Dual Effects of Brown Algae Impurities on Coral Concrete: Sulfate Resistance Decay and Multiscale Predictive Modeling

Modelling the impact of temperature on nanocarrier behavior: Thermodynamics, structural transitions, and drug release.

A rational design for next-generation thermo-responsive nanocarriers is proposed, in which polymer chemistry, nanoparticle structure, experimental characterization, and mechanistic modelling are integrated from the earliest stages of material development.

Modeling Environmentally Driven Seasonal Moisture Migration and Ground Movements in Expansive Clays

This paper describes the formulation of a numerical model for simulating environmentally driven one-dimensional (1D) ground movements of expansive clay. The formulation is based on a finite-element model that simulates the redistribution of matric suction through a diffusion-type equation, explicitly accounting for volume changes due to wetting and drying of the clay. We synthesize and modify highly nonlinear constitutive relationships for (1) hysteretic soil water retention; (2) reversible soil shrinkage and expansion of clay; and (3) hydraulic conductivity, explicitly incorporating desiccation cracks through a multidomain framework and assuming a critical surface crack depth. These models are well-calibrated to published laboratory tests on a reference expansive clay, Denver bentonite. We demonstrate capabilities of the proposed formulation to simulate the response of a homogeneous expansive clay to periods of drying and wetting, considering the initial matric suction, saturated hydraulic conductivity of the intact clay, and critical crack depth as three primary sources of uncertainty. We compare ensemble model simulations with measured ground movements from an instrumented expansive clay test site in Texas over a 3-year period using detailed records of potential evapotranspiration and precipitation. By assigning weights to the ensemble simulations based on their performance, we constrain the ranges of the three key uncertain parameters. The results showed very reasonable first-order agreement with the measured data and highlight the potential of the proposed formulation. We anticipate that more reliable predictions can be achieved through direct measurements of actual in situ evaporation rates and local soil properties.

Numerical Simulation and Optimization of Airflow Distribution Characteristics in the Air Distribution Chamber of a Needle-type Forage Dryer

To address uneven air supply among multiple needle tubes during the drying of high-density forage bales, this study investigated the airflow characteristics and structural optimization of the upper and lower air distribution chambers of a needle-type forage dryer. A three-dimensional CFD model was established, and airflow performance was evaluated using the velocity non-uniformity coefficient M and the inlet-to-outlet total pressure drop Δp. Response surface methodology was used to optimize the key structural parameters. For the upper chamber, installation of a T-shaped baffle and optimization of the cavity height Hc, diffuser angle α, and top-plate opening area ratio Ra yielded an optimal combination of Hc = 133.29 mm, α = 12.51°, and Ra = 1.12, reducing M from 11.2264% to 3.3886%. For the lower chamber, a strip-perforated airflow equalizing plate with Hb = 74.82 mm, D = 23.79 mm, and W = 25.03 mm reduced M from 9.8772% to 1.5484%, with Δp of approximately 130 Pa. Mesh-refinement and turbulence-model sensitivity analyses supported the robustness of the numerical predictions. Repeated outlet-velocity measurements yielded mean absolute relative errors of 3.09%–4.58%. Smoke visualization and grayscale analysis further indicated that the optimized structures enhanced airflow diffusion and redistribution. The results provide guidance for air distribution chamber design in needle-type forage dryers.

DiTFusion: Prostate magnetic resonance image fusion based on Scalable Diffusion Models with transformers

p-LDM: Partitioned latent diffusion model for memory-efficient 3D medical image translation

CHAI – Compliant Human-centered Adaptive Interaction through Diffusion-based Language Trajectory Transformer

CHAI (Compliant Human-centered Adaptive Interaction), a novel language-driven framework for real-time modulation of a robot’s kinematics and mechanical compliance in real-world environments, introduces on-the-fly language-driven impedance (compliance) modulation along both translational and rotational directions.