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Specific techniques of spectral analysis to determine the nutritional stress caused by sulfur (S) may allow the early detection of its deficiency and directed supplementation in the corrective fert...

This paper explores two new weightless neural network models, Regression WiSARD and ClusRegression WiSARD, in the challenging task of predicting the total palm oil production of a set of 28 (twenty eight) differently located sites under different climate and soil profiles. Both models were derived from Kolcz and Allinson’s n-Tuple Regression weightless neural model and obtained mean absolute error (MAE) rates of 0.09097 and 0.09173, respectively. Such results are very competitive with the state-of-the-art (0.07983), whilst being four orders of magnitude faster during the training phase. Additionally the models have been tested on three classic regression datasets, also presenting competitive performance with respect to other models often used in this type of task.

Unmanned aircraft systems (UAS) have advanced rapidly enabling low-cost capture of high-resolution images with cameras, from which three-dimensional photogrammetric point clouds can be derived. More recently UAS equipped with laser scanners, or lidar, have been employed to create similar 3D datasets. While airborne lidar (originally from conventional aircraft) has been used effectively in forest systems for many years, the ability to obtain important tree features such as height, diameter at breast height, and crown dimensions is now becoming feasible for individual trees at reasonable costs thanks to UAS lidar. Getting to individual tree resolution is crucial for detailed phenotyping and genetic analyses. This study evaluates the quality of three three-dimensional datasets from three sensors—two cameras of different quality and one lidar sensor—collected over a managed, closed-canopy pine stand with different planting densities. For reference, a ground-based timber cruise of the same pine stand is also collected. This study then conducted three straightforward experiments to determine the quality of the three sensors’ datasets for use in automated forest inventory: manual mensuration of the point clouds to (1) detect trees and (2) measure tree heights, and (3) automated individual tree detection. The results demonstrate that, while both photogrammetric and lidar data are well-suited for single-tree forest inventory, the photogrammetric data from the higher-quality camera is sufficient for individual tree detection and height determination, but that lidar data is best. The automated tree detection algorithm used in the study performed well with the lidar data, detecting 98% of the 2199 trees in the pine stand, but fell short of manual mensuration within the lidar point cloud, where 100% of the trees were detected. The manually-mensurated heights in the lidar dataset correlated with field measurements at r = 0.95 with a bias of −0.25 m, where the photogrammetric datasets were again less accurate and precise.

The purpose of this study was to evaluate the effects of systemic administration of the probiotic Bifidobacterium animalis subsp. lactis HN019 (HN019) on ligature-induced periodontitis in rats with experimental rheumatoid arthritis (RA). 28 rats were divided into four groups (n=7): RA (rheumatoid arthritis), RA/PROB (probiotic), RA/EP (experimental periodontitis) and RA/EP/PROB. From day zero, HN019 was added daily to the water of the PROB groups animals until the end of the experiment. From day seven, RA was induced. On day 28, in EP groups, ligatures were positioned around mandibular first molars and remained in position for 11 days, in order to induce periodontitis. The animals were euthanised on day 39. Microtomographic, histomorphometric, immunoenzymatic and microbiological analyses were performed. Data were statistically analysed (P

A contaminação de solos por mercúrio é um problema ambiental grave, com potencial de biomagnificação em cadeias alimentares e danos à saúde humana. O objetivo do presente trabalho foi avaliar o efeito de diferentes concentrações de HgO na germinação e desenvolvimento de plântulas de Sapindus saponária submetidas a escarificação mecânica. O experimento foi instalado em DIC com quatro repetições de 25 sementes, no esquema fatorial 4 x 2, sendo estudado o efeito de quatro concentrações de HgO em vermiculita (C1 – 0,000 g/cm3;.C2 – 0,025 g/cm3; C3 – 0,050 g/cm3 e C4 – 0,075 g/cm3) e de dois pré-tratamentos (P1 – Testemunha: sementes com tegumento intacto e P2 – escarificação mecânica do tegumento em esmeril elétrico). Avaliaram-se atributos relacionados à germinação e desenvolvimento de plântulas. Realizaram-se teste F, análise de regressão e teste t pareado, todos a 5,0 % de significância estatística. A escarificação mecânica do tegumento com esmeril elétrico favoreceu a embebição das sementes (100,0 %), germinação (85,25 %) e emissões de raízes laterais (70,0 %) e de parte aérea (76,25 %). A presença de mercúrio na vermiculita prejudicou o desenvolvimento das plântulas. Conclui-se que a escarificação mecânica do tegumento com esmeril elétrico pode ser indicado para superar a dormência das sementes de S. saponaria. Esta espécie tolera pequenas concentrações de HgO (0,0045 g/cm3) sem causar maiores danos ao seu crescimento e acúmulo de massa verde.

