Low-biofouling membrane bioreactor: Effects of cis-2-Decenoic acid addition on EPS and biofouling mitigation.

Biofouling is inevitable in the membrane process, particularly in membrane bioreactors (MBR) combined with activated sludge processes. Regulating microbial signaling systems with diffusible signal factors such as cis-2-Decenoic acid (CDA) can control biofilm formation without microbial death or growth inhibition. This study assessed the effectiveness of CDA in controlling biofouling in membrane bioreactors (MBRs), essential for wastewater treatment. By modulating microbial signaling, CDA mitigated biofilm formation without hindering microbial growth. Analysis using Confocal Laser Scanning Microscopy (CLSM) revealed structural alterations in the biofilm, reducing biomass and thickness upon CDA application. Moreover, examination of extracellular polymeric substances (EPS) highlighted a decrease in total EPS, particularly effective polysaccharides. In addition, the possibility of shifting from high molecular weight EPS to low molecular weight EPS was revealed through the change in dispersion activity. The 56% extension of MBR operational lifespan resulting from the reduction in EPS is anticipated to offer potential cost savings and improved performance. Despite these results, further investigation is crucial to validate any potential environmental risks associated with CDA and to comprehend its long-term effects at various conditions.

A Simple Method for Automatic 3D Reconstruction of Coronary Arteries From X-Ray Angiography.

Automatic three-dimensional (3-D) reconstruction of the coronary arteries (CA) from medical imaging modalities is still a challenging task. In this study, we present a deep learning-based method of automatic identification of the two ends of the vessel from X-ray coronary angiography (XCA). We also present a method of using template models of CA in matching the two-dimensional segmented vessels from two different angles of XCA. For the deep learning network, we used a U-net consisting of an encoder (Resnet) and a decoder. The two ends of the vessel were manually labeled to generate training images. The network was trained with 2,342, 1,907, and 1,523 labeled images for the left anterior descending (LAD), left circumflex (LCX), and right coronary artery (RCA), respectively. For template models of CA, ten reconstructed 3-D models were averaged for each artery. The accuracy of correspondence using template models was compared with that of manual matching. The deep learning network pointed the proximal region (20% of the total length) in 97.7, 97.5, and 96.4% of 315, 201, and 167 test images for LAD, LCX, and RCA, respectively. The success rates in pointing the distal region were 94.9, 89.8, and 94.6%, respectively. The average distances between the projected points from the reconstructed 3-D model to the detector and the points on the segmented vessels were not statistically different between the template and manual matchings. The computed FFR was not significantly different between the two matchings either. Deep learning methodology is feasible in identifying the two ends of the vessel in XCA, and the accuracy of using template models is comparable to that of manual correspondence in matching the segmented vessels from two angles.

A Transparent Nanopatterned Chemiresistor: Visible-Light Plasmonic Sensor for Trace-Level NO2 Detection at Room Temperature.

The highly selective detection of trace gases using transparent sensors at room temperature remains challenging. Herein, transparent nanopatterned chemiresistors composed of aligned 1D Au-SnO2 nanofibers, which can detect toxic NO2 gas at room temperature under visible light illumination is reported. Ten straight Au-SnO2 nanofibers are patterned on a glass substrate with transparent electrodes assisted by direct-write, near-field electrospinning, whose extremely low coverage of sensing materials (≈0.3%) lead to the high transparency (≈93%) of the sensor. The sensor exhibits a highly selective, sensitive, and reproducible response to sub-ppm levels of NO2 , and its detection limit is as low as 6 ppb. The unique room-temperature NO2 sensing under visible light emanates from the localized surface plasmonic resonance effect of Au nanoparticles, thereby enabling the design of new transparent oxide-based gas sensors without external heaters or light sources. The patterning of nanofibers with extremely low coverage provides a general strategy to design diverse compositions of gas sensors, which can facilitate the development of a wide range of new applications in transparent electronics and smart windows wirelessly connected to the Internet of Things.

