A comparative analysis of classical and machine learning methods for forecasting TB/HIV co-infection.

TB/HIV coinfection poses a complex public health challenge. Accurate forecasting of future trends is essential for efficient resource allocation and intervention strategy development. This study compares classical statistical and machine learning models to predict TB/HIV coinfection cases stratified by gender and the general populations. We analyzed time series data using exponential smoothing and ARIMA to establish the baseline trend and seasonality. Subsequently, machine learning models (SVR, XGBoost, LSTM, CNN, GRU, CNN-GRU, and CNN-LSTM) were employed to capture the complex dynamics and inherent non-linearities of TB/HIV coinfection data. Performance metrics (MSE, MAE, sMAPE) and the Diebold-Mariano test were used to evaluate the model performance. Results revealed that Deep Learning models, particularly Bidirectional LSTM and CNN-LSTM, significantly outperformed classical methods. This demonstrates the effectiveness of Deep Learning for modeling TB/HIV coinfection time series and generating more accurate forecasts.

Facial morphological analysis for the development of a representative atlas of the brazilian population.

The objective of this study was to propose categories of morphological classification for the face and its anatomical structures, as well as to propose illustrations to support the development of an atlas that facilitates facial morphological analysis of adult Brazilians. It was a descriptive study based on the analysis of the frequency and distribution of 13 photoanthropometric facial ratios (RFAs) obtained from a representative sample of the Brazilian population. RFAs related to facial height and width, eye width, intercanthal distance, nose length and width, philtrum ridge height and width, mouth thickness and width, upper and lower lip thickness, and chin height were analyzed. The study included a sample of 5.000 individuals aged between 18 and 22 years, evenly distributed between genders. Data normality was assessed using the Shapiro-Wilk test, considering them as parametric when p > 0.05. For the RFAs that showed normal distribution, mean ± 1.5 standard deviations (SD) were used to categorize facial measurements as regular, below average, or above average. Non-parametric RFAs were analyzed based on the median and 10th and 90th percentiles of the data. Based on the established average iris diameter, which is considered the most stable facial measurement, the values of the described RFAs were converted to a numerical scale in centimeters, allowing for the illustration of female and male faces. In this way, it was possible to categorize the facial anatomical structures and, consequently, visualize the facial morphological pattern of the adult Brazilian population.

Binary decisions of artificial intelligence to classify third molar development around the legal age thresholds of 14, 16 and 18 years.

Third molar development is used for dental age estimation when all the other teeth are fully mature. In most medicolegal facilities, dental age estimation is an operator-dependent procedure. During the examination of unaccompanied and undocumented minors, this procedure may lead to binary decisions around age thresholds of legal interest, namely the ages of 14, 16 and 18 years. This study aimed to test the performance of artificial intelligence to classify individuals below and above the legal age thresholds of 14, 16 and 18 years using third molar development. The sample consisted of 11,640 panoramic radiographs (9680 used for training and 1960 used for validation) of males (n = 5400) and females (n = 6240) between 6 and 22.9 years. Computer-based image annotation was performed with V7 software (V7labs, London, UK). The region of interest was the mandibular left third molar (T38) outlined with a semi-automated contour. DenseNet121 was the Convolutional Neural Network (CNN) of choice and was used with Transfer Learning. After Receiver-operating characteristic curves, the area under the curve (AUC) was 0.87 and 0.86 to classify males and females below and above the age of 14, respectively. For the age threshold of 16, the AUC values were 0.88 (males) and 0.83 (females), while for the age of 18, AUC were 0.94 (males) and 0.83 (females). Specificity rates were always between 0.80 and 0.92. Artificial intelligence was able to classify male and females below and above the legal age thresholds of 14, 16 and 18 years with high accuracy.

The quantum maxima for the basic graphs of exclusivity are not reachable in Bell scenarios.

