Monthly Streamflow Modeling Based on Self-Organizing Maps and Satellite-Estimated Rainfall Data

Hydrological data provide valuable information for the decision-making process in water resources management, where long and complete time series are always desired. However, it is common to deal with missing data when working on streamflow time series. Rainfall-streamflow modeling is an alternative to overcome such a difficulty. In this paper, self-organizing maps (SOM) were developed to simulate monthly inflows to a reservoir based on satellite-estimated gridded precipitation time series. Three different calibration datasets from Três Marias Reservoir, composed of inflows (targets) and 91 TRMM-estimated rainfall data (inputs), from 1998 to 2019, were used. The results showed that the inflow data homogeneity pattern influenced the rainfall-streamflow modeling. The models generally showed superior performance during the calibration phase, whereas the outcomes varied depending on the data homogeneity pattern and the chosen SOM structure in the testing phase. Regardless of the input data homogeneity, the SOM networks showed excellent results for the rainfall-runoff modeling, presenting Nash–Sutcliffe coefficients greater than 0.90.

Graphical Abstract

     

Prospective Analysis of Artisanal Mining in the Santa Rita Village: Municipality of Andes,Antioquia

Mine Water and the Environment - Artisanal and small-scale mining (ASM) of gold has adversely affected the environment and human health for decades, mostly due to excessive use of mercury. With the...     

A Flexi-PEGDA Upconversion Implant for Wireless Brain Photodynamic Therapy

Near-infrared (NIR) activatable upconversion nanoparticles (UCNPs) enable wireless-based phototherapies by converting deep-tissue-penetrating NIR to visible light. UCNPs are therefore ideal as wireless transducers for photodynamic therapy (PDT) of deep-sited tumors. However, the retention of unsequestered UCNPs in tissue with minimal options for removal limits their clinical translation. To address this shortcoming, biocompatible UCNPs implants are developed to deliver upconversion photonic properties in a flexible, optical guide design. To enhance its translatability, the UCNPs implant is constructed with an FDA-approved poly(ethylene glycol) diacrylate (PEGDA) core clad with fluorinated ethylene propylene (FEP). The emission spectrum of the UCNPs implant can be tuned to overlap with the absorption spectra of the clinically relevant photosensitizer, 5-aminolevulinic acid (5-ALA). The UCNPs implant can wirelessly transmit upconverted visible light till 8 cm in length and in a bendable manner even when implanted underneath the skin or scalp. With this system, it is demonstrated that NIR-based chronic PDT is achievable in an untethered and noninvasive manner in a mouse xenograft glioblastoma multiforme (GBM) model. It is postulated that such encapsulated UCNPs implants represent a translational shift for wireless deep-tissue phototherapy by enabling sequestration of UCNPs without compromising wireless deep-tissue light delivery.     

Energy-Aware Production Scheduling in Flow Shop and Job Shop Environments Using a Multi-Objective Genetic Algorithm

Abstract

The energy-aware scheduling problem is a multi-objective optimization problem where the main goal is to achieve energy savings without affecting productivity in a manufacturing system. In this work, we present an approach for energy-aware flow shop scheduling problem and energy-aware job shop scheduling problem considering the process speed as the main energy-related decision variable. This approach allows one to set the appropriate process speed for every considered operation in the corresponding machine. When the speed is high, the processing time is short but the energy demand increases, and vice versa. Therefore, two objectives are worked together: a production objective, paired with an energy efficiency objective. A generic elitist multi-objective genetic algorithm was implemented to solve both problems. Results from a simple comparative design of experiments and a nonparametric test show that it is possible to smooth the energy demand profile and obtain reductions that average 19.8% in energy consumption. This helps to reduce peak loads and drops on applied energy sources demand, stabilizing the conversion units operational efficiency across the entire operational time with a minimum effect on the production maximum completion time (makespan).     

Photon absorption in a hybrid slurry photocatalytic reactor: Assessment of differential approximations

Radiative transfer inside a slurry photocatalytic reactor with hybrid illumination from both solar radiation and lamps is examined. The local volumetric rate of photon absorption is evaluated. For this purpose, the P1 and the modified differential approximations (MDAs) are used, and results compared to a solution by the Monte Carlo method. It is found that significant differences may arise between the predictions of the above approximations and the exact results provided by the Monte Carlo simulations. The P1 approximation is very inaccurate near to the radiation entrance for the partially collimated solar radiation, although it improves, as optical depth increases. As expected, the MDA improves the results near to the boundary. Surprisingly, it turns out to be much worse than the P1 approximation at medium and large optical depths. In the case of lamp irradiation, the behavior of the MDA is the opposite; it works better at small optical depths. © 2011 American Institute of Chemical Engineers AIChE J, 58: 3256–3265, 2012     

Renewable polybenzoxazines based in diphenolic acid

The reaction of mixtures of renewable diphenolic acid (DPA) and its methylesterbenzoxazine derivative (MDP-Bz) has been studied. The DPA was introduced to lower the high temperature needed to complete the curing of the pure benzoxazine. In this way, samples with different DPA/MDP-Bz ratio (0, 2, 5, 10 and 25% of DPA) were investigated. Moreover, high performance flame retardant thermosetting resins with phosphorus were prepared through the mixture of MDP-Bz and a DPA-phosphazene derivative (DPA-PPZ). The curing behavior of these materials was studied by differential scanning calorimetry (DSC). Finally, the properties of the materials were evaluated by termogravimetric analysis (TGA), dynamic mechanical analysis (DMTA), tensile measurements, limiting oxygen index (LOI) and UL-94 Burn Test.     

Self-foaming diphenolic acid benzoxazine

This work concerns the investigation of porous polybenzoxazines based on the non-toxic renewable diphenolic acid. The approach described relies on the in situ generation of foaming agent (CO₂) during the thermal curing. For this purpose, the previously synthesized benzoxazine monomer from diphenolic acid was thermally polymerized at different temperatures. As the beginning of decarboxylation is about 200 °C, we selected five foaming temperatures (T_f) ranging from 190 to 230 °C. The influence of the foaming temperature on the cellular structure and its dependency on final properties is discussed.