Generating 3D brain tumor regions in MRI using vector-quantization Generative Adversarial Networks.

Medical image analysis has significantly benefited from advancements in deep learning, particularly in the application of Generative Adversarial Networks (GANs) for generating realistic and diverse images that can augment training datasets. The common GAN-based approach is to generate entire image volumes, rather than the region of interest (ROI). Research on deep learning-based brain tumor classification using MRI has shown that it is easier to classify the tumor ROIs compared to the entire image volumes.

3D-printed microstructured alginate scaffolds for neural tissue engineering.

Alginate (Alg) is a versatile biopolymer for scaffold engineering and a bioink component widely used for direct cell printing. However, due to a lack of intrinsic cell-binding sites, Alg must be functionalized for cellular adhesion when used as a scaffold. Moreover, direct cell-laden ink 3D printing requires tedious disinfection procedures and cell viability is compromised by shear stress.

Evaluation of Pore-Former Size and Volume Fraction on Tape Cast Porous 430 Stainless Steel Substrates for Plasma Spraying.

Porous 430L stainless steel disks made by tape casting with various pore-former sizes and volume fractions were evaluated as substrates for solid oxide cell (SOC) fabrication by plasma spraying. This work reports the substrate properties relevant to the SOC operation of disks made by using extra fine metal powder with dense sintering to minimize the fine porosity between particles. In contrast, the coarse porosity is introduced by the pore former.

Bayesian Learning Aided Theoretical Optimization of IrPdPtRhRu High Entropy Alloy Catalysts for the Hydrogen Evolution Reaction.

The complex compositional space of high entropy alloys (HEAs) has shown a great potential to reduce the cost and further increase the catalytic activity for hydrogen evolution reaction (HER) by compositional optimization. Without uncovering the specifics of the HER mechanism on a given HEA surface, it is unfeasible to apply compositional modifications to enhance the performance and save costs. In this work, a combination of density functional theory and Bayesian machine learning is used to demonstrate the unique catalytic mechanism of IrPdPtRhRu HEA catalysts for HER.

High sensing performance flexible nanocomposite sensor with a hybrid nanostructure constructed nanoscale confined motion of nanofibers and nanoplatelets.

The swing process between the construction and destruction of hybrid nanostructures in conductive nanocomposites under an external stimulation plays a pivotal role in their sensing performance and is directly related to the nanoscale motion of the corresponding hybrid nanoparticles. When one-dimensional (1D) nanofibers and two-dimensional (2D) nanoplatelets were selectively distributed in thin cell walls supercritical CO foaming, the confined nanoscale motion of 1D nanofibers and 2D nanoplatelets in the stretching process, including hybrid nanoparticle rotation and separation, was precisely regulated based on the hybrid nanoparticles' Monte Carlo theoretical modelling. Correspondingly, an optimized complex hybrid nanostructure with a suitable nanoparticle content, hybrid ratio and geometry was proposed to achieve a high gauge factor of 4469.

Automated electrosynthesis reaction mining with multimodal large language models (MLLMs).

Leveraging the chemical data available in legacy formats such as publications and patents is a significant challenge for the community. Automated reaction mining offers a promising solution to unleash this knowledge into a learnable digital form and therefore help expedite materials and reaction discovery. However, existing reaction mining toolkits are limited to single input modalities (text or images) and cannot effectively integrate heterogeneous data that is scattered across text, tables, and figures.

Generation of Backward-Looking Complex Reflections for a Motivational Interviewing-Based Smoking Cessation Chatbot Using GPT-4: Algorithm Development and Validation.

Background: Motivational interviewing (MI) is a therapeutic technique that has been successful in helping smokers reduce smoking but has limited accessibility due to the high cost and low availability of clinicians. To address this, the MIBot project has sought to develop a chatbot that emulates an MI session with a client with the specific goal of moving an ambivalent smoker toward the direction of quitting. One key element of an MI conversation is reflective listening, where a therapist expresses their understanding of what the client has said by uttering a reflection that encourages the client to continue their thought process.

Heteroatom-vacancy centres in molecular nanodiamonds: a computational study of organic molecules possessing triplet ground states through σ-overlap.

Small molecules possessing a triplet ground state are fundamentally intriguing but also in high demand for applications such as quantum sensing and quantum computing. Such molecules are rare, and most examples involve extended π-systems. Topology and shape of the spin density will be very different for molecules where the triplet state arises from σ-overlap.