A necessary condition for the probabilities of a set of events to exhibit Bell non-locality or Kochen-Specker contextuality is that the graph of exclusivity of the events contains induced odd cycles with five or more vertices, called odd holes, or their complements, called odd antiholes. From this perspective, events whose graph of exclusivity are odd holes or antiholes are the building blocks of contextuality. For any odd hole or antihole, any assignment of probabilities allowed by quantum theory can be achieved in specific contextuality scenarios. However, here we prove that, for any odd hole, the probabilities that attain the quantum maxima cannot be achieved in Bell scenarios. We also prove it for the simplest odd antiholes. This leads us to the conjecture that the quantum maxima for any of the building blocks cannot be achieved in Bell scenarios. This result sheds light on why the problem of whether a probability assignment is quantum is decidable, while whether a probability assignment within a given Bell scenario is quantum is, in general, undecidable. This also helps to understand why identifying principles for quantum correlations is simpler when we start by identifying principles for quantum sets of probabilities defined with no reference to specific scenarios. This article is part of the theme issue 'Quantum contextuality, causality and freedom of choice'.

Accuracy of an AI-based automated plate reading mobile application for the identification of clinical mastitis-causing pathogens in chromogenic culture media.

Using on-farm microbiological culture (OFC), based on chromogenic culture media, enables the identification of mastitis causing pathogens in about 24 h, allows rapid decision making on selective treatment and control management measures of cows with clinical mastitis (CM). However, accurate interpretation of OFC results requires trained and experienced operators, which could be a limitation for the use of OFC in dairy farms. Our hypothesis was that AI-based automated plate reading mobile application can analyze images of microorganisms' colonies in chromogenic culture media with similar diagnostic performance as a trained specialist evaluator. Therefore, the aim of the present study was to evaluate the diagnostic accuracy of an AI-based application (Rumi; OnFarm, Piracicaba, São Paulo, Brazil) for interpreting images of mastitis causing microorganism colonies grown in chromogenic culture media. For this study two trials were organized to compare the results obtained using an AI-based application Rumi with the interpretation of: (1) a trained specialist, using MALDI-TOF MS as the gold standard; (2) farm personnel users (FPU). In trial 1, a total of 476 CM milk samples, from 11 farms located in São Paulo (n = 7) and Minas Gerais (n = 4), southeast Brazil, were inoculated in chromogenic culture media plates (Smartcolor 2, OnFarm, Piracicaba, São Paulo, Brazil) by specialists under lab conditions, and digital images were recorded 24 h after incubation at 37 °C. After that, all the 476 digital images were analyzed by the Rumi and by another specialist (who only had access to the digital images) and the diagnostic accuracy indicators sensitivity (Se) and specificity (Sp) were calculated using MALDI-TOF MS microbiological identification of the isolates as the reference. In Trial 2, a total of 208 CM milk samples, from 150 farms from Brazil, were inoculated in chromogenic culture media plates by FPU, and the results of microbiological growth were visually interpreted by FPU under on-farm conditions. After visual interpretation, results were recorded using an OnFarmApp application (herd manage application for mastitis by OnFarm, Piracicaba, São Paulo, Brazil), and the images of the chromogenic culture plates were captured by the OnFarmApp to be evaluated by Rumi and Bayesian Latent Class Models were performed to compare Rumi and the FPU. In Trial 1, Rumi presented high and intermediate accuracy results, with the only exception of the low Enterococcus spp.'s Se. In comparison with the specialist, Rumi performed similarly in Se and Sp for most groups of pathogens, with the only exception of non-aureus staphylococci where Se results were lower. Both Rumi and the specialist achieved Sp results > 0.96. In Trial 2, Rumi had similar results as the FPU in the Bayesian Latent Class Model analysis. In conclusion, the use of the AI-based automated plate reading mobile application can be an alternative for visual interpretation of OFC results, simplifying the procedures for selective treatment decisions for CM based on OFC.

