusing these trends was conducted, with a particular emphasis on their applications in real environments. From the results of the study, some challenges are discussed, as well as opportunities for future research. Finally, a high-level cloud-based IoT architecture is presented, serving as foundation for designing future smart agricultural systems. It is expected that this work will positively impact the research around Agriculture 4.0 systems, providing a clear characterisation of the concept along with guidelines to assist the actors in a successful transition towards the digitalisation of the sectorinfo:eu-repo/semantics/publishedVersio