Desenvolvimento de sistema computacional para auxílio à reabilitação de distúrbios auditivos leves ou moderados

Este artigo apresenta o desenvolvimento de um software com o objetivo de reduzir/eliminar dificuldades de linguagem e aprendizagem que deficientes auditivos e pessoas portadoras de distúrbios do processamento auditivo venham a possuir. O Software Auxiliar na Reabilitação dos Distúrbios Auditivos – SARDA - é constituído por cinco jogos que visam desenvolver, principalmente, as seguintes habilidades auditivas: localização da fonte sonora, reconhecimento e discriminação auditiva, atenção seletiva e sustentada. Os jogos estão organizados em etapas, fases e níveis de dificuldades que têm como foco diferenças acústicas relacionadas ao tempo dos sons não verbais e verbais. Desta forma, a linha mestre entre os jogos é auxiliar a criança a ser mais eficiente e eficaz em processar os estímulos auditivos no tempo. O software tem como objetivo principal para o fonoaudiólogo desenvolver estas habilidades auditivas em crianças com distúrbios auditivos, enquanto que para o professor o foco principal é desenvolver estas habilidades auditivas em crianças em fase de desenvolvimento escolar. Ambos os profissionais podem utilizar o software e obter um parecer a respeito da evolução ou não da criança no tratamento.This paper presents the development of a system to reduce/eliminate language and learning difficulties of low or moderate hearing impaired children. The Software Auxiliar na Reabilitação dos Distúrbios Auditivos - SARDA has five games to develop this hearing skills: to locate the sound, recognition sound, selective and supported attention. The games are organized in stages, phases and levels with differences acoustics related to the sounds time, verbal or not verbal. To the phonoaudiology the software is to develop the hearing skills at hearing impaired children, and to the teacher is to develop this hearing skills in children at school development. Both can use the software and to have informations about the evolution of the child in the treatment.Red de Universidades con Carreras en Informática (RedUNCI

Mortality from gastrointestinal congenital anomalies at 264 hospitals in 74 low-income, middle-income, and high-income countries: a multicentre, international, prospective cohort study

Summary Background Congenital anomalies are the fifth leading cause of mortality in children younger than 5 years globally. Many gastrointestinal congenital anomalies are fatal without timely access to neonatal surgical care, but few studies have been done on these conditions in low-income and middle-income countries (LMICs). We compared outcomes of the seven most common gastrointestinal congenital anomalies in low-income, middle-income, and high-income countries globally, and identified factors associated with mortality. Methods We did a multicentre, international prospective cohort study of patients younger than 16 years, presenting to hospital for the first time with oesophageal atresia, congenital diaphragmatic hernia, intestinal atresia, gastroschisis, exomphalos, anorectal malformation, and Hirschsprung’s disease. Recruitment was of consecutive patients for a minimum of 1 month between October, 2018, and April, 2019. We collected data on patient demographics, clinical status, interventions, and outcomes using the REDCap platform. Patients were followed up for 30 days after primary intervention, or 30 days after admission if they did not receive an intervention. The primary outcome was all-cause, in-hospital mortality for all conditions combined and each condition individually, stratified by country income status. We did a complete case analysis. Findings We included 3849 patients with 3975 study conditions (560 with oesophageal atresia, 448 with congenital diaphragmatic hernia, 681 with intestinal atresia, 453 with gastroschisis, 325 with exomphalos, 991 with anorectal malformation, and 517 with Hirschsprung’s disease) from 264 hospitals (89 in high-income countries, 166 in middleincome countries, and nine in low-income countries) in 74 countries. Of the 3849 patients, 2231 (58·0%) were male. Median gestational age at birth was 38 weeks (IQR 36–39) and median bodyweight at presentation was 2·8 kg (2·3–3·3). Mortality among all patients was 37 (39·8%) of 93 in low-income countries, 583 (20·4%) of 2860 in middle-income countries, and 50 (5·6%) of 896 in high-income countries (p<0·0001 between all country income groups). Gastroschisis had the greatest difference in mortality between country income strata (nine [90·0%] of ten in lowincome countries, 97 [31·9%] of 304 in middle-income countries, and two [1·4%] of 139 in high-income countries; p≤0·0001 between all country income groups). Factors significantly associated with higher mortality for all patients combined included country income status (low-income vs high-income countries, risk ratio 2·78 [95% CI 1·88–4·11], p<0·0001; middle-income vs high-income countries, 2·11 [1·59–2·79], p<0·0001), sepsis at presentation (1·20 [1·04–1·40], p=0·016), higher American Society of Anesthesiologists (ASA) score at primary intervention (ASA 4–5 vs ASA 1–2, 1·82 [1·40–2·35], p<0·0001; ASA 3 vs ASA 1–2, 1·58, [1·30–1·92], p<0·0001]), surgical safety checklist not used (1·39 [1·02–1·90], p=0·035), and ventilation or parenteral nutrition unavailable when needed (ventilation 1·96, [1·41–2·71], p=0·0001; parenteral nutrition 1·35, [1·05–1·74], p=0·018). Administration of parenteral nutrition (0·61, [0·47–0·79], p=0·0002) and use of a peripherally inserted central catheter (0·65 [0·50–0·86], p=0·0024) or percutaneous central line (0·69 [0·48–1·00], p=0·049) were associated with lower mortality. Interpretation Unacceptable differences in mortality exist for gastrointestinal congenital anomalies between lowincome, middle-income, and high-income countries. Improving access to quality neonatal surgical care in LMICs will be vital to achieve Sustainable Development Goal 3.2 of ending preventable deaths in neonates and children younger than 5 years by 2030