Breeding biology review of White­backed Stilt Himantopus melanurus in Brazil and a case study in the largest restinga protected area (Aves, Charadriiformes, Recurvirostridae)

In Brazil, the White-backed Stilt Himantopus melanurus is distributed in the midwest, south and southeast but breeding information is scarce. In this study, species breeding information in the country was compiled from online platform (WikiAves, eBird) and literature. A case study describing nests and egg biometry were reported in Restinga of Jurubatiba National Park (RJNP), on the north cost of Rio de Janeiro state, as well potential threats to the species. Sampling was carried out in September and December 2018, monthly in 2019 and between January to March and September to December in 2020. Overall, 70 breeding records were compiled, between 1997 and November 2021, being 64 from WikiAves in all regions of Brazil, four records from eBird in São Paulo state (in 2021) and two records in literature (one from São Paulo state, in 2007 and one from Rio de Janeiro in 2012). In RJNP, 44 nests were identified being 34 active, with an average of 3.5 eggs per nest, and overall 118 eggs were measured. The main materials used to build the nests were the saltmarsh plant and mud. Around 60% of nests were degraded or predated. Predation was the main cause of egg loss. Successful nests (with chicks or hatching signs) represented 26% of the total nests monitored. This study reports the first information on the biometry of the species' eggs and nests, confirming the northern coast of Rio de Janeiro state as a nesting area for the species.(AU)

Evaluating the presence of Mycoplasma hyorhinis, Fusobacterium nucleatum, and Helicobacter pylori in biopsies of patients with gastric cancer.

BACKGROUND: Gastric cancer is the third leading cause of cancer-related deaths worldwide and has been associated with infections that may promote tumour progression. Accordingly, we analysed the presence of Mollicutes, Mycoplasma hyorhinis, Fusobacterium nucleatum and Helicobacter pylori in gastric cancer tissues and evaluated their correlation with clinicopathological factors. METHODS: Using a commercial kit, DNA were extracted from 120 gastric samples embedded in paraffin: 80 from patients with gastric cancer and 40 from cancer free patients, dating from 2006 to 2016. Mollicutes and H. pylori were detected by PCR; F. nucleatum and M. hyorhinis were detected by qPCR, together with immunohistochemistry for the latter bacteria. RESULTS: Mollicutes were detected in the case and control groups (12% and 2.5%) and correlated with the papillary histologic pattern (P = 0.003), likely due to cell transformation promoted by Mollicutes. M. hyorhinis was detected in the case and control group but was not considered a cancer risk factor. H. pylori was detected at higher loads in the case compared to the control group (8% and 22%, P = 0.008) and correlated with metastasis (P = 0.024), lymphatic invasion (P = 0.033), tumour of diffused type (P = 0.028), and histopathological grading G1/G2 (P = 0.008). F. nucleatum was the most abundant bacteria in the case group, but was also detected in the control group (26% and 2.5%). It increased the cancer risk factor (P = 0.045, OR = 10.562, CI95% = 1.057-105.521), and correlated with old age (P = 0.030) and tumour size (P = 0.053). Bacterial abundance was significantly different between groups (P = 0.001). CONCLUSION: Our findings could improve the control and promote our understanding of opportunistic bacteria and their relevance to malignant phenotypes.

Breeding review of Gray-hooded Gull Chroicocephalus cirrocephalus in Brazil with contributions on nests and egg biometry

The Gray-hooded Gull (Chroicocephalus cirrocephalus) is a seabird distributed in almost all South American countries. However, breeding information on the species in Brazil is scarce. In this study, a literature review and searches in online databases (WikiAves and eBird) were carried out to gather breeding information on the species in the country and new records of nests of the Gray-hooded Gull were registered on the northern coast of the Rio de Janeiro state. Literature review indicated breeding records in Rio Grande do Sul, Rio de Janeiro and Rio Grande do Norte states. On WikiAves, 19 records of the species with nests, eggs, chicks and breeding colonies were reported between 2009 and 2020, in Macau, Rio Grande do Norte and one adult hatching at Rio Grande do Sul. In August 2019, two nests were recorded at Ubatuba lagoon (22°09′S and 41°18′W) in the Restinga de Jurubatiba National Park, in the Quissamã municipality in Rio de Janeiro. The nests were described and monitored during five weeks. Each nest contained two eggs and was built with the grass Paspalum vaginatum. Over time, the eggs were degraded and disappeared from the nests, without signs of hatching and possible predation. This study compiles for the first time all the breeding information on the species in Brazil and contributes with data about nests and egg biometry.(AU)

Estimating sex and age from a face: a forensic approach using machine learning based on photo-anthropometric indexes of the Brazilian population.

