Natural variability of lotic Mediterranean ecosystems or wildfire perturbations: who will win?

This study evaluates the impacts of wildfires in lotic Mediterranean ecosystems. It was carried out at Monchique ridge after big wildfires occurred during 2002 and 2003. Deferential impacts were evaluated comparing historical results obtained before the wildfires (1999 and 2001), with the post fire ones (2006 and 2007). Physical and chemical parameters of the water, habitat morphology, diatoms, macrophytes, macroinvertebrates and fishes were evaluated at 10 collecting places, before and after wildfires. High recovering rates were observed to the vegetation, but it is still possible to found fire impacts over macrophytes and river morphology. Wildfires, contributed to canopy decrease and, consequently to the growth of plants that usually are controlled by shadow. As a result, vegetation biodiversity tend to increase. River banks tend also to be invaded by terrestrial plants. Higher post fires recover rates were observed to the more aquatic communities (diatoms, macroinvertebrates and fishes). For those communities, comparing spring situations before and after the fires no substantial differences were observed. Sometimes differences between consecutive years are even higher. So it can be concluded that magnitude of wildfire impacts is less than the natural inter-annual variability of Mediterranean rivers. Long-term effects of forest fires, resulting from large woody debries, were also detected by morphological alterations, like debries dams. Habitat diversity increase and impacts on aquatic communities are expected

Student teachers' perceptions of the Internet: Motivation, influences, and use

The Internet's rapid growth and diffusion, both worldwide and in Portugal, as well as its importance for teacher education, made the authors feel the need to reflect on how their student teachers integrate themselves in such quite novel environmental conditions and teaching communities This paper reports on one specific Portuguese university's student teachers' Internet usage during their teaching practice and what reasons motivated them to do so. It also looks into student teachers' perceptions about Internet discussion and usage by other teachers in their schools and, in particular, in their own disciplinary groups. The data was collected using a questionnaire which was anonymously answered by 189 of the entire 360-student teacher 2000/2001 population from all 9 different preservice programs

EFECTO DE UNA FUENTE DE ALIMENTO EXPERIMENTAL SOBRE UNA ASOCIACIÓN HORMIGA-HEMIPTERO

In order to assess if ants attracted to honeydew-producing Hemiptera switched food sources when offered an additional, considerably rich and abundant food source, we studied the interaction between the plant Solanum lycocarpum (Solanaceae), an efn-lacking shrub, the predominantly diurnal ant Camponotus crassus (Hymenoptera: Formicidae), and two species of membracids (Enchenopa spp.; Homoptera: Membracidae). The study was done during September of 1999 at the Reserva Ecológica of IBGE (ca. 35 km S of Brasilia-DF, Brasil). The results show that ants were attracted both to the experimental food source and to the membracids. Moreover, the mean number of ants visiting the experimental nectary was significantly higher than those visiting the membracids. However, the membracids were never left unattended, which suggests that ants, even though presented with an abundant and rich food source, do not abandon other sources. The latter can be explained due to an increment in the honeydew production rate by the membracids, thus the attention levels of ants does not vary Another possibility is the fidelity of worker ants to a food source and its location. To show that ants switch food sources based on quality and/or quantity, and not merely based of their presence and/or absence, requires future research, both for plants with and without extrafloral nectaries.Estudiamos la asociación entre el arbusto sin nectarios extraflorales (NEF) Solanum lycocarpum (Solanaceae), la hormiga Camponotus crassus (Hymenoptera: Formicidae) y dos especies de membrácidos (Enchenopa spp., Hemiptera: Membracidae) productores de ambrosía, para determinar si las hormigas abandonarían a los membrácidos al ofrecerles experimentalmente una fuente de alimento considerablemente rica y abundante. El estudio se realizó en septiembre de 1999 en la Reserva Ecológica del Instituto Brasileiro de Geografía y Estadística (IBGE) (ca. 35 km al sur de Brasilia-DF, Brasil). Los resultados muestran que las hormigas fueron atraídas tanto al nectario experimental como a los membrácidos. Más aún, el número promedio de hormigas visitando a los nectarios experimentales fue significativamente mayor que el de las que visitaron a los membrácidos. Sin embargo, los membrácidos nunca fueron abandonados, lo que sugiere que las hormigas, a pesar de explotar una fuente abundante de alimento, no abandonan otras fuentes. Lo anterior puede explicarse por un incremento en la tasa de producción de ambrosía por los membrácidos, por lo que los niveles de atención de las hormigas hacia ellos no varía aún en la presencia de una fuente alternativa de alimento. Otra posibilidad puede ser la lealtad de las obreras por un recurso y su ubicación; algunos individuos retornan siempre a un sitio con una fuente de alimento. El poder demostrar que las hormigas cambian de recurso alimenticio basadas en cantidad y/o calidad, y no solamente basadas en la presencia o ausencia de los mismos, requiere de investigaciones futuras, tanto para plantas con como sin NEF

