Hierarchically Porous Poly(aryl thioether)s Through Dynamic Linker Engineering for Thiyl Radical Photocatalysis.

Hierarchically porous polymers offer large surface areas for enhanced catalytic activity, but incorporating photocatalytic sites into these pore channels remains challenging. Inspired by nature's disulfide bonds, which stabilize proteins and enable redox activity, this study introduces a hierarchically porous poly(aryl thioether) photocatalyst via dual disulfide and thioether linkages formed by polycondensation. Thiolate intermediates undergo partial oxidation in air, yielding a micro/mesoporous polymer with a 757 m g⁻¹ surface area, comparable to its microporous counterpart synthesized in N₂.

Designing Robust Quasi-2D Perovskites Thin Films for Stable Light-Emitting Applications.

Quasi-2D perovskite made with organic spacers co-crystallized with inorganic cesium lead bromide inorganics is demonstrated for near unity photoluminescence quantum yield at room temperature. However, light emitting diodes made with quasi-2D perovskites rapidly degrade which remains a major bottleneck in this field. In this work, It is shown that the bright emission originates from finely tuned multi-component 2D nano-crystalline phases that are thermodynamically unstable.

Comparative photocatalytic degradation of cationic rhodamine B and anionic bromocresol green using reduced ZnO: A detailed kinetic modeling approach.

The photocatalytic degradation of rhodamine B (RhB), a cationic dye, and bromocresol green (BCG), an anionic dye, was investigated using oxygen vacancy-enriched ZnO as the catalyst. These dyes were selected due to their differing charges and molecular structures, allowing for a deeper exploration of how these characteristics impact the degradation process. The catalyst was prepared by reducing ZnO with 10% H/Ar gas at 500 °C, and the introduction of oxygen vacancies was confirmed using various characterization techniques.

Understanding Standard Procedure in Auditory Brainstem Response: Importance of Normative Data.

The auditory brainstem response (ABR) is a noninvasive test that measures neural activity in response to auditory stimuli. Racial differences in head shape have provided strong evidence for specific normative data and accurate device calibration. International standards emphasize the need for standardized procedures and references.

Real-time chlorophyll-a forecasting using machine learning framework with dimension reduction and hyperspectral data.

Since water is an essential resource in various fields, it requires constant monitoring. Chlorophyll-a concentration is a crucial indicator of water quality and can be used to monitor water quality. In this study, we developed methods to forecast chlorophyll-a concentrations in real-time using hyperspectral data on IoT platform and various machine learning algorithms.

Encapsulated stretchable amphibious strain sensors.

Soft and stretchable strain sensors have found wide applications in health monitoring, motion tracking, and robotic sensing. There is a growing demand for strain sensors in amphibious environments, such as implantable sensors, wearable sensors for swimmers/divers, and underwater robotic sensors. However, developing a sensitive, stretchable, and robust amphibious strain sensor remains challenging.

Anomalous Correlation between Thermal Conductivity and Elastic Modulus in Two-Dimensional Hybrid Metal Halide Perovskites.

Device-level implementation of soft materials for energy conversion and thermal management demands a comprehensive understanding of their thermal conductivity and elastic modulus to mitigate thermo-mechanical challenges and ensure long-term stability. Thermal conductivity and elastic modulus are usually positively correlated in soft materials, such as amorphous macromolecules, which poses a challenge to discover materials that are either soft and thermally conductive or hard and thermally insulative. Here, we show anomalous correlations of thermal conductivity and elastic modulus in two-dimensional (2D) hybrid organic-inorganic perovskites (HOIP) by engineering the molecular interactions between organic cations.

Synthesis and Optical Properties of One Year Air-Stable Chiral Sb(III) Halide Semiconductors.

Chiral hybrid metal-halide semiconductors (MHS) pose as ideal candidates for spintronic applications owing to their strong spin-orbit coupling (SOC), and long spin relaxation times. Shedding light on the underlying structure-property relationships is of paramount importance for the targeted synthesis of materials with an optimum performance. Herein, we report the synthesis and optical properties of 1D chiral (-/-THBTD)SbBr (THBTD = 4,5,6,7-tetrahydro-benzothiazole-2,6-diamine) semiconductors using a multifunctional ligand as a countercation and a structure directing agent.

Effects of hole transporting PEDOT:PSS on the photoemission of upconverted hot electron in Mn-doped CdS/ZnS quantum dots.

In this work, we investigated the effect of hole transporting poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS) interfacing with Mn-doped CdS/ZnS quantum dots (QDs) deposited on an indium tin oxide (ITO) substrate on the photoemission of upconverted hot electrons under weak continuous wave photoexcitation in a vacuum. Among the various factors that can influence the photoemission of the upconverted hot electrons, we studied the role of PEDOT:PSS in facilitating the hole transfer from QDs and altering the energy of photoemitted hot electrons. Compared to hot electrons emitted from QDs deposited directly on the ITO substrate, the addition of the PEDOT:PSS layer between the QD and ITO layers increased the energy of the photoemitted hot electrons.

Unveiling the Fatigue Behavior of 2D Hybrid Organic-Inorganic Perovskites: Insights for Long-Term Durability.

2D hybrid organic-inorganic perovskites (HOIPs) are commonly found under subcritical cyclic stresses and suffer from fatigue issues during device operation. However, their fatigue properties remain unknown. Here, the fatigue behavior of (C H -NH ) (CH NH ) Pb I , the archetype 2D HOIP, is systematically investigated by atomic force microscopy (AFM).