Mapping land use capability in tropical conditions adapting criteria to different levels of agricultural management

ABSTRACT Land use capability is one of the most widespread technical-interpretative classification systems, however, regional adaptations may be necessary because different attributes may affect it. For these adaptations, the Minas Gerais soil map was used as the starting point for this study. The criteria to define the land use capability were adapted to management levels with small (level A) and medium (level B) application of capital and modern technology (level C). The aim of the present study was to map land use capability for Minas Gerais state, Brazil, following the criteria adapted to different levels of management and measure the accuracy of the resulting maps. The system of land use capability is widely used by INCRA in evaluations of rural properties. Erosion criterion was replaced by erodibility. The information was handled in a geographic information system. For validation, soil profiles from regional pedological surveys were sampled, classified, and its land use capability was compared to the land use capability shown on the map according to the different management levels. In spite of the small scale of the soil map, the maps of land use capability exhibited adequate accuracy: 73% (management level A), 71% (B), and 50% (C). Therefore, it can be applied in initial phases of regional planning studies, in which the level of details required is reduced (for example, in ecological-economic zoning). More detailed analyses still depend on detailed field surveys, as advocated by the system of land use capability

Portable X-ray fluorescence (pXRF) spectrometry applied to the prediction of chemical attributes in Inceptisols under different land uses

ABSTRACT Portable X-ray fluorescence (pXRF) spectrometry has been increasingly adopted for varying studies worldwide. This work aimed at characterizing effects of soil management on the content of chemical elements detected by pXRF in managed and unmanaged areas of Inceptisols, and evaluating the potential of using pXRF data to generate prediction models for soil fertility attributes, evaluating the effect of land uses on such models. Samples were collected in A, B, and C horizons of soils under native forest, native Cerrado, coffee crops with 1 and 5 years of implantation and eucalyptus. Soil fertility attributes were determined through laboratory analyses, whereas, elemental contents were obtained through pXRF analysis. PXRF data were used for modeling (regressions) and validation of soil fertility attributes and necessity of lime (NL) application, with or without distinction between managed and unmanaged areas. Management practices on coffee crops increased the levels of Sr, CaO, P2O5, Cu, and Zn. CaO content was efficient for prediction of exchangeable Ca2+ contents (R2 = 0.91), pH (R2 = 0.88), base saturation (R2 = 0.89) in managed areas. General models presented adequate results to predict exchangeable Ca2+ (R2 = 0.92), pH (R2 = 0.85), and base saturation (R2 = 0.90). Models for unmanaged areas were less effective. PXRF detected modifications in elemental contents caused by management practices and provided reliable predictions of soil fertility attributes

Arbuscular mycorrhizal fungal communities in an iron mining area and its surroundings: Inoculum potential, density, and diversity of spores related to soil properties

ABSTRACT Arbuscular mycorrhizal fungi (AMF) interact symbiotically with most plant species, facilitating revegetation of areas under rehabilitation. The aim of this study was to evaluate the inoculum potential, density, and diversity of AMF spores in five environments, as well as the relation of species with soil properties. Soil samples were collected in five environments in a mining area and its surroundings in the Quadrilátero Ferrífero, Minas Gerais (Brazil): tailings piles in rehabilitation with grass, canga, Cerrado, native forest, and eucalyptus plantation; these samples were subjected to chemical and physical analyses. Spores were directly extracted from field samples and from trap cultures (TCs) established in two locations in the Southeast and South regions of Brazil for taxonomic identification of the species. Species richness, the Shannon diversity index (H’), and equitability were determined. Principal component analysis (PCA) was used to identify soil properties that most influenced AMF occurrence. Spore density showed no significant difference among the environments. A total of 59 AMF species were found. This is the first report of the occurrence of Acaulospora nivalis and Acaulospora alpina in Brazil. Higher H’ and species richness in the field were found in tailings piles and lower in canga. Canga showed higher inoculum potential. The development of TCs in two locations allowed a wider diversity of AMF species to be captured. Environments of the Quadrilátero Ferrífero are hotspots of AMF diversity, and the soil pH and exchangeable S and P contents are the properties that best explain the distribution of AMF species

