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BackgroundChronic obstructive pulmonary disease (COPD) is one of the major morbidities in public health, and the use of mHealth technology for rehabilitation of patients with COPD can help increase physical activity and ameliorate respiratory symptoms. ObjectiveThis study aimed to develop a comprehensive rehabilitation management platform to improve physical activity and quality of life in patients with COPD. MethodsThe study comprised the following 2 stages: (1) a pilot stage in which a prototype app was developed; and (2) a fully-fledged platform development stage in which 2 apps and 1 COPD patient monitoring website were developed. We conducted a randomized clinical trial to investigate the efficacy of the apps developed in the second stage of the study. In addition, two 12-week exercise regimens (fixed and fixed-interactive) were tested for the trial. The clinical parameters of the respiratory function and patient global assessment (PGA) of the app were obtained and analyzed. Notably, Android was the chosen operating system for apps. ResultsWe developed 2 COPD rehabilitation apps and 1 patient monitoring website. For the clinical trial, 85 patients were randomized into the following 3 groups: 57 were allocated to the 2 intervention groups and 28 to the control group. After 6 weeks, the COPD assessment test scores were significantly reduced in the fixed group (P=.01), and signs of improvement were witnessed in the fixed-interactive group. In addition, the PGA score was moderate or high in all aspects of the user experience of the apps in both intervention groups. ConclusionsA well-designed mobile rehabilitation app for monitoring and managing patients with COPD can supplement or replace traditional center-based rehabilitation programs and achieve improved patient health outcomes. Trial RegistrationClinicalTrials.gov NCT03432117; https://clinicaltrials.gov/ct2/show/NCT03432117 (Archived by WebCite at http://www.webcitation.org/71Yp0P64a)

This study presents findings indicating that the ferroelectric tunnel junction (FTJ) or resistive random-access memory (RRAM) in one cell can be intentionally selected depending on the application. The HfAlO film annealed at 700 °C shows stable FTJ characteristics and can be converted into RRAM by forming a conductive filament inside the same cell, that is, the process of intentionally forming a conductive filament is the result of defect generation and redistribution, and applying compliance current prior to a hard breakdown event of the dielectric film enables subsequent RRAM operation. The converted RRAM demonstrated good memory performance. Through current–voltage fitting, it was confirmed that the two resistance states of the FTJ and RRAM had different transport mechanisms. In the RRAM, the 1/f noise power of the high-resistance state (HRS) was about ten times higher than that of the low-resistance state (LRS). This is because the noise components increase due to the additional current paths in the HRS. The 1/f noise power according to resistance states in the FTJ was exactly the opposite result from the case of the RRAM. This is because the noise component due to the Poole–Frenkel emission is added to the noise component due to the tunneling current in the LRS. In addition, we confirmed the potentiation and depression characteristics of the two devices and further evaluated the accuracy of pattern recognition through a simulation by considering a dataset from the Modified National Institute of Standards and Technology. [ABSTRACT FROM AUTHOR]

This study presents a preliminary exploration of thermally oxidized TaOx-based memristors and their potential as artificial synapses. Unlike the 10-min annealed devices, which display instability due to current overshoots, the 5-min annealed device exhibits stable resistive switching, retention, and endurance characteristics. Moreover, our memristor showcases synaptic behaviors encompassing potentiation, depression, spike-timing-dependent plasticity, and excitatory postsynaptic currents. This synaptic emulation holds tremendous promise for applications in neuromorphic computing, offering the opportunity to replicate the adaptive learning principles observed in biological synapses. In addition, we evaluate the device's suitability for pattern recognition within a neural network using the modified National Institute of Standards and Technology dataset. Our assessment reveals that the Pt/TaOx/Ta memristor with an oxidized insulator achieves outstanding potential manifested by an accuracy of 93.25% for the identical pulse scheme and an impressive accuracy of 95.42% for the incremental pulse scheme. [ABSTRACT FROM AUTHOR]