Local pattern of host plant utilization by lepidopteran larvae in the cerrado vegetation

Diniz IR, Morais HC. 2002. Local pattern of host plant utilization by lepidopteran larvae in the cerrado vegetation. Entomotropica 17(2):115-119. The first inventory of lepidopteran larvae associated to buds, flowers and fruits and the study of the degree of specialization on host plant species and/or plant tissues was conducted in cerrado areas (savanna like vegetation) in Federal District (Brazil). Adults of 83 species from 15 lepidopteran families were obtained on 36 plant species of 20 families. Four of the Lepidoptera families were the richest in species and included 69% of the total species: Gelechiidae (22 species), Tortricidae (17), Lycaenidae (10), and Pyralidae (8). The present results indicate three lepidopteran groups: (1) monophagous or oligophagous of a plant part from a single plant genus, 58% of the species; (2) polyphagous of plant families and plant tissues, 25% of the species; (3) oligophagous, but opportunists over the parts of the same plant species, 17% of the species.Diniz IR, Morais HC. 2002. Patrones locales de utilizaci\uf3n de plantas hospederas por larvas de Lepidoptera en vegetaci\uf3n de cerrado. Entomotropica 17(2):115-119. En este trabajo se presentan los resultados del primer inventario de larvas de Lepidoptera asociadas a botones florales, flores y frutos, de plantas de una \ue1rea de cerrado (sabana tropical) del Distrito Federal (Brasil). Tambi\ue9n fueron estudiados el grado de especializaci\uf3n por especie de planta y/o por los tejidos de la planta. Adultos se obtuvieron de 83 especies de 15 familias de Lepidoptera en 36 especies de plantas pertenecientes a 20 familias bot\ue1nicas. Cuatro familias de Lepidoptera fueron las de mayor riqueza, reuniendo el 69% del total de especies: Gelechiidae (22 especies), Tortricidae (17), Lycaenidae (10) y Pyralidae (8). Los resultados obtenidos indican que en la regi\uf3n de est\ufadio pueden reconocerse tres grupos de Lepidoptera: (1) mon\uf3fagos u oligofagos en tejidos de un s\uf3lo g\ue9nero de plantas, 58% de las especies; (2) pol\uedfagos a nivel de familias y tejidos de plantas, 25% de las especies; (3) oligofagos, pero oportunistas, sobre los recursos de la misma especie de plantas, 17% de las especies

Augmented synthetic dataset with structured light to develop Ai-based methods for breast depth estimation

Breast interventions are common healthcare procedures that nor mally require experienced professionals, expensive setups, and high execution times. With the evolution of robot-assisted technologies and image analysis algorithms, new methodologies can be imple mented to facilitate the interventions in this area. To enable the introduction of robot-assisted approaches for breast procedures, strategies with real-time capacity and high precision for 3D breast shape estimation are required. In this paper, it is proposed to fuse the structured light (SL) and deep learning (DL) techniques to perform the depth estimation of the breast shape with high precision. First, multiple synthetic datasets of breasts with different printed patterns, resembling the SL technique, are created. Thus, it is possi ble to take advantage of the pattern’s deformation induced by the breast surface in order to improve the quality of the depth infor mation and to study the most suitable design. Then, distinct DL architectures, taken from the literature, were implemented to esti mate the breast shape from the created datasets and study the DL architectures’ influence on depth estimation. The results obtained with the introduction of a yellow grid pattern, composed of thin stripes, fused with the DenseNet-161 architecture achieved the best results. Overall, the current study demonstrated the potential of the proposed practice for breast depth estimation or other human body parts in the future when we rely exclusively on 2D images.The authors acknowledge the funding of the projects "NORTE01-0145-FEDER000045” and "NORTE-01-0145-FEDER-000059", supported by Northern Portugal Regional Operational Programme (NORTE 2020), under the Portugal 2020 Partnership Agreement, through the European Regional Development Fund (FEDER). It was also funded by national funds, through the Fundação para a Ciência e a Tecnologia (FCT) and FCT/MCTES in the scope of the projects UIDB/05549/2020,UIDP/05549/2020 and LASILA/P/0104/2020. The authors also acknowledge FCT, Portugal and the European Social Found, European Union, for funding support through the “Programa Operacional Capital Humano” (POCH) in the scope of the PhD grants SFRH/BD/136721/2018 (B. Oliveira) and SFRH/BD/136670/2018 (H. Torres)

