Clinical domain knowledge-derived template improves post hoc AI explanations in pneumothorax classification.

Objective: Pneumothorax is an acute thoracic disease caused by abnormal air collection between the lungs and chest wall. Recently, artificial intelligence (AI), especially deep learning (DL), has been increasingly employed for automating the diagnostic process of pneumothorax. To address the opaqueness often associated with DL models, explainable artificial intelligence (XAI) methods have been introduced to outline regions related to pneumothorax.

Reliable segmentation of multiple lesions from medical images.

Background: Focusing on the complicated pathological features, such as blurred boundaries, severe scale differences between symptoms, and background noise interference, we aim to enhance the reliability of multiple lesions joint segmentation from medical images.

Purpose: Propose a novel reliable multi-scale wavelet-enhanced transformer network, which can provide accurate segmentation results with reliability assessment.

Methods: Focusing on enhancing the model's capability to capture intricate pathological features in medical images, this work introduces a novel segmentation backbone.

Congested C(sp3)-rich architectures enabled by iron-catalysed conjunctive alkylation.

Catalytic cross-coupling by transition metals has revolutionized the formation of C-C bonds in organic synthesis. However, the challenge of forming multiple alkyl-alkyl bonds in crowded environments remains largely unresolved. Here, we report the regioselective functionalization of olefins with sp-hybridized organohalides and organozinc reagents using a simple (terpyridine)iron catalyst.

Atomistic Characterization of Healthy and Damaged Hair Surfaces: A Molecular Dynamics Simulation Study of Fatty Acids on Protein Layer.

Amid the bourgeoning demand for in-silico designed, environmentally sustainable, and highly effective hair care formulations, a growing interest is evident in the exploration of realistic computational model for the hair surface. In this work, we present an atomistic model for the outermost layer of the hair surface derived through molecular dynamics simulations, which comprises 18-Methyleicosanoic acid (18-MEA) fatty acid chains covalently bound onto the keratin-associated protein 10-4 (KAP10-4) at a spacing distance of ~1 nm. Remarkably, this hair surface model facilitates the inclusion of free fatty acids (free 18-MEA) into the gaps between chemically bound 18-MEA chains, up to a maximum number that results in a packing density of 0.

Confidence-aware multi-modality learning for eye disease screening.

Multi-modal ophthalmic image classification plays a key role in diagnosing eye diseases, as it integrates information from different sources to complement their respective performances. However, recent improvements have mainly focused on accuracy, often neglecting the importance of confidence and robustness in predictions for diverse modalities. In this study, we propose a novel multi-modality evidential fusion pipeline for eye disease screening.

Co-training based prediction of multi-label protein-protein interactions.

Prediction of protein-protein interaction (PPI) types enhances the comprehension of the underlying structural characteristics and functions of proteins, which gives rise to a multi-label classification problem. The nominal features describe the physicochemical characteristics of proteins directly, establishing a more robust correlation with the interaction types between proteins than ordered features. Motivated by this, we propose a multi-label PPI prediction model referred to as CoMPPI (Co-training based Multi-Label prediction of Protein-Protein Interaction).

Iterative feedback-based models for image and video polyp segmentation.

Accurate segmentation of polyps in colonoscopy images has gained significant attention in recent years, given its crucial role in automated colorectal cancer diagnosis. Many existing deep learning-based methods follow a one-stage processing pipeline, often involving feature fusion across different levels or utilizing boundary-related attention mechanisms. Drawing on the success of applying Iterative Feedback Units (IFU) in image polyp segmentation, this paper proposes FlowICBNet by extending the IFU to the domain of video polyp segmentation.

The role of microstructure in the thermal fatigue of solder joints.

Thermal fatigue is a common failure mode in electronic solder joints, yet the role of microstructure is incompletely understood. Here, we quantify the evolution of microstructure and damage in Sn-3Ag-0.5Cu joints throughout a ball grid array (BGA) package using EBSD mapping of localised subgrains, recrystallisation and heavily coarsened AgSn.

A mechanically robust spiral fiber with ionic-electronic coupling for multimodal energy harvesting.

Wearable electronics are some of the most promising technologies with the potential to transform many aspects of human life such as smart healthcare and intelligent communication. The design of self-powered fabrics with the ability to efficiently harvest energy from the ambient environment would not only be beneficial for their integration with textiles, but would also reduce the environmental impact of wearable technologies by eliminating their need for disposable batteries. Herein, inspired by classical Archimedean spirals, we report a metastructured fiber fabricated by scrolling followed by cold drawing of a bilayer thin film of an MXene and a solid polymer electrolyte.

Deterministic positioning and alignment of a single-molecule exciton in plasmonic nanodimer for strong coupling.

Experimental realization of strong coupling between a single exciton and plasmons remains challenging as it requires deterministic positioning of the single exciton and alignment of its dipole moment with the plasmonic fields. This study aims to combine the host-guest chemistry approach with the cucurbit[7]uril-mediated active self-assembly to precisely integrate a single methylene blue molecule in an Au nanodimer at the deterministic position (gap center of the nanodimer) with the maximum electric field (EF) and perfectly align its transition dipole moment with the EF, yielding a large spectral Rabi splitting of 116 meV for a single-molecule exciton-matching the analytical model and numerical simulations. Statistical analysis of vibrational spectroscopy and dark-field scattering spectra confirm the realization of the single exciton strong coupling at room temperature.

Linear Electro-Optic Effect in 2D Ferroelectric for Electrically Tunable Metalens.