The paradigm of the Internet of Everything (IoE) adds value to Internet of Things (IoT) in connections among people, processes, data, and things. However, knowledge creation process in IoE context still requires concerns to what extent connected sensors and actuators collaborates in value created and outcomes of IoE applications. This study focuses on the requirement and design approach for identification of critical knowledge within IoE domain though a knowledge ranking approach. Existing solutions for semantic definitions and taxonomies in IoE are reviewed for this purpose. In addition, this work proposes the use of a knowledge-based taxonomy as the main driver for ranking knowledge in smart sensors as IoE enablers with a qualitative approach of its dimensions. To the best of our knowledge, this is the first work that comprehensively integrate a taxonomy concerning ranking knowledge in IoE applications.

The paradigm of the Internet of everything (IoE) is advancing toward enriching people’s lives by adding value to the Internet of things (IoT), with connections among people, processes, data, and things. This paper provides a survey of the literature on IoE research, highlighting concerns in terms of intelligence services and knowledge creation. The significant contributions of this study are as follows: (1) a systematic literature review of IoE taxonomies (including IoT); (2) development of a taxonomy to guide the identification of critical knowledge in IoE applications, an in-depth classification of IoE enablers (sensors and actuators); (3) validation of the defined taxonomy with 50 IoE applications; and (4) identification of issues and challenges in existing IoE applications (using the defined taxonomy) with regard to insights about knowledge processes. To the best of our knowledge, and taking into consideration the 76 other taxonomies compared, this present work represents the most comprehensive taxonomy that provides the orchestration of intelligence in network connections concerning knowledge processes, type of IoE enablers, observation characteristics, and technological capabilities in IoE applications.

This work takes into account the benefits of machine learning in order to estimate the valence of emotions on the OMG Empathy dataset, considering the information obtained from face expressions and dialogue of interlocutors. RegressionWiSARD and ClusRegressionWiSARD n-tuple regressors and its ensembles were employed to this end. The best performance achieved among all the combinations of weightless neural models considered (evaluated using the CCC metric) was 0.25 in validation set of the Personalized Track.

The aim of this study was to evaluate the use of leaf color pattern to analyze leaf nutrient concentrations in Eucalyptus and to establish relationships between color patterns and leaf nutrient concentrations. The study was carried out in Eucalyptus stands at 25 months old using three leaves from the lower of tree crowns classified into five color patterns of Munsell color charts for plant tissues. The principal component analyses and the self-organizing maps were used to aid in the classification of samples in leaf color patterns. Subsequently, the k-means cluster algorithm was performed. In principal component analysis, the 7.5 GY 8/8 leaf color pattern stood out from the others and it was mainly influenced by nitrogen, phosphorous, copper, and potassium concentrations. The samples of 7.5 GY 8/4 leaf color pattern did not present a great nitrogen, phosphorous, sulfur, copper and potassium concentrations as the 7.5 GY 8/8 neither a great manganese, calcium, boron, zinc and iron concentrations as others leaf color patterns. The self-organizing map provides a greater proximity between the 7.5 GY 8/8 and 7.5 GY 8/4 leaf color patterns and the others leaf color patterns were randomly distributed in the U-matrix. Although the k-means algorithm presented two clusters in both analyses, the self-organizing map presented a slight superiority than principal component analysis. Using leaf color patterns was possible to infer about leaf nutrient concentrations in Eucalyptus. Both methods were able to distinguish only the healthy leaves 7.5 GY 8/8 from those whose were in the leaf senescence process.