Dual consistency loss for contour-aware segmentation in medical images

Medical image segmentation is a paramount task for several clinical applications, namely for the diagnosis of pathologies, for treatment planning, and for aiding image-guided surgeries. With the development of deep learning, Convolutional Neural Networks (CNN) have become the state-of-the-art for medical image segmentation. However, issues are still raised concerning the precise object boundary delineation, since traditional CNNs can produce non-smooth segmentations with boundary discontinuities. In this work, a U-shaped CNN architecture is proposed to generate both pixel-wise segmentation and probabilistic contour maps of the object to segment, in order to generate reliable segmentations at the object's boundaries. Moreover, since the segmentation and contour maps must be inherently related to each other, a dual consistency loss that relates the two outputs of the network is proposed. Thus, the network is enforced to consistently learn the segmentation and contour delineation tasks during the training. The proposed method was applied and validated on a public dataset of cardiac 3D ultrasound images of the left ventricle. The results obtained showed the good performance of the method and its applicability for the cardiac dataset, showing its potential to be used in clinical practice for medical image segmentation.Clinical Relevance-The proposed network with dual consistency loss scheme can improve the performance of state-of-the-art CNNs for medical image segmentation, proving its value to be applied for computer-aided diagnosis.- (undefined

Classification of chronic venous disorders using an ensemble optimization of convolutional neural networks

Chronic Venous Disorders (CVD) of lower limbs are one of the most prevalent medical conditions, affecting 35% of adults in Europe and North America. The early diagnosis of CVD is critical, however, the diagnosis relies on a visual recognition of the various venous disorders which is time- consuming and dependent on the physician's expertise. Thus, automatic strategies for the classification of the CVD severity are claimed. This paper proposed an automatic ensemble-based strategy of Deep Convolutional Neural Networks (DCNN) for the classification of CVDs severity from medical images. First, a clinical dataset containing 1376 images of patients' legs with CVD of 5 different levels of severity was constructed. Then, the constructed dataset was randomly split into training, testing, and validation datasets. Subsequently, a set of DCNN were individually applied to the images for classification. Finally, instead of a traditional voting ensemble strategy, extracted feature vectors from each DCNN were concatenated and fed into a new ensemble optimization network. Experiments showed that the proposed strategy achieved a classification with 93.8%, 93.4%, 92.4% of accuracy, precision, and recall, respectively. Moreover, compared to the traditional ensemble strategy, improvement in the accuracy of ~2% was registered. The proposed strategy showed to be accurate and robust for the diagnosis of CVD severity from medical images. Nevertheless, further research using an extensive clinical database is required to validate the potential of this strategy.The authors acknowledge Fundação para a Ciência e a Tecnologia (FCT), Portugal and the European Social Found, European Union, for funding support through the “Programa Operacional Capital Humano” (POCH) in the scope of the PhD grants SFRH/BD/136721/2018 (B. Oliveira) and SFRH/BD/136670/2018 (H. Torres). Moreover, authors gratefully acknowledge the funding of the projects "NORTE-01-0145-FEDER000045” and "NORTE-01-0145-FEDER-000059", supported by Northern Portugal Regional Operational Programme (NORTE 2020), under the Portugal 2020 Partnership Agreement, through the European Regional Development Fund (FEDER). It was also funded by national funds, through the FCT and FCT/MCTES in the scope of the project LASI-LA/P/0104/2020, UIDB/00319/2020, UIDB/05549/2020 and UIDP/05549/2020