Predicting outcomes in pulmonary tuberculosis is challenging despite effective treatments. This study aimed to identify factors influencing treatment success and culture conversion, focusing on artificial intelligence (AI)-based chest X-ray analysis and Xpert MTB/RIF assay cycle threshold (Ct) values. In this retrospective study across six South Korean referral centers (January 1 to December 31, 2019), we included adults with rifampicin-susceptible pulmonary tuberculosis confirmed by Xpert assay from sputum samples. We analyzed patient characteristics, AI-based tuberculosis extent scores from chest X-rays, and Xpert Ct values. Of 230 patients, 206 (89.6%) achieved treatment success. The median age was 61 years, predominantly male (76.1%). AI-based radiographic tuberculosis extent scores (median 7.5) significantly correlated with treatment success (odds ratio [OR] 0.938, 95% confidence interval [CI] 0.895–0.983) and culture conversion at 8 weeks (liquid medium: OR 0.911, 95% CI 0.853–0.973; solid medium: OR 0.910, 95% CI 0.850–0.973). Sputum smear positivity was 49.6%, with a median Ct of 26.2. However, Ct values did not significantly correlate with major treatment outcomes. AI-based radiographic scoring at diagnosis is a significant predictor of treatment success and culture conversion in pulmonary tuberculosis, underscoring its potential in personalized patient management. [ABSTRACT FROM AUTHOR]

Are highly specialized hikers really more likely to behave in a pro-environmental manner? By discussing a negative linkage between recreation specialization and pro-environmental behavior, this study tackles a narrowly optimistic view that specialized hikers are always likely to behave pro-environmentally. We examined survey data from South Korean hikers and found that while recreation specialization does not significantly affect attitudes, it negatively affects perceived behavioral control. Further, all types of pro-environmental behavior were significantly impacted by their attitude, but only one pro-environmental behavior (i.e., following designated trails) was strongly impacted by perceived behavioral control. By synthesizing our findings with current literature, we suggest comprehensively evaluating all three motivational factors—self-interest, prosocial, and affective motivations—to predict pro-environmental behavior. [ABSTRACT FROM AUTHOR]

The use of Hf0.5Zr0.5O2 (HZO) films within hafnia‐based ferroelectric tunnel junctions (FTJ) presents a promising avenue for next‐generation non‐volatile memory devices. HZO exhibits excellent ferroelectric properties, ultra‐thinness, low power consumption, nondestructive readout, and compatibility with silicon devices. In this study, Mo/HZO/n+ Si devices are investigated, incorporating a 1 nm HfO2 dielectric layer at the top and bottom of the HZO ferroelectric layer. Comparing the FTJ device configurations, it is observed that the metal‐ferroelectric‐dielectric‐semiconductor (MFIS) outperforms the metal‐dielectric‐ferroelectric‐semiconductor (MIFS) in terms of ferroelectricity, displaying a high 2Pr value of ≈69 µC cm−2. Additionally, MFIS exhibits lower leakage current, higher tunneling electro‐resistance ratio, and a thin dead layer during short pulse switching, as confirmed through DC double sweeping of I−V characteristics. The modified half‐bias scheme demonstrates a maximum array size of 191 for MFIS, showcasing its superior performance over MIFS. Synaptic characteristics, including potentiation, depression, paired‐pulse facilitation, spike‐rate‐dependent plasticity, and excitatory postsynaptic current, are measured using MFIS, highlighting its outstanding ferroelectric properties. As a physical reservoir, the FTJ device implements 16 states of 4 bits in reservoir computing. Finally, pattern recognition using a deep learning neural network achieves high accuracy with using the Modified National Institute of Standards and Technology dataset. [ABSTRACT FROM AUTHOR]

