Counting and Locating High-Density Objects Using Convolutional Neural Network

This paper presents a Convolutional Neural Network (CNN) approach for counting and locating objects in high-density imagery. To the best of our knowledge, this is the first object counting and locating method based on a feature map enhancement and a Multi-Stage Refinement of the confidence map. The proposed method was evaluated in two counting datasets: tree and car. For the tree dataset, our method returned a mean absolute error (MAE) of 2.05, a root-mean-squared error (RMSE) of 2.87 and a coefficient of determination (R$^2$) of 0.986. For the car dataset (CARPK and PUCPR+), our method was superior to state-of-the-art methods. In the these datasets, our approach achieved an MAE of 4.45 and 3.16, an RMSE of 6.18 and 4.39, and an R$^2$ of 0.975 and 0.999, respectively. The proposed method is suitable for dealing with high object-density, returning a state-of-the-art performance for counting and locating objects.Comment: 15 pages, 10 figures, 8 table

Thermal image segmentation in studies of wildlife animals

Thermal imaging analysis is an important tool in the study of wildlife animals. The segmentation of thermal images has not extensively explored by the Ecology and Biology communities. In this paper we propose a new approach for segmenting thermal images using the SLIC superpixel algorithm and connected component labeling. Experiments were performed on images taken over the behaviour activity of four mammal species. The results show that our approach has a great potential for partioning animals and background.IPÊ - Instituto de Pesquisas Ecológica

Soroprevalência de anticorpos do vírus SARS-CoV-2 em escolares no município de São Paulo, 2020

OBJECTIVE: To estimate seroprevalence of SARS-CoV-2 antibodies in schoolchildren aged 4 to 14 years living in the city of São Paulo, according to clinical, demographic, epidemiological, and social variables, during the school closure period as a measure against covid-19 spread. METHODS: A serological survey was made in September 2020 with a random sample stratified by school system (municipal public, state public and private) type. A venous blood sample was collected using the Wondfo SARS-CoV-2 Antibody Test (lateral flow method) for detection of total SARS-CoV-2 virus antibodies. Semi-structured questionnaires were applied to collect clinical, demographic, social, and epidemiological data. RESULTS: Seroprevalence of SARS-CoV-2 antibodies in schoolchildren was of 16.6% (95%CI 15.4–17.8). The study found higher seroprevalence in the municipal (18.5%; 95%CI 16.6–20.6) and state (16.2%; 95%CI 14.4–18.2) public school systems compared to the private school system (11.7; 95%CI 10.0–13.7), among black and brown students (18.4%; 95%CI 16.8–20.2) and in the most vulnerable social stratum (18.5 %;95%CI 16.9–20.2). Lower seroprevalence was identified in schoolchildren who reported following the recommended protective measures against covid-19. CONCLUSION: Seroprevalence of SARS-CoV-2 antibodies is found mainly in the most socially vulnerable schoolchildren. This study can contribute to support public policies that reinforce the importance of suspending face-to-face classes and developing strategies aimed at protective measures and monitoring of the serological status of those who have not yet been included in the vaccination schedule.OBJETIVO: Estimar a soroprevalência de anticorpos do vírus SARS-CoV-2 em escolares de quatro a 14 anos de idade residentes no município de São Paulo, segundo variáveis clínicas, demográficas, epidemiológicas e sociais, durante o período de fechamento das escolas como medida de controle da covid-19. MÉTODOS: Realizou-se um inquérito sorológico em setembro de 2020 com amostra aleatória estratificada por tipo de rede de ensino (pública municipal, pública estadual e privada). Foi coletada amostra de sangue venoso utilizando-se o teste de imunoensaio de fluxo lateral da fabricante Wondfo para detecção de anticorpos totais contra o vírus SARS-CoV-2. Aplicaram-se questionários semiestruturados para o levantamento de dados clínicos, demográficos, sociais e epidemiológicos. RESULTADOS: A soroprevalência de anticorpos do vírus SARS-CoV-2 em escolares foi de 16,6% (IC95% 15,4–17,8). O estudo encontrou soroprevalências mais elevadas na rede pública municipal (18,5%; IC95% 16,6–20,6) e estadual (16,2%; IC95% 14,4–18,2) em relação à rede privada (11,7; IC95% 10,0–13,7) e entre escolares da raça/cor preta e parda (18,4%; IC95% 16,8–20,2) e no estrato social mais vulnerável (18,5%; IC95% 16,9–20,2). A pesquisa identificou menores soroprevalências nos escolares que relataram seguir as medidas recomendadas de proteção contra a covid-19. CONCLUSÃO: A soroprevalência de anticorpos contra o vírus SARS-CoV-2 atinge principalmente os escolares socialmente mais vulneráveis. Este estudo pode contribuir para embasar políticas públicas que reforcem a importância da suspensão das aulas presenciais e da necessidade de estratégias de medidas de proteção e acompanhamento do status sorológico daqueles que ainda não foram contemplados no calendário vacinal