Multi-Functional Silole Hole Transport Layer for Efficient and Stable Lead-Tin Perovskite and Tandem Solar Cells.

Despite high theoretical efficiencies and rapid improvements in performance, high-efficiency ≈1.2 eV mixed Sn-Pb perovskite solar cells (PSCs) generally rely on poly(3,4-ethylenedioxythiophene) polystyrenesulfonate (PEDOT: PSS) as the hole transport layer (HTL); a material that is considered to be a bottleneck for long-term stability due to its acidity and hygroscopic nature. Seeking to replace PEDOT: PSS with an alternative HTL with improved atmospheric and thermal stability, herein, a silole derivative (Silole-COOH) tuned with optimal electronic properties and efficient carrier transport by incorporating a carboxyl functional group is designed, which results in an optimal band alignment for hole extraction from Sn-Pb perovskites and robust air and thermal stability.

Sample-to-answer centrifugal microfluidic droplet PCR platform for quantitation of viral load.

Droplet digital polymerase chain reaction (ddPCR) stands out as a highly sensitive diagnostic technique that is gaining traction in infectious disease diagnostics due to its ability to quantitate very low numbers of viral gene copies. By partitioning the sample into thousands of droplets, ddPCR enables precise and absolute quantification without relying on a standard curve. However, current ddPCR systems often exhibit relatively low levels of integration, and the analytical process remains dependent on elaborate workflows for up-front sample preparation.

Microfluidic Platform for Generating and Releasing Patient-Derived Cancer Organoids with Diverse Shapes: Insight into Shape-Dependent Tumor Growth.

Multicellular spheroids and patient-derived organoids find many applications in fundamental research, drug discovery, and regenerative medicine. Advances in the understanding and recapitulation of organ functionality and disease development require the generation of complex organoid models, including organoids with diverse morphologies. Microfluidics-based cell culture platforms enable time-efficient confined organoid generation.

Scaling CO Electrolyzer Cell Area from Bench to Pilot.

To contribute meaningfully to carbon dioxide (CO) emissions reduction, CO electrolyzer technology will need to scale immensely. Bench-scale electrolyzers are the norm, with active areas <5 cm. However, cell areas on the order of 100s or 1000s of cm will be required for industrial deployment.

Resurfacing of InAs Colloidal Quantum Dots Equalizes Photodetector Performance across Synthetic Routes.

The synthesis of highly monodispersed InAs colloidal quantum dots (CQDs) is needed in InAs CQD-based optoelectronic devices. Because of the complexities of working with arsenic precursors such as tris-trimethylsilyl arsine ((TMSi)As) and tris-trimethylgermyl arsine ((TMGe)As), several attempts have been made to identify new candidates for synthesis; yet, to date, only the aforementioned two highly reactive precursors have led to excellent photodetector device performance. We begin the present study by investigating the mechanism, finding that the use of the cosurfactant dioctylamine plays a crucial role in producing monodispersed InAs populations.

Two-Dimensional Nanorod-Shaped Co(II) Coordination Polymer on Three-Dimensional Metallic Foam: A Hybrid Platform for Electrochemical Oxidation of Glucose.

This study unveils a novel electrochemical biosensor for monitoring glucose in biological fluids by employing nanorods of a cobalt-bispyridyl/dicarboxylate framework grown in a layer-by-layer manner on a highly porous nickel substrate. The hybrid microporous system has a bicatalytic effect on glucose oxidation due to the synergistic catalytic impact of the nickel and cobalt ions with varying oxidation states as electroactive sites. In addition, the controlled growth of inorganic-organic frameworks changes the mechanism of electron transfer from a diffusion-controlled process to an adsorption-controlled process, thus yielding a low onset oxidation potential (∼0.

Rehabilitation exercise quality assessment through supervised contrastive learning with hard and soft negatives.

Exercise-based rehabilitation programs have proven to be effective in enhancing the quality of life and reducing mortality and rehospitalization rates. AI-driven virtual rehabilitation, which allows patients to independently complete exercises at home, utilizes AI algorithms to analyze exercise data, providing feedback to patients and updating clinicians on their progress. These programs commonly prescribe a variety of exercise types, leading to a distinct challenge in rehabilitation exercise assessment datasets: while abundant in overall training samples, these datasets often have a limited number of samples for each individual exercise type.