Population Age Structure and Greenhouse Gas Emissions from Road Transportation: A Panel Cointegration Analysis of 21 OECD Countries.

Using panel data from 21 Organization for Economic Cooperation and Development (OECD) countries collected between 2000 and 2016, this study analyzes the effect of age structure on greenhouse gas (GHG) emissions from road transportation. Previous studies have failed to reflect the driver's behavior patterns, especially by age group. We apply the Fully-Modified Ordinary Least Squares (FMOLS) method, including the age structure effect by reorganizing 17 age groups into a polynomial structure. The age structure exhibits an asymmetric inverted U-shaped effect on GHG emissions. Initially, people emit more GHGs as they age, and reach peak emissions in their late 20s, after which emissions fall until around the age of 70, when GHG emissions remain constant because of minimum mobility demand. Factors, such as higher income, increased vehicle ownership, and raised transport volumes increase emission rates. On the other hand, fuel transition and increased fuel price, population density, urbanization rate, and fuel economy reduce GHG emissions. Furthermore, we perform a projection of GHG emissions until 2050, and conclude that the effect of age structure is limited because of the minimum mobility demand of the elderly. We conclude that various policy measures, such as increased fuel economy and urbanization, must be considered in order to achieve sustainable transport.

Do Aging and Low Fertility Reduce Carbon Emissions in Korea? Evidence from IPAT Augmented EKC Analysis.

The purpose of this article is to empirically find the Environmental Kuznets Curve (EKC) relationship between income and carbon dioxide (CO2) emissions and to analyze the influence of population aging on such emissions. We utilize Korean regional panel data of 16 provinces during the period from 1998 to 2016. To account for the nonstationary time series in the panel, we employ a fully modified ordinary least squares (FMOLS) and estimate long-run elasticity. From the empirical results, we can find the nonlinear relationship between income and CO2 emissions. Additionally, we verify the fact that population aging reduces CO2 emissions. A 1% increase in the proportion of the elderly results in a 0.4% decrease in CO2 emissions. On the other hand, the younger population increases CO2 emissions. These results were in line with those of additional analysis on residential and transportation CO2 emissions, for the robustness check.

In situ procedure for high-efficiency computational modeling of atrial fibrillation reflecting personal anatomy, fiber orientation, fibrosis, and electrophysiology.

We previously reported the feasibility and efficacy of a simulation-guided clinical catheter ablation of atrial fibrillation (AF) in an in-silico AF model. We developed a highly efficient realistic AF model reflecting the patient endocardial voltage and local conduction and tested its clinical feasibility. We acquired > 500 endocardial bipolar electrograms during right atrial pacing at the beginning of the AF ablation procedures. Based on the clinical bipolar electrograms, we generated simulated voltage maps by applying fibrosis and local activation maps adjusted for the fiber orientation. The software's accuracy (CUVIA2.5) was retrospectively tested in 17 patients and feasibility prospectively in 10 during clinical AF ablation. Results: We found excellent correlations between the clinical and simulated voltage maps (R = 0.933, p < 0.001) and clinical and virtual local conduction (R = 0.958, p < 0.001). The proportion of virtual local fibrosis was 15.4, 22.2, and 36.9% in the paroxysmal AF, persistent AF, and post-pulmonary vein isolation (PVI) states, respectively. The reconstructed virtual bipolar electrogram exhibited a relatively good similarities of morphology to the local clinical bipolar electrogram (R = 0.60 ± 0.08, p < 0.001). Feasibility testing revealed an in situ procedural computing time from the clinical data acquisition to wave-dynamics analyses of 48.2 ± 4.9 min. All virtual analyses were successfully achieved during clinical PVI procedures. We developed a highly efficient, realistic, in situ procedural simulation model reflective of individual anatomy, fiber orientation, fibrosis, and electrophysiology that can be applied during AF ablation.