Current perspectives

The increasing knowledge of the mechanisms involved in metabolism is shifting the paradigms by which the pathophysiology of many pulmonary diseases is understood. Metabolic dysfunction is recognized in obesity-associated asthma, but other metabolic conditions have been shown to be independently related to asthma. Novel insights have also recently been brought by metabolomics in this filed. The purpose of this review is to discuss current perspectives regarding metabolic dysfunction in asthma, from obesity-related asthma to other metabolic conditions and the role of current pharmacological therapeutic strategies and lifestyle interventions. Obesity is a well-recognized risk factor for asthma across the lifespan, which is generally associated with poorer response to current available treatments, rendering a more severe, refractory disease status. Besides the epidemiological and clinical link, untargeted metabolomics studies have recently supported the obesity-associated asthma phenotype at the molecular level. Not only obesity-related, but also other aspects of metabolic dysregulation can be independently linked to asthma. These include hyperinsulinemia, dyslipidemia and hypertension, which need to be taken into account, even in the non-obese patient. Untargeted metabolomics studies have further highlighted several other metabolic pathways that can be altered in asthma, namely regarding oxidative stress and systemic inflammation, and also suggesting the importance of microbiota in asthma pathogenesis. Considering the reduced response to corticosteroids, other pharmacologic treatments have been shown to be effective regardless of body mass index. Non-pharmacologic treatments (namely weight reduction and dietary changes) may bring substantial benefit to the asthmatic patient. Taken together, this evidence points towards the need to improve our knowledge in this filed and, in particular, to address the influence of environmental factors in metabolic dysfunction and asthma development. Personalized medicine is definitely needed to optimize treatment, including a holistic view of the asthmatic patient in order to set accurate pharmacologic therapy together with dietary, physical exercise and lifestyle interventions.publishersversionpublishe

Characterization of the workspace and limits of operation of laser treatments for vascular lesions of the lower limbs

The increase of the aging population brings numerous challenges to health and aesthetic segments. Here, the use of laser therapy for dermatology is expected to increase since it allows for non-invasive and infection-free treatments. However, existing laser devices require doctors’ manually handling and visually inspecting the skin. As such, the treatment outcome is dependent on the user’s expertise, which frequently results in ineffective treatments and side effects. This study aims to determine the workspace and limits of operation of laser treatments for vascular lesions of the lower limbs. The results of this study can be used to develop a robotic-guided technology to help address the aforementioned problems. Specifically, workspace and limits of operation were studied in eight vascular laser treatments. For it, an electromagnetic tracking system was used to collect the real-time positioning of the laser during the treatments. The computed average workspace length, height, and width were 0.84 ± 0.15, 0.41 ± 0.06, and 0.78 ± 0.16 m, respectively. This corresponds to an average volume of treatment of 0.277 ± 0.093 m3. The average treatment time was 23.2 ± 10.2 min, with an average laser orientation of 40.6 ± 5.6 degrees. Additionally, the average velocities of 0.124 ± 0.103 m/s and 31.5 + 25.4 deg/s were measured. This knowledge characterizes the vascular laser treatment workspace and limits of operation, which may ease the understanding for future robotic system development.The authors acknowledge Fundação para a Ciência e a Tecnologia (FCT), Portugal and the European Social Fund, European Union, for funding support through [the “Programa Operacional Capital Humano” (POCH) in the scope of the PhD], grants number [SFRH/BD/136721/2018 (B. Oliveira) and SFRH/BD/136670/2018 (H. Torres)]. Moreover, authors gratefully acknowledge the funding of the projects “NORTE-01-0145-FEDER-000045” and “NORTE-01-0145-FEDER-000059”, supported by [Northern Portugal Regional Operational Programme (NORTE 2020), under the Portugal 2020 Partnership Agreement, through the European Regional Development Fund (FEDER)]. It was also funded by [national funds, through the FCT and FCT/MCTES in the scope of the projects UIDB/05549/2020, UIDP/05549/2020, and LASI-LA/P/0104/2020]

Tree-Dwelling Ants: Contrasting Two Brazilian Cerrado Plant Species without Extrafloral Nectaries

Ants dominate vegetation stratum, exploiting resources like extrafloral nectaries (EFNs) and insect honeydew. These interactions are frequent in Brazilian cerrado and are well known, but few studies compare ant fauna and explored resources between plant species. We surveyed two cerrado plants without EFNs, Roupala montana (found on preserved environments of our study area) and Solanum lycocarpum (disturbed ones). Ants were collected and identified, and resources on each plant noted. Ant frequency and richness were higher on R. montana (67%; 35 spp) than S. lycocarpum (52%; 26), the occurrence of the common ant species varied between them, and similarity was low. Resources were explored mainly by Camponotus crassus and consisted of scale insects, aphids, and floral nectaries on R. montana and two treehopper species on S. lycocarpum. Ants have a high diversity on cerrado plants, exploring liquid and prey-based resources that vary in time and space and affect their presence on plants