Multiple linear regression and random forest to predict and map soil properties using data from portable X-ray fluorescence spectrometer (pXRF)

ABSTRACT Determination of soil properties helps in the correct management of soil fertility. The portable X-ray fluorescence spectrometer (pXRF) has been recently adopted to determine total chemical element contents in soils, allowing soil property inferences. However, these studies are still scarce in Brazil and other countries. The objectives of this work were to predict soil properties using pXRF data, comparing stepwise multiple linear regression (SMLR) and random forest (RF) methods, as well as mapping and validating soil properties. 120 soil samples were collected at three depths and submitted to laboratory analyses. pXRF was used in the samples and total element contents were determined. From pXRF data, SMLR and RF were used to predict soil laboratory results, reflecting soil properties, and the models were validated. The best method was used to spatialize soil properties. Using SMLR, models had high values of R² (≥0.8), however the highest accuracy was obtained in RF modeling. Exchangeable Ca, Al, Mg, potential and effective cation exchange capacity, soil organic matter, pH, and base saturation had adequate adjustment and accurate predictions with RF. Eight out of the 10 soil properties predicted by RF using pXRF data had CaO as the most important variable helping predictions, followed by P2O5, Zn and Cr. Maps generated using RF from pXRF data had high accuracy for six soil properties, reaching R2 up to 0.83. pXRF in association with RF can be used to predict soil properties with high accuracy at low cost and time, besides providing variables aiding digital soil mapping

Arbuscular mycorrhizal fungal communities in an iron mining area and its surroundings: Inoculum potential, density, and diversity of spores related to soil properties

<div><p>ABSTRACT Arbuscular mycorrhizal fungi (AMF) interact symbiotically with most plant species, facilitating revegetation of areas under rehabilitation. The aim of this study was to evaluate the inoculum potential, density, and diversity of AMF spores in five environments, as well as the relation of species with soil properties. Soil samples were collected in five environments in a mining area and its surroundings in the Quadrilátero Ferrífero, Minas Gerais (Brazil): tailings piles in rehabilitation with grass, canga, Cerrado, native forest, and eucalyptus plantation; these samples were subjected to chemical and physical analyses. Spores were directly extracted from field samples and from trap cultures (TCs) established in two locations in the Southeast and South regions of Brazil for taxonomic identification of the species. Species richness, the Shannon diversity index (H’), and equitability were determined. Principal component analysis (PCA) was used to identify soil properties that most influenced AMF occurrence. Spore density showed no significant difference among the environments. A total of 59 AMF species were found. This is the first report of the occurrence of Acaulospora nivalis and Acaulospora alpina in Brazil. Higher H’ and species richness in the field were found in tailings piles and lower in canga. Canga showed higher inoculum potential. The development of TCs in two locations allowed a wider diversity of AMF species to be captured. Environments of the Quadrilátero Ferrífero are hotspots of AMF diversity, and the soil pH and exchangeable S and P contents are the properties that best explain the distribution of AMF species.</p></div

Multiple linear regression and random forest to predict and map soil properties using data from portable X-ray fluorescence spectrometer (pXRF)

<div><p>ABSTRACT Determination of soil properties helps in the correct management of soil fertility. The portable X-ray fluorescence spectrometer (pXRF) has been recently adopted to determine total chemical element contents in soils, allowing soil property inferences. However, these studies are still scarce in Brazil and other countries. The objectives of this work were to predict soil properties using pXRF data, comparing stepwise multiple linear regression (SMLR) and random forest (RF) methods, as well as mapping and validating soil properties. 120 soil samples were collected at three depths and submitted to laboratory analyses. pXRF was used in the samples and total element contents were determined. From pXRF data, SMLR and RF were used to predict soil laboratory results, reflecting soil properties, and the models were validated. The best method was used to spatialize soil properties. Using SMLR, models had high values of R² (≥0.8), however the highest accuracy was obtained in RF modeling. Exchangeable Ca, Al, Mg, potential and effective cation exchange capacity, soil organic matter, pH, and base saturation had adequate adjustment and accurate predictions with RF. Eight out of the 10 soil properties predicted by RF using pXRF data had CaO as the most important variable helping predictions, followed by P2O5, Zn and Cr. Maps generated using RF from pXRF data had high accuracy for six soil properties, reaching R2 up to 0.83. pXRF in association with RF can be used to predict soil properties with high accuracy at low cost and time, besides providing variables aiding digital soil mapping.</p></div