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Herein, the effects of the precursor solution's acidity level on the crystal structure, morphology, nucleation, and growth of WO3·nH2O and WO3 nanostructures are reported. Structural investigations on WO3·nH2O using X-ray diffraction and Fourier–transform infrared spectroscopy confirm that the quantity of hydrate groups increases due to the interaction between H+ and water molecules with increasing HCl volume. Surface analysis results support our claim that the evolution of grain size, surface roughness, and growth direction on WO3·nH2O and WO3 nanostructures rely on the precursor solution's pH value. Consequently, the photocurrent density of a WO3 photoanode using a HCl-5 mL sample achieves the best results with 0.9 mA/cm2 at 1.23 V vs. a reversible hydrogen electrode (RHE). We suggest that the improved photocurrent density of the HCl-5 mL sample is due to the efficient light absorption from the densely grown WO3 nanoplates on a substrate and that its excellent charge transport kinetics originate from the large surface area, low charge transfer resistance, and fast ion diffusion through the photoanode/electrolyte interface. [ABSTRACT FROM AUTHOR]

Pressure ulcers (PUs) are a prevalent skin disease affecting patients with impaired mobility and in high-risk groups. These ulcers increase patients' suffering, medical expenses, and burden on medical staff. This study introduces a clinical decision support system and verifies it for predicting real-time PU occurrences within the intensive care unit (ICU) by using MIMIC-IV and in-house ICU data. We develop various machine learning (ML) and deep learning (DL) models for predicting PU occurrences in real time using the MIMIC-IV and validate using the MIMIC-IV and Kangwon National University Hospital (KNUH) dataset. To address the challenge of missing values in time series, we propose a novel recurrent neural network model, GRU-D++. This model outperformed other experimental models by achieving the area under the receiver operating characteristic curve (AUROC) of 0.945 for the on-time prediction and AUROC of 0.912 for 48h in-advance prediction. Furthermore, in the external validation with the KNUH dataset, the fine-tuned GRU-D++ model demonstrated superior performances, achieving an AUROC of 0.898 for on-time prediction and an AUROC of 0.897 for 48h in-advance prediction. The proposed GRU-D++, designed to consider temporal information and missing values, stands out for its predictive accuracy. Our findings suggest that this model can significantly alleviate the workload of medical staff and prevent the worsening of patient conditions by enabling timely interventions for PUs in the ICU. [ABSTRACT FROM AUTHOR]

A nitrate-sensing system that consists of a micromachined sensor substrate, anion-permeable membrane, integrated microfluidic channels, and standard fluidic connectors has been designed, fabricated, assembled, and tested. Our microsensor was designed for in-situ monitoring of nitrate concentrations in ground water. A silver electrode was patterned for amperometric nitrate detection. An electrochemically oxidized silver electrode was used as a reference electrode. Microfluidic channels were fabricated as flow paths to the microelectrochemical (MEC) cell for the eluent and ground-water sample. The sensor also incorporates an anion-permeable membrane that is used for selective measurement of nitrate. With standard addition methods, linear calibration curves have been obtained and the detection limit is ~1 μM. To test selectivity, the sensor response to a 100-μM-nitrate solution and a mixture of nitrate and interfering ions (100 μM each of NO₃⁻, PO₄⁻², SO₄⁻³, F⁻, and Cl⁻) were compared. Despite the 400% increase in total ionic concentration, the sensor output only increased 13.9%.

Nitrate-sensing system that consists of a micromachined sensor substrate, nitrate-permeable membrane, integrated microfluidic channels, and standard fluidic connectors has been designed, fabricated, assembled, and tested. Our microsensor was designed for in-situ monitoring of nitrate concentrations in ground water. A silver electrode was patterned for amperometric nitrate detection. An electrochemically oxidized silver electrode was used as a reference electrode. Microfluidic channels were fabricated as flow paths for the eluent and ground-water sample to the microelectrochemical (MEC) cell. The sensor also incorporates a nitrate-permeable membrane that is used for selective measurement of nitrate. The sensor has a linear response over concentration ranging from 1 μM to 1 mM.

We study the collective behaviors of an attractively coupled system of swarm sphere models. The swarm sphere model is a prototype particle model describing the aggregate dynamics of particles on a sphere under suitable conditions on system parameters and initial data. In this paper, we investigate emergent dynamics resulting from the attractive coupling of two swarm sphere models with heterogeneous system parameters such as natural frequency matrices, frustration matrices, and inter and intra coupling strengths. Due to the intricate interplay between system parameters, several collective behaviors of the whole mixed ensemble emerge. To this end, we provide several sufficient frameworks leading to the local and global aggregation dynamics that can be achieved in both complete and practical senses. The proposed frameworks are formulated in terms of system parameters and initial data, and we provide local and global aggregation estimates within the proposed frameworks. As a direct application of emergent dynamics, we show that the swarm sphere model with a uniform frustration is uniformly $ \ell_2 $-stable with respect to initial data. [ABSTRACT FROM AUTHOR]

Phase control in Hf1-xZrxO2 (HZO) is crucial for optimizing its electrical properties, such as ferroelectricity and high dielectricity. However, phase optimization in HZO has remained challenging due to limited theoretical understanding. This work devised an atomistic methodology based on density functional theory calculations to predict the phase fractions in HZO. The detailed phase evolution and phase fractions during the sequential processes of crystallization, annealing, and cooling were predicted by calculating the nucleation barrier from amorphous, the transition barrier between polymorphs, and Boltzmann fractions, considering the combined effects of composition (x), grain size (dT), and annealing temperature (Tannealing). The findings revealed that the polar orthorhombic (PO) phase exhibited the highest fraction at Tannealing = 770 K in Hf0.5Zr0.5O2, resulting in maximum ferroelectricity. Meanwhile, the fractions of PO and tetragonal phases are similar at dT = 7 nm in Hf0.4Zr0.6O2 and dT = 11 nm in Hf0.3Zr0.7O2, both at Tannealing = 770 K, leading to the highest dielectricity. These results are highly consistent with the experimental results. This work demonstrates that the comprehensive interpretations of both thermodynamic and kinetic effects are essential for quantitatively predicting the phase fraction and their corresponding electrical functionality. [ABSTRACT FROM AUTHOR]