Humidity-Independent Gas Sensors Using Pr-Doped In2O3 Macroporous Spheres: Role of Cyclic Pr3+/Pr4+ Redox Reactions in Suppression of Water-Poisoning Effect.

Pure and 3-12 at. % Pr-doped In2O3 macroporous spheres were fabricated by ultrasonic spray pyrolysis and their acetone-sensing characteristics under dry and humid conditions were investigated to design humidity-independent gas sensors. The 12 at. % Pr-doped In2O3 sensor exhibited approximately the same acetone responses and sensor resistances at 450 °C regardless of the humidity variation, whereas the pure In2O3 exhibited significant deterioration in gas-sensing characteristics upon the change in the atmosphere, from dry to humid (relative humidity: 80%). Moreover, the 12 at. % Pr-doped In2O3 sensor exhibited a high response to acetone with negligible cross responses to interfering gases (NH3, CO, benzene, toluene, NO2, and H2) under the highly humid atmosphere. The mechanism for the humidity-immune gas-sensing characteristics was investigated by X-ray photoelectron and diffuse reflectance infrared Fourier transform spectroscopies together with the phenomenological gas-sensing results and discussed in relation with Pr3+/Pr4+ redox pairs, regenerative oxygen adsorption, and scavenging of hydroxyl groups.

Monitoring biofouling based on aerobic respiration in reverse osmosis system.

A monitoring method of biofouling in reverse osmosis (RO) system was proposed based on the fluorescent signal of resorufin, which is reduced by nicotinamide adenine dinucleotide released from viable cells during aerobic respiration. The fluorescent signal of resorufin reduced by planktonic cells and microorganisms of biofilm showed linearity, indicating its feasibility to monitor biofouling in a RO system. For the application of the method to the lab-scale RO system, the injection concentration of resazurin and the injection flow rate were optimized. Biofilm on RO membranes continuously operated in a lab-scale RO system was estimated by resorufin fluorescence under optimized detection condition. As a result, resorufin fluorescence on RO membrane showed a significant increase in which the permeability of RO system decreased by 30.48%. Moreover, it represented the development of biofilm as much as conventional biofilm parameters such as adenosine triphosphate, extracellular polymeric substances, and biofilm thickness. The proposed method could be used as a sensitive and low-cost technology to monitor biofouling without autopsy of membranes.

Pro-Arrhythmogenic Effects of Heterogeneous Tissue Curvature　- A Suggestion for Role of Left Atrial Appendage in Atrial Fibrillation.

BACKGROUND: The arrhythmogenic role of complex atrial morphology has not yet been clearly elucidated. We hypothesized that bumpy tissue geometry can induce action potential duration (APD) dispersion and wavebreak in atrial fibrillation (AF). Methods and Results: We simulated a 2D-bumpy atrial model by varying the degree of bumpiness, and 3D-left atrial (LA) models integrated by LA computed tomographic (CT) images taken from 14 patients with persistent AF. We also analyzed wave-dynamic parameters with bipolar electrograms during AF and compared them with LA-CT geometry in 30 patients with persistent AF. In the 2D-bumpy model, APD dispersion increased (P<0.001) and wavebreak occurred spontaneously when the surface bumpiness was greater, showing phase transition-like behavior (P<0.001). The bumpiness gradient 2D-model showed that spiral wave drifted in the direction of higher bumpiness, and phase singularity (PS) points were mostly located in areas with higher bumpiness. In the 3D-LA model, PS density was higher in the LA appendage (LAA) compared with other parts of the LA (P<0.05). In 30 persistent-AF patients, the surface bumpiness of LAA was 5.8-fold that of other LA parts (P<0.001), and exceeded critical bumpiness to induce wavebreak. Wave dynamics complexity parameters were consistently dominant in the LAA (P<0.001). CONCLUSIONS: Bumpy tissue geometry promoted APD dispersion, wavebreak, and spiral wave drift in in-silico human atrial tissue, and corresponded to clinical electroanatomical maps.

