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In modern society, individuals spend an increasing amount of time indoors, emphasizing the importance of understanding the health impacts of indoor environments. This study focused on measuring indoor air quality to identify vulnerable populations and observe the effects of residential environment improvements on air quality. Targeting low-income families and elderly households, known for their heightened vulnerability to environmental health risks, the study involved direct visits to 2328 low-income households across 16 cities and provinces in South Korea from 2021 to 2022. Indoor air quality parameters, including PM2.5, PM10, total volatile organic compounds (TVOC), formaldehyde (HCHO), and airborne mold, were measured. Among these households, 300 with critically compromised living conditions received support for wallpaper and paneling replacement. Comparative measurements before and after the renovations revealed that single-person households had higher levels of PM2.5 and TVOC compared with households with four or more members. Additionally, households with elevated concentrations of airborne mold also exhibited higher levels of PM2.5 and PM10. Importantly, households that received environmental improvements showed a significant reduction in airborne mold concentration by approximately 50% or more. This study underscores the importance of indoor environmental health and provides valuable evidence supporting policies focused on health promotion and residential welfare improvements for vulnerable populations. The research is distinguished by its comprehensive nature, involving direct measurements from nearly 2000 households nationwide, rather than relying solely on secondary data.

Pyrimidine is a privileged scaffold in many synthetic compounds exhibiting diverse pharmacological activities, and is used for therapeutic applications in a broad spectrum of human diseases. In this study, we prepared a small set of pyrimidine libraries based on the structure of two hit compounds that were identified through the screening of an in-house library in order to identify an inhibitor of anoctamin 1 (ANO1). ANO1 is amplified in various types of human malignant tumors, such as head and neck, parathyroid, and gastrointestinal stromal tumors, as well as in breast, lung, and prostate cancers. After initial screening and further structure optimization, we identified Aa3 as a dose-dependent ANO1 blocker. This compound exhibited more potent anti-cancer activity in the NCI-H460 cell line, expressing high levels of ANO1 compared with that in A549 cells that express low levels of ANO1. Our results open a new direction for the development of small-molecule ANO1 blockers composed of a pyrimidine scaffold and a nitrogen-containing heterocyclic moiety, with drug-like properties.

The choice of materials that constitute electrodes and the way they are interconnected, i.e., the microstructure, influences the performance of lithium-ion batteries. For batteries with high energy and power densities, the microstructure of the electrodes must be controlled during their manufacturing process. Moreover, understanding the microstructure helps in designing a high-performance, yet low-cost battery. In this study, we propose a systematic algorithm workflow for the images of the microstructure of anodes obtained from a focused ion beam scanning electron microscope (FIB-SEM). Here, we discuss the typical issues that arise in the raw FIB-SEM images and the corresponding preprocessing methods that resolve them. Next, we propose a Fourier transform-based filter that effectively reduces curtain artifacts. Also, we propose a simple, yet an effective, global-thresholding method to identify active materials and pores in the microstructure. Finally, we reconstruct the three-dimensional structures by concatenating the segmented images. The whole algorithm workflow used in this study is not fully automated and requires user interactions such as choosing the values of parameters and removing shine-through artifacts manually. However, it should be emphasized that the proposed global-thresholding method is deterministic and stable, which results in high segmentation performance for all sectioning images.

A simple thermal annealing was performed to prepare tungsten oxide nanorods directly from tungsten (W) film. The W film was deposited on Si(100) substrate by chemical vapor deposition (CVD) at 450 °C using W(CO)6. A high density of tungsten oxide nanorods was produced by heating of the W film at 600–700 °C. The morphology, structure, composition, and chemical binding states of the prepared nanorods were characterized by scanning electron microscopy (SEM), x-ray diffraction (XRD), x-ray photoelectron spectroscopy (XPS), and transmission electron microscopy (TEM) analysis. XRD and TEM results showed that the grown nanorods were single-crystalline W18O49. According to XPS analysis, the W18O49 nanorods contained ∼55.69% W6+, ∼32.28% W5+, and ∼12.03% W4+. The growth mechanism based on thermodynamics is discussed for the growth of tungsten oxide nanorods from W film.

