A Multilayer Perceptron Neural Network Model to Classify Hypertension in Adolescents Using Anthropometric Measurements: A Cross-Sectional Study in Sarawak, Malaysia.

This study outlines and developed a multilayer perceptron (MLP) neural network model for adolescent hypertension classification focusing on the use of simple anthropometric and sociodemographic data collected from a cross-sectional research study in Sarawak, Malaysia. Among the 2,461 data collected, 741 were hypertensive (30.1%) and 1720 were normal (69.9%). During the data gathering process, eleven anthropometric measurements and sociodemographic data were collected. The variable selection procedure in the methodology proposed selected five parameters: weight, weight-to-height ratio (WHtR), age, sex, and ethnicity, as the input of the network model. The developed MLP model with a single hidden layer of 50 hidden neurons managed to achieve a sensitivity of 0.41, specificity of 0.91, precision of 0.65, F-score of 0.50, accuracy of 0.76, and Area Under the Receiver Operating Characteristic (ROC) Curve (AUC) of 0.75 using the imbalanced data set. Analyzing the performance metrics obtained from the training, validation and testing data sets show that the developed network model is well-generalized. Using Bayes' Theorem, an adolescent classified as hypertensive using this created model has a 66.2% likelihood of having hypertension in the Sarawak adolescent population, which has a hypertension prevalence of 30.1%. When the prevalence of hypertension in the Sarawak population was increased to 50%, the developed model could predict an adolescent having hypertension with an 82.0% chance, whereas when the prevalence of hypertension was reduced to 10%, the developed model could only predict true positive hypertension with a 33.6% chance. With the sensitivity of the model increasing to 65% and 90% while retaining a specificity of 91%, the true positivity of an adolescent being hypertension would be 75.7% and 81.2%, respectively, according to Bayes' Theorem. The findings show that simple anthropometric measurements paired with sociodemographic data are feasible to be used to classify hypertension in adolescents using the developed MLP model in Sarawak adolescent population with modest hypertension prevalence. However, a model with higher sensitivity and specificity is required for better positive hypertension predictive value when the prevalence is low. We conclude that the developed classification model could serve as a quick and easy preliminary warning tool for screening high-risk adolescents of developing hypertension.

Stretchable AgX (X = Se, Te) for Efficient Thermoelectrics and Photovoltaics.

Transition metal chalcogenides (TMCs) have gained worldwide interest owing to their outstanding renewable energy conversion capability. However, the poor mechanical flexibility of most existing TMCs limits their practical commercial applications. Herein, triggered by the recent and imperative synthesis of highly ductile α-Ag2S, an effective approach based on evolutionary algorithm and ab initio total-energy calculations for determining stable, ductile phases of bulk and two-dimensional AgxSe1-x and AgxTe1-x compounds was implemented. The calculations correctly reproduced the global minimum bulk stoichiometric P212121-Ag8Se4 and P21/c-Ag8Te4 structures. Recently reported metastable AgTe3 was also revealed but it lacks dynamical stability. Further single-layered screening unveiled two new monolayer P4/nmm-Ag4Se2 and C2-Ag8Te4 phases. Orthorhombic Ag8Se4 crystalline has a narrow, direct band gap of 0.26 eV that increases to 2.68 eV when transforms to tetragonal Ag4Se2 monolayer. Interestingly, metallic P21/c-Ag8Te4 changes to semiconductor when thinned down to monolayer, exhibiting a band gap of 1.60 eV. Present findings confirm their strong stability from mechanical and thermodynamic aspects, with reasonable Vickers hardness, bone-like Young's modulus (E) and high machinability observed in bulk phases. Detailed analysis of the dielectric functions ε(ω), absorption coefficient α(ω), power conversion efficiency (PCE) and refractive index n(ω) of monolayers are reported for the first time. Fine theoretical PCE (SLME method ∼11-28%), relatively high n(0) (1.59-1.93), and sizable α(ω) (104-105 cm-1) that spans the infrared to visible regions indicate their prospects in optoelectronics and photoluminescence applications. Effective strategies to improve the temperature dependent power factor (PF) and figure of merit (ZT) are illustrated, including optimizing the carrier concentration. With decreasing thickness, ZT of p-doped Ag-Se was found to rise from approximately 0.15-0.90 at 300 K, leading to a record high theoretical conversion efficiency of ∼12.0%. The results presented foreshadow their potential application in a hybrid device that combines the photovoltaic and thermoelectric technologies.