Diante da complexa relação entre reflectância foliar e aspectos fisiológicos da planta em dias e diferentes horários do dia, a pesquisa foi desenvolvida para averiguar e mensurar o grau da influência do dia e o período do dia em espectros de reflectância foliar de árvores de eucalipto. O experimento foi conduzido em um plantio de eucalipto clonal, híbrido espontâneo de Eucalyptus grandis com centroide nas coordenadas 18º 12’ 12,19’’S e 43º 34’ 20,28’’O. Em cada uma das cinco árvores-amostra escolhidas aleatoriamente, amostraram-se quatro folhas distribuídas em cada ponto cardeal. Todas as folhas selecionadas foram avaliadas nos dias 7, 8, 9 e 10 de dezembro de 2013, em dois períodos do dia: entre 8 e 9 horas e entre 15 e 16 horas. A leitura da reflectância foliar foi realizada utilizando um mini-espectrometro com posterior suavização e dessa forma realizou-se a análise de componentes principais e com posterior análise de agrupamento por dendrograma. No geral, a média das reflectâncias foliares no segundo dia foram as menores e as médias do terceiro dia maiores. Em média a reflectância foliar foi menor no período da manhã do que no período da tarde. O dia e o período do dia em que foi realizada a leitura influenciaram de forma aleatória na reflectância foliar de eucalipto. A reflectância foliar do eucalipto pode se alterar em um curto período de tempo, inclusive em um mesmo dia, o que indica a importância da padronização no horário de coleta para futuros estudos.

In this paper, we describe the second design cycle of Acropolis, a social computing platform that allows citizens to build and share their own narratives about complex or long-term news stories, by involving them in collaborative processing of news data called social curation. Experimental results produced through quantitative and qualitative evaluations have shown, by positive evidence, that our proposed approach was able to support citizen engagement in collaborative curation of news content. Using the action design research methodology, we concluded the second design cycle of the platform with a set of design recommendations for building similar platforms.

This paper presents the use of WiSARD and ClusWiSARD weightless neural networks models for the classification of the contraction and extension of Action Units, the facial muscles involved in emotive expressions. This is a complex problem due to the large number of very similar classes, and because it is a multi-label classification task, where the positive expression of one class can modify the response of the others. WiSARD and ClusWiSARD solutions are proposed and validated using the CK+ dataset, producing responses with accuracy of 89.66%. Some of the major works in the field are cited here, but a proper comparison is not possible due to a lack of appropriate information about such solutions, such as the subset of classes used and the time of training/testing. The contribution of this paper is in the pioneering use of weightless neural networks in an AUs classification task, in the unpublished application of the WiSARD and ClusWiSARD models in multi-label tasks and in the new unsupervised expansion of ClusWiSARD proposed here.

OBJECTIVE To evaluate the healing of critical size defects (CSDs) in calvaria of rats with osteoporosis induced by ovariectomy and treated with leukocyte- and platelet-rich fibrin (L-PRF) associated or not with bovine bone graft (XENO). MATERIAL AND METHODS A total of 32 rats underwent a bilateral ovariectomy procedure. After 3 months, one 5 mm in diameter CSD was created in the middle of the calvaria of each animal. In group C, defect was filled with blood clot only. In PRF, XENO, and PRF-XENO groups, defects were filled with 0.1 ml of L-PRF, 0.1 ml of XENO, and a mixture of 0.1 ml of L-PRF plus 0.1 ml of XENO, respectively. L-PRF compressed clots were used to cover the defects in PRF and PRF-XENO groups. Animals were submitted to euthanasia at 30 postoperative days. Histomorphometric, microtomographic, and immunohistochemical analyses were performed. RESULTS PRF-XENO group presented greater amount of neoformed bone (NB) when compared with XENO group, as well as higher expression of vascular endothelial growth factor (VEGF), osteocalcin (OCN), and bone morphogenetic protein (BMP-2/4) (p

Waiting for service is a problem faced by people from different countries and cultures. The problem of waiting in a queue can bring losses of quality of life and even economic problems. In this paper, we propose a mechanism for automatic detection of wait events via smartphones. This detection is done cooperatively by observing data collected from the user's smartphone's wifi and accelerometer sensors, and such information is compared to contributions made by other users. Experiments have proven the efficacy of this mechanism to be about 99% accurate.