Background and Objective: When multiple complex air pollutants are combined in real‐world settings, the reliability of estimating the effect of a single pollutant is questionable. This study aimed to investigate the combined effects of changes in air pollutants on small airway dysfunction (SAD). Methods: We analysed Korea National Health and Nutrition Examination Survey (KNHANES) V–VIII database from 2010 to 2018 to elucidate the associations between annual changes in air pollutants over a previous 5‐year period and small airway function. We estimated the annual concentrations of five air pollutants: NO2, O3, PM2.5, SO2 and CO. Forced expiratory flow between 25% and 75% of vital capacity (FEF25%–75%) <65% was defined as SAD. Using the quantile generalized‐Computation (g‐Computation) model, the combined effect of the annual changes in different air pollutants was estimated. Results: A total of 29,115 individuals were included. We found significant associations between SAD and the quartiles of annual changes in NO2 (OR = 1.10, 95% CI = 1.08–1.12), O3 (OR = 1.03, 95% CI = 1.00–1.05), PM2.5 (OR = 1.03, 95% CI = 1.00–1.05), SO2 (OR = 1.04, 95% CI = 1.02–1.08) and CO (OR = 1.16, 95% CI = 1.12–1.19). The combined effect of the air pollutant changes was significantly associated with SAD independent of smoking (OR = 1.31, 95% CI = 1.26–1.35, p‐value <0.001), and this trend was consistently observed across the entire study population and various subgroup populations. As the estimated risk of SAD, determined by individual‐specific combined effect models, increased and the log odds for SAD increased linearly. Conclusion: The combined effect of annual changes in multiple air pollutant concentrations were associated with an increased risk of SAD. [ABSTRACT FROM AUTHOR]

This study implements a highly uniform 3D vertically stack resistive random‐access memory (VRRAM) with a four‐layer contact hole structure. The fabrication process of a four‐layer VRRAM is demonstrated, and its physical and electrical properties are thoroughly examined. X‐ray photoelectron spectroscopy and transmission electron microscopy are employed to analyze the chemical distribution and physical structure of the VRRAM device. Multilevel capability, reliable endurance (>104 cycles), and retention (104 s) are successfully obtained. Synaptic memory plasticity, such as spike time‐dependent plasticity, spike rate‐dependent plasticity, excitatory post‐synaptic current, paired‐pulse facilitation, and long‐term potentiation and depression is presented. Finally, the vector‐matrix multiplication (VMM) operation is conducted on a 4 × 12 VRRAM array, according to the low resistance state ratio. It is ascertained that the accuracy drop, which can occur due to VMM error, can be limited to a decrease of less than 0.44% point. Utilizing the high‐density, multilevel, and biological characteristics of VRRAM, it is possible to implement high‐performance neuromorphic systems that require densely integrated synaptic devices. [ABSTRACT FROM AUTHOR]

Background: Comorbidities of chronic obstructive pulmonary disease (COPD) influence clinical characteristics and prognosis. Objectives: This study compared the clinical characteristics and exacerbation rate of COPD according to the presence of depression or anxiety. Design: This study used data from The Korea COPD Subgroup Study (KOCOSS) cohort, a nationwide prospective cohort from 54 medical centers, between April 2012 and 2019. Methods: Depression and anxiety were diagnosed with the Beck Depression Inventory and Beck Anxiety Inventory. Negative binomial regression analysis was performed to analyze the frequency of exacerbations in depressed patients and anxiety. Differences in lung function trajectory according to presence of depression/anxiety were analyzed using a linear mixed model. Results: In all, 2147 patients were enrolled. Depressed patients or anxiety had lower lung function, higher modified Medical Research Council (mMRC) grade, St. George Respiratory Questionnaire (SGRQ) score, and COPD assessment test score, and higher rates of exacerbation in the past year than those without depression/anxiety. Depressed patients had a higher frequency of moderate to severe exacerbations [Incidence Rate Ratio (IRR): 1.57, CI: 1.17–2.11, p = 0.002] and those with anxiety had higher frequencies of moderate to severe (IRR: 1.52, CI: 1.03–2.27, p = 0.038) and severe exacerbations (IRR: 2.13, CI: 1.09–4.15, p = 0.025) during 1-year follow-up compared to those without these comorbidities. The differences in the change in annual forced expiratory volume in 1 seconds (FEV1) over 3 years according to the presence of depression or anxiety were not statistically significant. Conclusion: Depressed and anxious patients showed increased respiratory symptoms and exacerbation rate as well as reduced health-related quality of life, whereas there were no significant differences in changes in lung function between groups with and without depression/anxiety. [ABSTRACT FROM AUTHOR]