An Automated Cell Detection Method for TH-positive Dopaminergic Neurons in a Mouse Model of Parkinson's Disease Using Convolutional Neural Networks.

Quantification of tyrosine hydroxylase (TH)-positive neurons is essential for the preclinical study of Parkinson's disease (PD). However, manual analysis of immunohistochemical (IHC) images is labor-intensive and has less reproducibility due to the lack of objectivity. Therefore, several automated methods of IHC image analysis have been proposed, although they have limitations of low accuracy and difficulties in practical use.

Spatiotemporally controlled drug delivery via photothermally driven conformational change of self-integrated plasmonic hybrid nanogels.

Background: Spatiotemporal regulation is one of the major considerations for developing a controlled and targeted drug delivery system to treat diseases efficiently. Light-responsive plasmonic nanostructures take advantage due to their tunable optical and photothermal properties by changing size, shape, and spatial arrangement.

Results: In this study, self-integrated plasmonic hybrid nanogels (PHNs) are developed for spatiotemporally controllable drug delivery through light-driven conformational change and photothermally-boosted endosomal escape.

A Critical Involvement of Glutamatergic Neurons in the Anterior Insular Cortex for Subdiaphragmatic Vagotomy-induced Analgesia.

Subdiaphragmatic vagotomy (SDV) is known to produce analgesic effect in various pain conditions including not only visceral pain but also somatic pain. We aimed to determine brain mechanisms by which SDV induces analgesic effect in somatic pain condition by using formalin-induced acute inflammatory pain model. We identified brain regions that mediate SDV-induced analgesic effect on acute inflammatory pain by analyzing c-Fos expression in the whole brain.

Covalent Scrambling in Porous Polyarylthioethers through a Stepwise S Ar for Tunable Bandgap and Porosity.

Porous poly(aryl thioether)s offer stability and electronic tunability by robust sulfur-aryl conjugated architecture, but synthetic access is hindered due to limited control over the nucleophilic nature of sulfides and the air sensitivity of aromatic thiols. Here, we report a simple, one-pot, inexpensive, regioselective synthesis of highly porous poly(aryl thioether)s through polycondensation of perfluoroaromatic compounds with sodium sulfide. The unprecedented temperature-dependent para-directing formation of thioether linkages leads to a stepwise transition of the polymer extension into a network, thereby allowing fine control of the porosity and optical band gaps.

Photoactive MOF-Derived Bimetallic Silver and Cobalt Nanocomposite with Enhanced Antibacterial Activity.

Conventional antibiotic-based treatment of bacterial infections remains one of the most difficult challenges in medicine because of the threat of multidrug resistance caused by indiscriminate abuse. To solve these problems, it is essential to develop an effective antibacterial agent that can be used at a small dose while minimizing the occurrence of multiple resistance. Metal-organic frameworks (MOFs), which are hyper-porous hybrid materials containing metal ions linked by organic ligands, have recently attracted attention because of their strong antibacterial activity through metal-ion release, unlike conventional antibiotics.

Tackling prediction uncertainty in machine learning for healthcare.

Predictive machine-learning systems often do not convey the degree of confidence in the correctness of their outputs. To prevent unsafe prediction failures from machine-learning models, the users of the systems should be aware of the general accuracy of the model and understand the degree of confidence in each individual prediction. In this Perspective, we convey the need of prediction-uncertainty metrics in healthcare applications, with a focus on radiology.

Prediction of oxygen requirement in patients with COVID-19 using a pre-trained chest radiograph xAI model: efficient development of auditable risk prediction models via a fine-tuning approach.

Risk prediction requires comprehensive integration of clinical information and concurrent radiological findings. We present an upgraded chest radiograph (CXR) explainable artificial intelligence (xAI) model, which was trained on 241,723 well-annotated CXRs obtained prior to the onset of the COVID-19 pandemic. Mean area under the receiver operating characteristic curve (AUROC) for detection of 20 radiographic features was 0.

MONITORING OF PULMONARY EDEMA USING ULTRASOUND RADIOFREQUENCY SIGNAL.

Objectives: Excessive accumulation of extravascular lung water impairs respiratory gas exchange and results in respiratory distress. Real-time radiofrequency signals of ultrasound can continuously and quantitatively monitor excessive lung water. This study aims to evaluate the availability of continuous real-time quantitative pulmonary edema monitoring using ultrasound radiofrequency signals and compare it with Pa o2 (partial pressure of arterial oxygen)/F io2 (fraction of inspired oxygen) (PF) ratio, conventional lung ultrasound, and the Hounsfield unit of chest computed tomography.

Organizing Reliable Polymer Electrode Lines in Flexible Neural Networks via Coffee Ring-Free Micromolding in Capillaries.

With an increase in the demand for smart wearable systems, artificial synapse arrays for flexible neural networks have received considerable attention. A synaptic device with a two-terminal configuration is promising for complex neural networks because of its ability to scale to a crossbar array architecture. To realize practical crossbar arrays with a high density, it is essential to achieve reliable electrode lines that act as signal terminals.

Systematic Modulation of Thiol Functionalities in Inexpensive Porous Polymers for Effective Mercury Removal.

Through accumulation, mercury contamination in aquatic systems still poses serious health risks despite the strict regulations on drinking water and industrial discharge. One effective strategy against this is adsorptive removal, in which a suitably functionalized porous material is added to water treatment protocols. Thiol (SH) group-grafted structures perform commendably; however, insufficient attention is paid to the cost, scalability, and reusability or how the arrangement of sulfur atoms could affect the Hg binding strength.