The advent of 2D ferroelectrics, characterized by their spontaneous polarization states in layer-by-layer domains without the limitation of a finite size effect, brings enormous promise for applications in integrated optoelectronic devices. Comparing with semiconductor/insulator devices, ferroelectric devices show natural advantages such as non-volatility, low energy consumption and high response speed. Several 2D ferroelectric materials have been reported, however, the device implementation particularly for optoelectronic application remains largely hypothetical.

Ionic Hydrogen Bond-Assisted Catalytic Construction of Nitrogen Stereogenic Center via Formal Desymmetrization of Remote Diols.

The control of noncarbon stereogenic centers is of profound importance owing to their enormous interest in bioactive compounds and chiral catalyst or ligand design for enantioselective synthesis. Despite various elegant approaches have been achieved for construction of S-, P-, Si- and B-stereocenters over the past decades, the catalyst-controlled strategies to govern the formation of N-stereogenic compounds have garnered less attention. Here, we disclose the first organocatalytic approach for efficient access to a wide range of nitrogen-stereogenic compounds through a desymmetrization approach.

Overcoming strength-ductility tradeoff with high pressure thermal treatment.

Conventional material processing approaches often achieve strengthening of materials at the cost of reduced ductility. Here, we show that high-pressure and high-temperature (HPHT) treatment can help overcome the strength-ductility trade-off in structural materials. We report an initially strong-yet-brittle eutectic high entropy alloy simultaneously doubling its strength to 1150 MPa and its tensile ductility to 36% after the HPHT treatment.

One Stone Two Birds: Anomalously Enhancing the Cross-Plane and In-Plane Heat Transfer in 2D/3D Heterostructures by Defects Engineering.

This study addresses a crucial challenge in two-dimensional (2D) material-based electronic devices-inefficient heat dissipation across the van der Waals (vdW) interface connecting the 2D material to its three-dimensional (3D) substrate. The objective is to enhance the interfacial thermal conductance (ITC) of 2D/3D heterostructures without compromising the intrinsic thermal conductivities (κ) of 2D materials. Using 2D-MoS/3D-GaN as an example, a novel strategy to enhance both the ITC across 2D/3D interface and κ of 2D material is proposed by introducing a controlled concentration (ρ) of vacancy defects to substrate's bottom surface.

Optical coherence tomography choroidal enhancement using generative deep learning.

Spectral-domain optical coherence tomography (SDOCT) is the gold standard of imaging the eye in clinics. Penetration depth with such devices is, however, limited and visualization of the choroid, which is essential for diagnosing chorioretinal disease, remains limited. Whereas swept-source OCT (SSOCT) devices allow for visualization of the choroid these instruments are expensive and availability in praxis is limited.

Massive field-of-view sub-cellular traction force videography enabled by Single-Pixel Optical Tracers (SPOT).

We report a massive field-of-view and high-speed videography platform for measuring the sub-cellular traction forces of more than 10,000 biological cells over 13 mm at 83 frames per second. Our Single-Pixel Optical Tracers (SPOT) tool uses 2-dimensional diffraction gratings embedded into a soft substrate to convert cells' mechanical traction force into optical colors detectable by a video camera. The platform measures the sub-cellular traction forces of diverse cell types, including tightly connected tissue sheets and near isolated cells.

Self-assembly of peptide nanocapsules by a solvent concentration gradient.

Biological systems can create materials with intricate structures and specialized functions. In comparison, precise control of structures in human-made materials has been challenging. Here we report on insect cuticle peptides that spontaneously form nanocapsules through a single-step solvent exchange process, where the concentration gradient resulting from the mixing of water and acetone drives the localization and self-assembly of the peptides into hollow nanocapsules.

An Atomically Resolved Schottky Barrier Height Approach for Bridging the Gap between Theory and Experiment at Metal-Semiconductor Heterojunctions.

We propose an atomically resolved approach to capture the spatial variations of the Schottky barrier height (SBH) at metal-semiconductor heterojunctions. This proposed scheme, based on atom-specific partial density of states (PDOS) calculations, further enables calculation of the effective SBH that aligns with conductance measurements. We apply this approach to study the variations of SBH at MoS@Au heterojunctions, in which MoS contains conducting and semiconducting grain boundaries (GBs).

Dual Redox Reaction Sites for Pseudocapacitance Based on Ti and -P Functional Groups of TiCPBr MXene.

MXenes have extensive applications due to their different properties determined by intrinsic structures and various functional groups. Exploring different functional groups of MXenes leads to improved performance or potential applications. In this work, we prepared new TiCPBr (x=0.

Certifying Sets of Quantum Observables with Any Full-Rank State.

We show that some sets of quantum observables are unique up to an isometry and have a contextuality witness that attains the same value for any initial state. We prove that these two properties make it possible to certify any of these sets by looking at the statistics of experiments with sequential measurements and using any initial state of full rank, including thermal and maximally mixed states. We prove that this "certification with any full-rank state" (CFR) is possible for any quantum system of finite dimension d≥3 and is robust and experimentally useful in dimensions 3 and 4.

Origami metamaterials for ultra-wideband and large-depth reflection modulation.

The dynamic control of electromagnetic waves is a persistent pursuit in modern industrial development. The state-of-the-art dynamic devices suffer from limitations such as narrow bandwidth, limited modulation range, and expensive features. To address these issues, we fuse origami techniques with metamaterial design to achieve ultra-wideband and large-depth reflection modulation.