Synergistic Layered Design of Aerogel Nanocomposite of Graphene Nanoribbon/MXene with Tunable Absorption Dominated Electromagnetic Interference Shielding.

Electromagnetic pollution presents growing challenges due to the rapid expansion of portable electronic and communication systems, necessitating lightweight materials with superior shielding capabilities. While prior studies focused on enhancing electromagnetic interference (EMI) shielding effectiveness (SE), less attention is given to absorption-dominant shielding mechanisms, which mitigate secondary pollution. By leveraging material science and engineering design, a layered structure is developed comprising rGOnR/MXene-PDMS nanocomposite and a MXene film, demonstrating exceptional EMI shielding and ultra-high electromagnetic wave absorption.

Natural Frequency Transmissibility for Detection of Cracks in Horizontal Axis Wind Turbine Blades.

Defects on horizontal axis wind turbine blades are difficult to identify and monitor with conventional forms of non-destructive examination due to the blade's large size and limited accessibility during continuous operation. This article examines both strain and acceleration transmissibility as methods of continuous damage detection on wind turbine blades. A scaled 117 cm offshore wind turbine blade was first designed, 3D printed, and modelled numerically in ANSYS.

Vaccination for communicable endemic diseases: optimal allocation of initial and booster vaccine doses.

For some communicable endemic diseases (e.g., influenza, COVID-19), vaccination is an effective means of preventing the spread of infection and reducing mortality, but must be augmented over time with vaccine booster doses.

Self-Assembly of Strain-Adaptable Surface-Enhanced Raman Scattering Substrate on Polydimethylsiloxane Nanowrinkles.

Flexible surface-enhanced Raman scattering (SERS) substrates adaptable to strains enable effective sampling from irregular surfaces, but the preparation of highly stable and sensitive flexible SERS substrates is still challenging. This paper reports a method to fabricate a high-performance strain-adaptable SERS substrate by self-assembly of Au nanoparticles (AuNPs) on polydimethylsiloxane (PDMS) nanowrinkles. Nanowrinkles are created on prestrained PDMS slabs by plasma-induced oxidation followed by the release of the prestrain, and self-assembled AuNPs are transferred onto the nanowrinkles to construct the high-performance SERS substrate.

Lightweight Dual-Functional Segregated Nanocomposite Foams for Integrated Infrared Stealth and Absorption-Dominant Electromagnetic Interference Shielding.

Lightweight infrared stealth and absorption-dominant electromagnetic interference (EMI) shielding materials are highly desirable in areas of aerospace, weapons, military and wearable electronics. Herein, lightweight and high-efficiency dual-functional segregated nanocomposite foams with microcellular structures are developed for integrated infrared stealth and absorption-dominant EMI shielding via the efficient and scalable supercritical CO (SC-CO) foaming combined with hydrogen bonding assembly and compression molding strategy. The obtained lightweight segregated nanocomposite foams exhibit superior infrared stealth performances benefitting from the synergistic effect of highly effective thermal insulation and low infrared emissivity, and outstanding absorption-dominant EMI shielding performances attributed to the synchronous construction of microcellular structures and segregated structures.

A combined AIMD and DFT study of the low-energy radiation responses of GaN.

Although GaN is a promising candidate for semiconductor devices, degradation of GaN-based device performance may occur when the device is bombarded by high-energy charged particles during its application in aerospace, astronomy, and nuclear-related areas. It is thus of great significance to explore the influence of irradiation on the microstructure and electronic properties of GaN and to reveal the internal relationship between the damage mechanisms and physical characteristics. Using a combined density functional theory (DFT) and molecular dynamics (AIMD) study, we explored the low-energy recoil events in GaN and the effects of point defects on GaN.

Multifunctional Applications Enabled by Fluorination of Hexagonal Boron Nitride.

2D materials exhibit exceptional properties as compared to their macroscopic counterparts, with promising applications in nearly every area of science and technology. To unlock further functionality, the chemical functionalization of 2D structures is a powerful technique that enables tunability and new properties within these materials. Here, the successful effort to chemically functionalize hexagonal boron nitride (hBN), a chemically inert 2D ceramic with weak interlayer forces, using a gas-phase fluorination process is exploited.