This paper presents an observatory for registering applications that use participatory sensing to collect data. Cataloging these applications will aid the scientific community to exchange more information, facilitating the comparison between different initiatives. Through an initial research, the applications are categorized in areas usually considered in the literature. We propose a survey to validate the platform and also discuss the taxonomies created as a result of this survey. The main contributions of this paper include the classification of crowdsensing applications in different ontological categories, as well as the proposal of a technology platform that enables the distributed and collaborative cataloging of crowdsensing initiatives.

Nitrogen (N) has commonly been applied in Eucalyptus stands in Brazil and it has a direct relation with biomass production and chlorophyll content. Foliar N concentrations are used to diagnose soil and plant fertility levels and to develop N fertilizer application rates. Normally, foliar N is obtained using destructive methods, but indirect analyses using Vegetation Indexes (VIs) may be possible. The aim of this work was to evaluate VIs to estimate foliar N concentration in three Eucalyptus clones. Lower crown leaves of three clonal Eucalyptus plantations (25 months old) were classified into five color patterns using the Munsell Plant Tissue Color Chart. For each color, N concentration was determined by the Kjeldahl method and foliar reflectance was measured using a CI-710 Miniature Leaf Spectrometer. Foliar reflectance data were used to obtain the VIs and the VIs were used to estimate N concentrations. In the visible region, the relationship between N concentration and reflectance percentage was negative. The highest correlations between VIs and N concentrations were obtained by the Inflection Point Position (IPP, r = 0.97), Normalized Difference Red-Edge (reNDVI, r = 0.97) and Modified Red-Edge Normalized Difference Vegetation Index (mNDI, r = 0.97). Vegetation indexes on the red edge region provided the most accurate estimates of foliar N concentration. The reNDVI index provided the best N concentration estimates in leaves of different colors of Eucalyptus urophylla × grandis and Eucalyptus urophylla × urophylla (R2 = 0.97 and RMSE = 0.91 g kg−1).

The jatobá (Hymenaea courbaril L.) occurring throughout Central America and tropical countries in South America. This specie has great potential timber, in addition to fruits, leaves and bark with medicinal properties. This study was conducted to evaluate the effect of weed competition and intoxication by glyphosate in jatobá plants. The experiment was carried out with jatobá plants in field. Eleven months after planting it was held a floristic inventory in the area. One month after thisfloristic inventory, it was installed an experimental design with six randomized blocks and six treatments: manual weeding of weeds; no manual weeding or herbicide; and four glyphosate doses, 1.25, 2.5, 3.75 and 5.00 L ha-1. At 15, 30, 45, 60 and 90 days after tratment it was carried out a photochemical efficiency analysis of photosystem II, chlorophyll indices, number of leaflets, height and stem diameter of the plants. Based on physiological variables (F0, Fm, Fv/Fm and ETR), the jatobá plants recovered 60 days after treatments. Although the jatobá plants are tolerant to glyphosate and weed competition, jatobá plants under 1.25 and 2.50 L ha-1 of glyphosate reduces the increase in height around 50%, plants under 3.75 and 5.00 L ha-1 reduces around 90% and plants under weed competition around 70%.

The waiting time for customer services is a problem that affects most cultures and has been studied by the academic community for several decades from the standpoint of psychology, sociology, marketing and computer science. In this paper we present a review of the literature on the subject, and also propose a classification of approaches that deal with this problem. We also report our participatory effort in articulating requirements and functionalities of a design solution to address this problem. A series of interviews were conducted with stakeholders and other people involved in the problem of waiting time delays in customer services, allowing requirements to be posed and validated through a survey. Finally, we present the latest details of an application being developed to address this problem and the final conclusions.

