Deep-pretrained-FWI: combining supervised learning with physics-informed neural network

An accurate velocity model is essential to make a good seismic image. Conventional methods to perform Velocity Model Building (VMB) tasks rely on inverse methods, which, despite being widely used, are ill-posed problems that require intense and specialized human supervision. Convolutional Neural Networks (CNN) have been extensively investigated as an alternative to solve the VMB task. Two main approaches were investigated in the literature: supervised training and Physics-Informed Neural Networks (PINN). Supervised training presents some generalization issues since structures, and velocity ranges must be similar in training and test set. Some works integrated Full-waveform Inversion (FWI) with CNN, defining the problem of VMB in the PINN framework. In this case, the CNN stabilizes the inversion, acting like a regularizer and avoiding local minima-related problems and, in some cases, sparing an initial velocity model. Our approach combines supervised and physics-informed neural networks by using transfer learning to start the inversion. The pre-trained CNN is obtained using a supervised approach based on training with a reduced and simple data set to capture the main velocity trend at the initial FWI iterations. We show that transfer learning reduces the uncertainties of the process, accelerates model convergence, and improves the final scores of the iterative process.Comment: Paper present at machine Learning and the Physical Sciences workshop, NeurIPS 202

Morphological Divergence among Progeny of Macroptilium lathyroides Accessions from the Semi-Arid Region of Pernambuco, Brazil

Macroptilium is a legume genus with approximately 20 species, usually annual or biennial, herbaceous and distributed mainly in the Americas. It is widely used as a forage resource in grasslands and usually fixes atmospheric N. Martins et al. (2001) indicated that half-sib family selection with progeny testing is the most common plant breeding method used in Brazil. In the scientific literature, however, there are few studies dedicated to Macroptilium spp. This study evaluated morphological divergence among Macroptilium spp. progeny from accessions collected in 4 counties located in the semi-arid region of Pernambuco State, NE Brazil

Pregnant and non-pregnant women and low back pain-related differences on postural control measures during different balance tasks

Introduction: Low back pain (LBP) is the most common musculoskeletal complaint in pregnancy, being responsible for many negative impacts. Objective: To evaluate the effect of LBP on static and dynamic balance in pregnant women and whether pregnancy mediates the results compared to non-pregnant women. Methods: 44 women (mean age 30 yrs) participated voluntarily in this study: 16 pregnant women with LBP starting in pregnancy, 14 pregnant women without LBP and 14 non-pregnant women as a group control. Participants were assessed for static postural balance using a force platform and dynamic mobility balance using the Timed Up and Go (TUG) test. Results: The pregnant women with LBP showed significant (P < 0.04, for mean, d= 1,2) poor postural balance in static tests (force platform), in the area of COP eyes open. In dynamic balance (TUG test), statistical difference was found between the groups (P 0.038) and the effect size were moderate to strong in the comparison between the three groups. The most sensitive differences were reported mainly between pregnant women with LBP versus non-pregnant control group in balance measures from force platform. Conclusion: The findings indicate that LBP associated to pregnant clinical status can decrease the balance capacity in women. These results have implication for balance evaluation and retraining in pregnant women with and without LBP from rehabilitation or prevention programs

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Ação inseticida do extrato de Derris amazonica Killip para Cerotoma arcuatus Olivier (Coleoptera: Chrysomelidae

A abundância e o potencial inseticida de Derris amazonica e a necessidade de controle de Cerotoma arcuatus Olivier (Coleoptera: Chrysomelidae) na cultura do feijão-caupi (Vigna unguiculata L. Walp) estimularam a realização desta pesquisa, que objetivou avaliar a ação inseticida do extrato de D. amazonica a adultos de C. arcuatus em condições de laboratório. Os bioensaios testaram as vias de intoxicação por ingestão de folhas contaminadas, contato com superfície contaminada e aplicação tópica, com delineamento experimental inteiramente casualizado, com quatro repetições. Os valores de mortalidade e consumo foliar dos insetos foram submetidos à análise de regressão, sendo utilizada a análise de Probit para determinação das CL50, da DL50 e dos TL50. O extrato de D. amazonica, contendo 3,7% de rotenona, foi tóxico para adultos de C. arcuatus via ingestão de folhas contaminadas (CL50=15,14 µL do extrato.mL-1 de água), superfície contaminada (CL50=0,45 µL do extrato.cm-2) e aplicação tópica (DL50=1,44 µL do extrato.g-1 do inseto). Mortalidades de adultos de C. arcuatus superiores a 80% e os menores tempos letais médios foram obtidos na concentração de 5% (v v-1) do extrato em todos os bioensaios. O consumo foliar de adultos de C. arcuatus foi inversamente proporcional a concentração do extrato quando expostos por via de ingestão foliar ou aplicação tópica, sendo inclusive observada inibição da alimentação dos indivíduos. O extrato de D. amazonica é tóxico para C. arcuatus e inibe a alimentação dos insetos a partir da concentração de 1% (v v-1).The abundance and insecticidal potential of Derris amazonica in addition to need of controlling Cerotoma arcuatus for bean crop stimulated this research. The objective of this work was to evaluate insecticide action of the extract of D. amazonica to adults of C. arcuatus in laboratory conditions. The bioassays were carried out using three distend methodologies: leaf intake, contact in treated surface (filter paper) and topical application. A completed randomized experimental design was used with four replications. Mortality values and leaf consumption of the insects were subjected to regression analyses, being the Probit analyses used to determine of the i.e., LC50, LT50 and LD50. The extract of D. amazonica containing 3.7% of rotenone was toxic to adults C. arcuatus when exposed to treated leaves (LC50 = 15.14 µl.mL-1), treated surface (LC50 = 0.45 µl.cm-2) and subjected to topical exposure (LD50 = 1.44 µl.g-1). In all bioassays the adults mortality was higher than 80% with lower median lethal times obtained with 5% (v.v-1) concentrations of the extract. Leaf consumption by adults C. arcuatus was inversely proportional to the concentration of the extract when exposed by leaf intake or topical application, also being observed inhibition of feeding individuals. The extract of D. amazonica is toxic to C. arcuatus and inhibits the feeding of insects from the concentration of 1% (v v-1)

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Evaluation of PCR for Diagnosis of American Cutaneous Leishmaniasis in an Area of Endemicity in Northeastern Brazil

PCR-based approaches targeting kinetoplast DNA were evaluated for the diagnosis of American cutaneous leishmaniasis (ACL) in regions of endemicity in northeastern Brazil. A total of 119 cutaneous biopsy specimens from patients with ACL and nonleishmaniasis cutaneous lesions were studied. Two PCR-based systems were used; one was specific for the subgenus Viannia, and the other was specific for the genus Leishmania. The PCR specific for the subgenus Viannia had a sensitivity of 95.4%, whereas the genus-specific PCR detected the target DNA in 88.2% of the samples tested. The specificities of the assays, determined with samples from a group with nonleishmaniasis cutaneous lesions, was 100%. The results of the conventional tests indicate that the sensitivities of the PCR-based methods were significantly higher than those of smear examination, histological staining, and isolation by culture (P < 0.05). Antibodies specific for Leishmania braziliensis were detected by indirect immunofluorescence in 82.9% of the patients tested. Parasites were isolated from 40 of 86 patients (46.5%). Sixty-seven percent of dermal scrapings and 66.2% of stained tissue sections were positive by microscopy. Amplified products from the subgenus-specific PCR hybridized with the Leishmania panamensis minicircle, confirming infection consistent with L. braziliensis. The evidence available at present incriminates L. braziliensis as the only causative agent of ACL in the state of Pernambuco in Brazil