Designing user-centered decision support systems for climate disasters: What information do communities and rescue responders need during floods?

Flooding events are the most common natural hazard globally, resulting in vast destruction and loss of life. An effective flood emergency response is necessary to lessen the negative impacts of flood disasters. However, disaster management and response efforts face a complex scenario.

MetaQA: Enhancing human-centered data search using Generative Pre-trained Transformer (GPT) language model and artificial intelligence.

Accessing and utilizing geospatial data from various sources is essential for developing scientific research to address complex scientific and societal challenges that require interdisciplinary knowledge. The traditional keyword-based geosearch approach is insufficient due to the uncertainty inherent within spatial information and how it is presented in the data-sharing platform. For instance, the Gulf of Mexico Coastal Ocean Observing System (GCOOS) data search platform stores geoinformation and metadata in a complex tabular.

Development of a Multi-target Protein Biomarker Assay for Circulating Tumor Cells.

We report a highly sensitive and selective CNT-switch liquid biopsy platform that detects and quantifies protein biomarker expressions from circulating tumor cells in blood for early detection of metastatic breast cancer and its relapse. This platform first isolates and enriches more than 99% of tumor cells with an off-chip micro-size membrane filtration technique and then conducts on-chip detection of the membrane and internal protein biomarkers of the tumor cells with high sensitivity and selectivity. High sensitivity is achieved with complete association of the antibody-antigen-antibody (Ab-Ag-Ab) complex by precisely and rapidly assembling carbon nanotubes (CNTs) across two parallel electrodes via sequential DC electrophoresis and dielectrophoresis (DEP) deposition.

Modeling Spatiotemporal Pattern of Depressive Symptoms Caused by COVID-19 Using Social Media Data Mining.

By 29 May 2020, the coronavirus disease (COVID-19) caused by SARS-CoV-2 had spread to 188 countries, infecting more than 5.9 million people, and causing 361,249 deaths. Governments issued travel restrictions, gatherings of institutions were cancelled, and citizens were ordered to socially distance themselves in an effort to limit the spread of the virus.

Towards perturbation prediction of biological networks using deep learning.

The mapping of the physical interactions between biochemical entities enables quantitative analysis of dynamic biological living systems. While developing a precise dynamical model on biological entity interaction is still challenging due to the limitation of kinetic parameter detection of the underlying biological system. This challenge promotes the needs of topology-based models to predict biochemical perturbation patterns.

A shear-enhanced CNT-assembly nanosensor platform for ultra-sensitive and selective protein detection.

Detection and quantification of low-concentration proteins in heterogeneous media are generally plagued by two distinct obstacles: lack of sensitivity due to high dissociation equilibrium constant K and non-specificity due to an abundance of non-targets with similar K. Herein, we report a nanoscale protein-sensing platform with a non-equilibrium on-off switch that employs dielectrophoretic and hydrodynamic shear forces to overcome these thermodynamic limitations with irreversible kinetics. The detection sensitivity is achieved with complete association of the antibody-antigen-antibody (Ab-Ag-Ab) complex by precisely and rapidly assembling carbon nanotubes (CNT) across two parallel electrodes via sequential DC electrophoresis and AC dielectrophoresis (DEP), and with single-CNT electron tunneling conductance.

A comparison of atomistic and continuum approaches to the study of bonding dynamics in electrocatalysis: microcantilever stress and in situ EXAFS observations of platinum bond expansion due to oxygen adsorption during the oxygen reduction reaction.

Microcantilever stress measurements are examined to contrast and compare their attributes with those from in situ X-ray absorption spectroscopy to elucidate bonding dynamics during the oxygen reduction reaction (ORR) on a Pt catalyst. The present work explores multiple atomistic catalyst properties that notably include features of the Pt-Pt bonding and changes in bond strains that occur upon exposure to O2 in the electrochemical environment. The alteration of the Pt electronic and physical structures due to O2 exposure occurs over a wide potential range (1.

All-nanoparticle layer-by-layer surface modification of micro- and ultrafiltration membranes.

Layer-by-layer (LbL) deposition using primarily inorganic silica nanoparticles is employed for surface modification of polymeric micro- and ultrafiltration (MF/UF) membranes to produce novel thin film composite (TFC) membranes intended for nanofiltration (NF) and reverse osmosis (RO) applications. A wide variety of porous substrate membranes with different surface characteristics are successfully employed. This report gives detailed results for polycarbonate track etched (PCTE), polyethersulfone (PES), and sulfonated PES (SPEES) MF/UF substrates.