Nanoparticles, which are defined as objects with characteristic lengths in the 10–9 – 10–7 m (nanoscale) size range, are used with increasing frequency in a wide of applications, leading to increases in nanomaterial interactions with biological and environmental systems. There is therefore considerable interest in studying the influence nanomaterials can have when inside the human body or dispersed in the ambient environment. However, nanoparticles persist as homo aggregates or heterogeneous mixtures with organic matters, such as proteins, in biological and environmental systems. A large and growing body of research confirm that nanomaterial morphology as well as the degree of aggregation between nanomaterials influences nanomaterial interactions with their surroundings. Specifically, the structures/morphologies of nanoparticles determine their overall surface areas and corresponding surface reactivity (e.g. their catalytic activity). Nanoparticle transport properties (e.g. diffusion coefficient and extent of cellular uptake) are also determined by both their structures and surface properties. Unfortunately, techniques to characterize nanomaterial size and shape quantitatively, when nanomaterials have complex geometries or persist as aggregates, are lacking. Hydrodynamic sizes of nanoparticles and their aggregates can be inferred by dynamic light scattering (DLS) or nanoparticle tracking analysis (NTA). However, since these techniques are relied on the scattering light intensity properties, sizes of polydisperse sub 30 nm particles cannot be effectively measured in those techniques. For structure inference of aggregated nanomaterials, microscopy images have been used for qualitative visual analysis, but the quantitative morphology analysis technique is yet to be developed. Five studies in this dissertation are hence aimed to develop new techniques to provide improved morphology characterization of aggregated nanomaterials in various biological and environmental colloidal systems. Aggregation mechanism and behavior of nanoparticles in surrounding were examined as a function of their quantified aggregate morphologies. The first three studies (Chapters 2, 3, and 4) introduced a new gas-phase particle size measurement system, a liquid nebulization-ion mobility spectrometry (LN-IMS) technique, to characterize nanomaterials (down to 5 nm in characteristic size) and nanoparticle-protein conjugates. In other two studies (Chapters 5 and 6), three dimensional structures of homo-aggregates were quantified with the fractal aggregate model, and resulted fractal structures of aggregates were correlated to their transport properties in surroundings.

The aim of the current study is to investigate how participants manage topics in online one-to-one English conversation instruction conducted through synchronous voice-based computer-mediated communication. To date, much work has been done on text-based media in the field of CMC. Recently, researchers have started becoming interested in examining spoken interaction. However, no research has yet been done on topic management in online one-to-one English conversation classes conducted through synchronous voice-based CMC. This study is the first to conduct a micro-analysis of non-verbal elements, such as pitch, volume, intonation, laughter, pauses, inhalations and exhalations, as well as verbal elements, to investigate what sort of interactions participants in online one-to-one conversation classes develop to manage topics during their classes. Thus, this study is expected to play a pioneering role in promoting further research into such classes. In order to illuminate how the participants in the online English classes managed topics during their conversations, four research questions were developed: first, how are topics initiated? second, how are topics maintained? third, how are topics terminated and changed? and fourth, how does trouble and repair in topic management occur? The research findings were obtained through the analysis of the spoken data from the perspective of Conversation Analysis (CA) so that paralinguistic forms as well as the interactional and sequential organisation of talk the participants produce could be analysed in order to answer the research questions. The findings obtained from the analysis revealed various actions associated with topic management that were performed during the online conversation classes. It was found that the participants initiate or proffer topics using questions and statements including topical items, that they maintain topics by employing two fundamental strategies: giving a preferred response or giving a response showing interest, and that they change topics mainly by engaging in collaborative topic transitions forming a topic boundary. It was also found that trouble and repair in topic management occurs: that is, inadequate lexical knowledge, rejection of a proffered topic, and technical problems and other interference affect the sequence of topic management. The findings of the current study will therefore contribute to current research into social interactions that occur during the management of topics in online English one-to-one conversation classes, since this is a subject that has not previously been studied in the fields of either CMC or CA. Accordingly, this study is also expected to fill a gap in these areas of research.

Nano-structured silicon anodes are attractive alternatives to graphite in Li-ion batteries. Despite recent remarkable progresses in numerous Si-C composites, the commercialisation with significance is still limited. One of the most critical issues remained to understand is fundamentals on Li-Si Coulombic efficiency, namely, CE. Particularly, it is key to quantitatively and qualitatively resolve CE alterations and evolutions by the various Li-Si structural changes over longer cycling. However, such work is surprisingly scarce. Here, we provide new findings that iterating the hysteretic amorphous-crystalline Li-Si phase transformations accumulatively governs CE evolutions, the manner of which is numerically distinguished from incremental amorphous Li-Si volume changes. The iterations, usually featured as capacity degradation factors, can form the most efficient CE profiles over hundreds of cycles, i.e. minimising accumulative irreversible Li consumption, among the given Li-Si reaction sequences. Combined with atomistic probing methodologies, we show that the iteration drastically alters electrochemical and structural characteristics, which is synchronised with the CE behaviours.

