Designing optical glasses by machine learning coupled with a genetic algorithm

Engineering new glass compositions have experienced a sturdy tendency to move forward from (educated) trial-and-error to data- and simulation-driven strategies. In this work, we developed a computer program that combines data-driven predictive models (in this case, neural networks) with a genetic algorithm to design glass compositions with desired combinations of properties. First, we induced predictive models for the glass transition temperature (T_g) using a dataset of 45,302 compositions with 39 different chemical elements, and for the refractive index (n_d) using a dataset of 41,225 compositions with 38 different chemical elements. Then, we searched for relevant glass compositions using a genetic algorithm informed by a design trend of glasses having high n_d (1.7 or more) and low T_g (500 °C or less). Two candidate compositions suggested by the combined algorithms were selected and produced in the laboratory. These compositions are significantly different from those in the datasets used to induce the predictive models, showing that the used method is indeed capable of exploration. Both glasses met the constraints of the work, which supports the proposed framework. Therefore, this new tool can be immediately used for accelerating the design of new glasses. These results are a stepping stone in the pathway of machine learning-guided design of novel glasses.     

Microwave hybrid fast sintering of red clay ceramics

This work aimed to examine the performance of the hybrid sintering of clay ceramic in a microwave furnace, compared to the sintering process in a conventional furnace. The raw materials were subjected to X-ray fluorescence, loss on ignition (LOI), X-ray diffraction, particle size distribution, real specific mass, and thermogravimetric analyses. The red clay ceramic mass was prepared, extruded, pre-sintered in a conventional furnace at 600°C/60 min, and sintered at temperatures between 700 °C and 1100 °C. The sintering conventional (resistive oven) was carried out for 60 min with a heating rate of 10°C/min. In the microwave furnace, the sintering times were 5, 10, and 15 min, with a heating rate of 50°C/min, with a sintering chamber coated with silicon carbide (susceptor). The sintered specimens were characterized according to linear shrinkage, water absorption, apparent porosity, apparent specific mass, X-ray diffraction, Raman spectroscopy analysis, spectroscopy analysis in the ultraviolet and visible regions, microhardness, and scanning electron microscopy. The results showed that microwave sintering promoted an increase in the microhardness and apparent specific mass, and reduction in water absorption and apparent porosity values, due to greater densification in the microstructure. The best results occurred for specimens sintered at 1100°C.     

Methodology for Estimating Streamflow by Water Balance and Rating Curve Methods Based on Logistic Regression

Both water balance (WB) and rating curve (RC) are methods for estimating streamflow. The first is mostly used to estimate reservoir outflows, while the second is usually adopted in hydrometeorological network streamflow gauges. While WB uses hourly collected data, the RC estimates streamflow using current water level and extrapolation techniques. The objective of this study was to analyze variations in the reservoir’s hourly outflow at Queimado Hydroelectric Power Plant (HPP Queimado) and to propose a method to evaluate whether the estimate of the daily outflows, obtained by the WB method, is similar to the flow values obtained at a conventional station. The logistic regression (LR) model was used because it is a method that adopts binary, categorically dependent variables to identify the event of interest. The results showed that the values of streamflow, obtained from an average of two daily readings, were a good representation of the flows in the region. The LR was able to identify atypical data, especially in the rainy season. This means that data consistency analysis can be faster and safer, when adequately employed and considering the proposed conditions, contributing to both management policies and the management of water resources.

     

Some Molecular and Cellular Stress Mechanisms Associated with Neurodegenerative Diseases and Atherosclerosis

Chronic stress is a combination of nonspecific adaptive reactions of the body to the influence of various adverse stress factors which disrupt its homeostasis, and it is also a corresponding state of the organism’s nervous system (or the body in general). We hypothesized that chronic stress may be one of the causes occurence of several molecular and cellular types of stress. We analyzed literary sources and considered most of these types of stress in our review article. We examined genes and mutations of nuclear and mitochondrial genomes and also molecular variants which lead to various types of stress. The end result of chronic stress can be metabolic disturbance in humans and animals, leading to accumulation of reactive oxygen species (ROS), oxidative stress, energy deficiency in cells (due to a decrease in ATP synthesis) and mitochondrial dysfunction. These changes can last for the lifetime and lead to severe pathologies, including neurodegenerative diseases and atherosclerosis. The analysis of literature allowed us to conclude that under the influence of chronic stress, metabolism in the human body can be disrupted, mutations of the mitochondrial and nuclear genome and dysfunction of cells and their compartments can occur. As a result of these processes, oxidative, genotoxic, and cellular stress can occur. Therefore, chronic stress can be one of the causes forthe occurrence and development of neurodegenerative diseases and atherosclerosis. In particular, chronic stress can play a large role in the occurrence and development of oxidative, genotoxic, and cellular types of stress.     

Pressure drop and optimization meta-models for arbitrary low-height pleated filter shapes and flowrates

Journal of Mechanical Science and Technology - This study delivers equations useful for low-height pleated fibrous filter design: two pressure drop equations and one set of optimum design equations...     

Defining Dry Eye from a Clinical Perspective

Over the past decades, the number of patients with dry eye disease (DED) has increased dramatically. The incidence of DED is higher in Asia than in Europe and North America, suggesting the involvement of cultural or racial factors in DED etiology. Although many definitions of DED have been used, discrepancies exist between the various definitions of dry eye disease (DED) used across the globe. This article presents a clinical consensus on the definition of DED, as formulated in four meetings with global DED experts. The proposed new definition is as follows: “Dry eye is a multifactorial disease characterized by a persistently unstable and/or deficient tear film (TF) causing discomfort and/or visual impairment, accompanied by variable degrees of ocular surface epitheliopathy, inflammation and neurosensory abnormalities.” The key criteria for the diagnosis of DED are unstable TF, inflammation, ocular discomfort and visual impairment. This definition also recommends the assessment of ocular surface epitheliopathy and neurosensory abnormalities in each patient with suspected DED. It is easily applicable in clinical practice and should help practitioners diagnose DED consistently. This consensus definition of DED should also help to guide research and clinical trials that, to date, have been hampered by the lack of an established surrogate endpoint.