O gênero Hymenaea pertence à família Leguminosae, subfamília Caesalpinoideae, com nome popular de jatobá. No gênero Hymenaea, foram descritas aproximadamente 25 espécies. Já no Brasil, verifica-se a presença de 13 espécies, com destaque para a Hymenaea martiana Hayne e a Hymenaea courbaril Linneaus. Na literatura, há vários trabalhos que tratam principalmente da quebra de dormência das sementes e da produção de mudas, sobretudo da espécie Hymenaea courbaril Linneaus, porém essas avaliações por matriz ainda são incipientes. Este trabalho teve por objetivo avaliar e comparar a germinação e o crescimento inicial de mudas entre as espécies e as matrizes de Hymenaea martiana Hayne e Hymenaea courbaril Linneaus. Foram desenvolvidos dois experimentos: o primeiro avaliou a germinação, e o segundo, o crescimento inicial de mudas. As duas espécies avaliadas apresentaram comportamentos distintos entre a germinação e o crescimento inicial das mudas, sendo a Hymenaea courbaril Linneaus a espécie com maior média para ambas variáveis, porém não apresentou variabilidade fenotípica entre matrizes. The Hymenaea genus belongs to the family Leguminosae, subfamily Caesalpinoideae with the common name jatobá. Approximately 25 species have been described in the genus Hymenaea and 13 of them are present in Brazil. Among them we can highlight the species Hymenaea martiana Hayne and Hymenaea courbaril Linneaus. In literature, there are several studies dealing mainly the dormancy breakage and the seedling production, mainly with Hymenaea coubaril Linneaus, but these reviews per matrices are incipient. This study aimed to evaluate and compare the germination and seedling growth between species and between matrices of the Hymenaea martiana Hayne and Hymenaea courbaril Linneaus. Two experiments were conducted: the first evaluated the germination and the second the seedlings growth. The two species studied showed different behavior between germination and the seedling growth, with Hymenaea courbaril Linneaus showing the greatest average for both variables. However, this did not show phenotypic variability between matrices.

This work in progress proposes the use of vivid impressions of users to monitor the waiting and service time in the provision of public and private services. The solution consists of an environment in which users can report the time spent waiting for the provision of a particular service. For the strategy to be successful, this account should be done through a simplified interface, preferably mobile, that takes advantage of the user's location knowledge. This approach uses the crowd collaboration to achieve some goal, and has been used in applications such as Waze.

Introduction Allergy is strongly associated with poor sleep quality, being sleep disruption and sleep disordered breathing (SDB) the most common alterations, both in asthma and allergic rhinitis (AR). Nasal obstruction and congestion are a risk factor for SDB and for its persistence after adenotonsillectomy (AT). This study aims to describe and characterize the population with respiratory allergic disease (rhinitis and asthma) referred to specialized sleep clinic for snoring and/or breathing pauses and its follow-up. Materials and methods Retrospective descriptive study, reviewing the clinical files of patients referred to our sleep clinic for SDB who had a history of asthma and/or AR from January 2008 to December 2012. Allergy was considered present if reported by the parents in child past medical history. Allergic patients represent 15.8% (n = 58) out of the total of the children referred for SDB. Descriptive and comparative (non-parametric tests) statistics were done. Results All the 68 children files were reviewed. Male gender predominates (42; 72.4%) and the median age at first observation was 9 (3; 16) years. Most children had a regular growth (56; 96.6%). Regarding respiratory allergic disease, 15 (25.9%) children had rhinitis, 27 (46.6%) had asthma, 16 (27.6%) had both. Fourteen (24.1%) had been previously submitted to TA. Family history of atopy was frequent (24; 41.4%), as well as family history of snoring (28; 48.3%). Most children were under allergy medication (47; 80.0%) on first observation. Of the 50 (86.2%) children who underwent polysomnography, 17 (29.3%) had a fragmented sleep, with multiple arousals; the median apnea-hypopnea index (AHI) was 0.42/h (0.00; 3.00), and the median desaturation index (DSI) was 1.42/h (0.00;7.80). Forty (69.0%) children were referred to Ear, Nose and Throat clinic, being 18 (45.0%) of them submitted to TA. In half of these (9; 50.0%) snoring had persisted, with no difference between children with asthma or rhinitis ( p -value = 0.143). Five (7.4%) children were referred to an orthodontics specialist and 1 needed CPAP. Conclusion Our review shows that allergic disease is frequent in children with SDB, even if it is not severe. In these children, snoring persists after TA in a large number of patients, being necessary to consider other therapeutic options and prolonged follow-up. Allergy should be accessed as a risk-factor in the management of sleep-disordered breathing in children.