With a recent increase in interest in metal-gas batteries, the lithium-carbon dioxide cell has attracted considerable attention because of its extraordinary carbon dioxide-capture ability during the discharge process and its potential application as a power source for Mars exploration. However, owing to the stable lithium carbonate discharge product, the cell enables operation only at low current densities, which significantly limits the application of lithium-carbon dioxide batteries and effective carbon dioxide-capture cells. Here, we investigate a high-performance lithium-carbon dioxide cell using a quinary molten salt electrolyte and ruthenium nanoparticles on the carbon cathode. The nitrate-based molten salt electrolyte allows us to observe the enhanced carbon dioxide-capture rate and the reduced discharge-charge over-potential gap with that of conventional lithium-carbon dioxide cells. Furthermore, owing to the ruthernium catalyst, the cell sustains its performance over more than 300 cycles at a current density of 10.0 A g −1 and exhibits a peak power density of 33.4 mW cm −2 . Lithium-carbon dioxide cells are challenging due to the sluggish electron transfer in the Lithium carbonate in aprotic electrolyte. Here, the authors report synergistic effect of molten salt electrolyte and Ruthenium catalyst to enhance the electrochemical performance of Lithium-carbon dioxide batteries

Background Diabetic nephropathy (DN) is associated with high risk of cardiovascular disease and mortality. Exosomal microRNAs (miRNAs) regulate gene expression in a variety of tissues and play important roles in the pathology of various diseases. We hypothesized that the exosomal miRNA profile would differ between DN patients and patients without nephropathy. Methods We prospectively enrolled 74 participants, including healthy volunteers (HVs), diabetic patients without nephropathy, and those with DN. The serum exosomal miRNA profiles of participants were examined using RNA sequencing. Results The expression levels of 107 miRNAs differed between HVs and patients without DN, whereas the expression levels of 95 miRNAs differed between HVs and patients with DN. Among these miRNAs, we found 7 miRNAs (miR-1246, miR-642a-3p, let-7c-5p, miR-1255b-5p, let-7i-3p, miR-5010-5p, miR-150-3p) that were uniquely up-regulated in DN patients compared to HVs, and miR-4449 that was highly expressed in DN patients compared to patients without DN. A pathway analysis revealed that these eight miRNAs are likely involved in MAPK signaling, integrin function in angiogenesis, and regulation of the AP-1 transcription factor. Moreover, they were all significantly correlated with the degree of albuminuria. Conclusions Patients with DN have a different serum exosomal miRNA profile compared to HVs. These miRNAs may be promising candidates for the diagnosis and treatment of DN and cardiovascular disease.

A spiral‐artificial basilar membrane (S‐ABM) sensor is reported that mimics the basilar membrane (BM) of the human cochlea and can detect sound by separating it into 24 sensing channels based on the frequency band. For this, an analytical function is proposed to design the width of the BM so that the frequency bands are linearly located along the length of the BM. To fabricate the S‐ABM sensor, a spiral‐shaped polyimide film is used as a vibrating membrane, with maximum displacement at locations corresponding to specific frequency bands of sound, and attach piezoelectric sensor modules made of poly(vinylidene fluoride‐trifluoroethylene) film on top of the polyimide film to measure the vibration amplitude at each channel location. As the result, the S‐ABM sensor implements a characteristic frequency band of 96‐12,821 Hz and 24‐independent critical bands. Using real‐time signals from discriminate channels, it is demonstrated that the sensor can rapidly identify the operational noises from equipment processes as well as vehicle sounds from environmental noises on the road. The sensor can be used in a variety of applications, including speech recognition, dangerous situation recognition, hearing aids, and cochlear implants, and more. The spiral‐artificial basilar membrane (S‐ABM) sensor is a biomimetic acoustic sensor consisting of an artificial basilar membrane (ABM) that discriminates sound into frequency bands, 24 independent critical bands, and piezoelectric sensor modules that generates an electrical signal by the vibration of the S‐ABM. An early detection system is developed that can detect and distinguish potential hazards that may occur in industrial processes and driving situations through the sensor.