The facial analysis permits many investigations, some of the most important of which are craniofacial identification, facial recognition, and age and sex estimation. In forensics, photo-anthropometry describes the study of facial growth and allows the identification of patterns in facial skull development, for example, by using a group of cephalometric landmarks to estimate anthropological information. Previous works presented, as indirect applications, the use of photo-anthropometric measurements to estimate anthropological information such as age and sex. In several areas, automation of manual procedures has achieved advantages over and similar measurement confidence as a forensic expert. This manuscript presents an approach using photo-anthropometric indexes, generated from frontal faces cephalometric landmarks of the Brazilian population, to create an artificial neural network classifier that allows the estimation of anthropological information, in this specific case age and sex. This work is focused on four tasks: (i) sex estimation on ages from 5 to 22 years old, evaluating the interference of age on sex estimation; (ii) age estimation from photo-anthropometric indexes for four age intervals (1 year, 2 years, 4 years, and 5 years); (iii) age group estimation for thresholds of over 14 and over 18 years old; and; (iv) the provision of a new data set, available for academic purposes only, with a large and complete set of facial photo-anthropometric points marked and checked by forensic experts, measured from over 18,000 faces of individuals from Brazil over the last 4 years. The proposed binary classifier obtained significant results, using this new data set, for the sex estimation of individuals over 14 years old, achieving accuracy values higher than 0.85 by the F1 measure. For age estimation, the accuracy results are 0.72 for the F1 measure with an age interval of 5 years. For the age group estimation, the F1 measures of accuracy are higher than 0.93 and 0.83 for thresholds of 14 and 18 years, respectively.

Breeding review of Gray-hooded Gull Chroicocephalus cirrocephalus in Brazil with contributions on nests and egg biometry

The Gray-hooded Gull (Chroicocephalus cirrocephalus) is a seabird distributed in almost all South American countries. However, breeding information on the species in Brazil is scarce. In this study, a literature review and searches in online databases (WikiAves and eBird) were carried out to gather breeding information on the species in the country and new records of nests of the Gray-hooded Gull were registered on the northern coast of the Rio de Janeiro state. Literature review indicated breeding records in Rio Grande do Sul, Rio de Janeiro and Rio Grande do Norte states. On WikiAves, 19 records of the species with nests, eggs, chicks and breeding colonies were reported between 2009 and 2020, in Macau, Rio Grande do Norte and one adult hatching at Rio Grande do Sul. In August 2019, two nests were recorded at Ubatuba lagoon (22°09′S and 41°18′W) in the Restinga de Jurubatiba National Park, in the Quissamã municipality in Rio de Janeiro. The nests were described and monitored during five weeks. Each nest contained two eggs and was built with the grass Paspalum vaginatum. Over time, the eggs were degraded and disappeared from the nests, without signs of hatching and possible predation. This study compiles for the first time all the breeding information on the species in Brazil and contributes with data about nests and egg biometry.

Breeding review of Gray-hooded Gull Chroicocephalus cirrocephalus in Brazil with contributions on nests and egg biometry

Abstract The Gray-hooded Gull (Chroicocephalus cirrocephalus) is a seabird distributed in almost all South American countries. However, breeding information on the species in Brazil is scarce. In this study, a literature review and searches in online databases (WikiAves and eBird) were carried out to gather breeding information on the species in the country and new records of nests of the Gray-hooded Gull were registered on the northern coast of the Rio de Janeiro state. Literature review indicated breeding records in Rio Grande do Sul, Rio de Janeiro and Rio Grande do Norte states. On WikiAves, 19 records of the species with nests, eggs, chicks and breeding colonies were reported between 2009 and 2020, in Macau, Rio Grande do Norte and one adult hatching at Rio Grande do Sul. In August 2019, two nests were recorded at Ubatuba lagoon (22°09S and 41°18W) in the Restinga de Jurubatiba National Park, in the Quissamã municipality in Rio de Janeiro. The nests were described and monitored during five weeks. Each nest contained two eggs and was built with the grass Paspalum vaginatum. Over time, the eggs were degraded and disappeared from the nests, without signs of hatching and possible predation. This study compiles for the first time all the breeding information on the species in Brazil and contributes with data about nests and egg biometry.