Estudo manométrico do esôfago distal de gatos anestesiados com tiopental sódico

OBJETIVO: Obter o padrão de normalidade da pressão e comprimento do esfíncter inferior do esôfago (EIE) em gatos anestesiados com tiopental e analisar a viabilidade prática do anestésico para uso neste tipo de investigação sobre atividade motora do esôfago de felinos. MÉTODOS: em 12 gatos anestesiados com tiopental sódico foram realizados estudos manométricos do EIE, com leitura por perfusão em três canais radiais. Foram avaliadas as pressões e comprimentos do EIE. RESULTADOS: Os valores médios da pressão e comprimento do EIE foram 33,52 ± 12,42 mmHg e 1,6 ± 0,4 cm, respectivamente. CONCLUSÃO: Foi possível estabelecer valor de referência para a pressão e comprimento do EIE de felinos, com uma contenção e retorno confortáveis para o animal, utilizando o tiopental sódico como agente anestésico.PURPOSE: To obtain the normality standard of the lower esophageal sphincter (LES) of cats anesthetized with tiopental and at analysing the practical viability of the anesthetic use in felines esophagus motor activity investigation. METHODS: Manometric studies of LES were performed in 12 cats anestetized with tiopental with perfusion reading in three radial channels. LES pressures and lengths were measured. RESULTS: The mean values of LES pressure and lengths were 33,52 ± 12,42 mmHg and 1,6 ± 0,4 cm respectively. CONCLUSION: A LES reference value for felines pressure and length was determined. Acommodation and return were comfortable for the animals with the use of sodic tiopental as an anesthetic agent

Prosthetic Improvement Of Pronounced Buccally Positioned Zygomatic Implants: A Clinical Report.

This report presents a prosthetic technique for the improvement of surgically positioned, buccally placed zygomatic implants with the use of custom abutments for improved retention screw position and an esthetic implant reconstruction. The patient presented four zygomatic implants with pronounced buccal inclination. The anterior implants were inclined toward the location where the anterior artificial teeth should be placed during rehabilitation. As the manufacturer does not provide angulated abutments, we attempted the waxing and overcasting of a prosthetic abutment, repositioning the access holes of the prosthetic screws to a more palatal position. This clinical report demonstrates that abutment customization could be an interesting way to relocate the access holes of the prosthetic screws in cases of zygomatic implants with pronounced buccal inclination.23504-

Prosthetic improvement of pronounced buccally positioned zygomatic implants: a clinical report

This report presents a prosthetic technique for the improvement of surgically positioned, buccally placed zygomatic implants with the use of custom abutments for improved retention screw position and an esthetic implant reconstruction. The patient presented four zygomatic implants with pronounced buccal inclination. The anterior implants were inclined toward the location where the anterior artificial teeth should be placed during rehabilitation. As the manufacturer does not provide angulated abutments, we attempted the waxing and overcasting of a prosthetic abutment, repositioning the access holes of the prosthetic screws to a more palatal position. This clinical report demonstrates that abutment customization could be an interesting way to relocate the access holes of the prosthetic screws in cases of zygomatic implants with pronounced buccal inclination236504508sem informaçã

A CNN Approach to Simultaneously Count Plants and Detect Plantation-Rows from UAV Imagery

In this paper, we propose a novel deep learning method based on a Convolutional Neural Network (CNN) that simultaneously detects and geolocates plantation-rows while counting its plants considering highly-dense plantation configurations. The experimental setup was evaluated in a cornfield with different growth stages and in a Citrus orchard. Both datasets characterize different plant density scenarios, locations, types of crops, sensors, and dates. A two-branch architecture was implemented in our CNN method, where the information obtained within the plantation-row is updated into the plant detection branch and retro-feed to the row branch; which are then refined by a Multi-Stage Refinement method. In the corn plantation datasets (with both growth phases, young and mature), our approach returned a mean absolute error (MAE) of 6.224 plants per image patch, a mean relative error (MRE) of 0.1038, precision and recall values of 0.856, and 0.905, respectively, and an F-measure equal to 0.876. These results were superior to the results from other deep networks (HRNet, Faster R-CNN, and RetinaNet) evaluated with the same task and dataset. For the plantation-row detection, our approach returned precision, recall, and F-measure scores of 0.913, 0.941, and 0.925, respectively. To test the robustness of our model with a different type of agriculture, we performed the same task in the citrus orchard dataset. It returned an MAE equal to 1.409 citrus-trees per patch, MRE of 0.0615, precision of 0.922, recall of 0.911, and F-measure of 0.965. For citrus plantation-row detection, our approach resulted in precision, recall, and F-measure scores equal to 0.965, 0.970, and 0.964, respectively. The proposed method achieved state-of-the-art performance for counting and geolocating plants and plant-rows in UAV images from different types of crops.Comment: 27 pages, 12 figures, 9 table