Cognitive Load Changes during Music Listening and its Implication in Earcon Design in Public Environments: An fNIRS Study.

A key for earcon design in public environments is to incorporate an individual's perceived level of cognitive load for better communication. This study aimed to examine the cognitive load changes required to perform a melodic contour identification task (CIT). While healthy college students (N = 16) were presented with five CITs, behavioral (reaction time and accuracy) and cerebral hemodynamic responses were measured using functional near-infrared spectroscopy. Our behavioral findings showed a gradual increase in cognitive load from CIT1 to CIT3 followed by an abrupt increase between CIT4 (i.e., listening to two concurrent melodic contours in an alternating manner and identifying the direction of the target contour, p < 0.001) and CIT5 (i.e., listening to two concurrent melodic contours in a divided manner and identifying the directions of both contours, p < 0.001). Cerebral hemodynamic responses showed a congruent trend with behavioral findings. Specific to the frontopolar area (Brodmann's area 10), oxygenated hemoglobin increased significantly between CIT4 and CIT5 (p < 0.05) while the level of deoxygenated hemoglobin decreased. Altogether, the findings indicate that the cognitive threshold for young adults (CIT5) and appropriate tuning of the relationship between timbre and pitch contour can lower the perceived cognitive load and, thus, can be an effective design strategy for earcon in a public environment.

Gas Selectivity Control in Co3O4 Sensor via Concurrent Tuning of Gas Reforming and Gas Filtering using Nanoscale Hetero-Overlayer of Catalytic Oxides.

Co3O4 sensors with a nanoscale TiO2 or SnO2 catalytic overlayer were prepared by screen-printing of Co3O4 yolk-shell spheres and subsequent e-beam evaporation of TiO2 and SnO2. The Co3O4 sensors with 5 nm thick TiO2 and SnO2 overlayers showed high responses (resistance ratios) to 5 ppm xylene (14.5 and 28.8) and toluene (11.7 and 16.2) at 250 °C with negligible responses to interference gases such as ethanol, HCHO, CO, and benzene. In contrast, the pure Co3O4 sensor did not show remarkable selectivity toward any specific gas. The response and selectivity to methylbenzenes and ethanol could be systematically controlled by selecting the catalytic overlayer material, varying the overlayer thickness, and tuning the sensing temperature. The significant enhancement of the selectivity for xylene and toluene was attributed to the reforming of less reactive methylbenzenes into more reactive and smaller species and oxidative filtering of other interference gases, including ubiquitous ethanol. The concurrent control of the gas reforming and oxidative filtering processes using a nanoscale overlayer of catalytic oxides provides a new, general, and powerful tool for designing highly selective and sensitive oxide semiconductor gas sensors.

Co3O4-SnO2 Hollow Heteronanostructures: Facile Control of Gas Selectivity by Compositional Tuning of Sensing Materials via Galvanic Replacement.

Co3O4 hollow spheres prepared by ultrasonic spray pyrolysis were converted into Co3O4-SnO2 core-shell hollow spheres by galvanic replacement with subsequent calcination at 450 °C for 2 h for gas sensor applications. Gas selectivity of the obtained spheres can be controlled by varying the amount of SnO2 shells (14.6, 24.3, and 43.3 at. %) and sensor temperatures. Co3O4 sensors possess an ability to selectively detect ethanol at 275 °C. When the amount of SnO2 shells was increased to 14.6 and 24.3 at. %, highly selective detection of xylene and methylbenzenes (xylene + toluene) was achieved at 275 and 300 °C, respectively. Good selectivity of Co3O4 hollow spheres to ethanol can be explained by a catalytic activity of Co3O4; whereas high selectivity of Co3O4-SnO2 core-shell hollow spheres to methylbenzenes is attributed to a synergistic effect of catalytic SnO2 and Co3O4 and promotion of gas sensing reactions by a pore-size control of microreactors.