Prediction of the marine spreading of low sulfur fuel oil using the long short-term memory model trained with three-phase numerical simulations.

In this study, we focus on the development and validation of a deep learning (long short-term memory, LSTM)-based algorithm to predict the accidental spreading of LSFO (low sulfur fuel oil) on the water surface. The data for the training was obtained by numerical simulations of artificial geometries with different configurations of islands and shorelines and wind speeds (2.0-8.0 m/s). For simulating the spread of oils in O(102) km scales, the volume of fluid and discrete phase models were adopted, and the kinematic variables of particle location, particle velocity, and water velocity were collected as input features for LSTM model. The predicted spreading pattern of LSFO matched well with the simulation (less than 10 % in terms of the mean absolute error for the untrained data). Finally, we applied the model to the Wakashio LSFO spill accident, considering actual geometry and weather information, which confirmed the practical feasibility of the present model.

Toward the eco-friendly cosmetic cleansing assisted by the micro-bubbly jet.

While numerous types of chemical cosmetic cleansers have been presented, those with sensitive skin may still experience some irritation while using them. Moreover, the environmental issue of chemical agents has been documented repeatedly. To address these, we suggest the potential application of a micro-sized bubble-laden water jet to cleanse the cosmetics without (or less) using chemical detergents. We devised a venturi-type nozzle with a mesh and air holes capable of generating massive fine bubbles. By testing with the foundation and lip tint (known to be highly adhesive) coated on the synthetic leather and artificial skin surfaces, we measured that the cleansing performance of the bubbly jet is much better (even without the chemical agent) than the single-phase liquid jet. As a mechanism for enhanced removal, it is understood that the greater kinetic energy of the jet due to the acceleration of the effective liquid-air mixture flow and the direct bubble-cosmetic collisions play essential roles. We believe that the present results will spur the development of environment-friendly cleaning methods.

Utilization of 2D materials in aqueous zinc ion batteries for safe energy storage devices.

Aqueous rechargeable battery has been an intense topic of research recently due to the significant safety issues of conventional Li-ion batteries (LIBs). Amongst the various candidates of aqueous batteries, aqueous zinc ion batteries (AZIBs) hold great promise as a next generation safe energy storage device due to its low cost, abundance in nature, low toxicity, environmental friendliness, low redox potential, and high theoretical capacity. Yet, the promise has not been realized due to their limitations, such as lower capacity compared to traditional LIB, dendrite growth, detrimental degradation of electrode materials structure as ions intercalate/de-intercalate, and gas evolution/corrosion at the electrodes, which remains a significant challenge. To address the challenges, various 2D materials with different physiochemical characteristics have been utilized. This review explores fundamental physiochemical characteristics of widely used 2D materials in AZIBs, including graphene, MoS2, MXenes, 2D metal organic framework, 2D covalent organic framework, and 2D transition metal oxides, and how their characteristics have been utilized or modified to address the challenges in AZIBs. The review also provides insights and perspectives on how 2D materials can help to realize the full potential of AZIBs for next-generation safe and reliable energy storage devices.

Development of rapid and effective oil-spill response system integrated with oil collection, recovery and storage devices for small oil spills at initial stage: From lab-scale study to field-scale test.

In the present study, through the laboratory-to-field scale experiments and trials, we report the development and evaluation of an integrated oil-spill response system capable of oil collection, recovery (separation), and storage, for a timely and effective response to the initial stage of oil-spill accidents. With the laboratory-scale experiments, first, we evaluate that the water-surface waves tend to abate the oil recovery rate below 80% (it is above 95% for the optimized configuration without the waves), which is overcome by installing the hydrophilic (and oleophobic) porous structures at the inlet and/or near the water outlet of the separator. In the follow-up meso-scale towing tank tests with a scaled-up prototype, (i) we optimize the maneuverability of the assembled system depending on the speed and existence of waves, and (ii) evaluate the oil recovery performance (more than 80% recovery for the olive oil and Bunker A fuel oil). Although more thorough investigations and improvements are needed, a recovery rate of over 50% can be achieved for the newly enforced marine fuel oil (low sulfur fuel oil, LSFO) that was not targeted at the time of development. Finally, we perform a series of field tests with a full-scale system, to evaluate the rapid deployment and operational stability in the real marine environment. The overall floating balance and coordination of each functional part are sustained to be stable during the straight and rotary maneuvers up to the speed of 5 knots. Also, the collection of the floating debris (mimicking the spilled oil) is demonstrated in the field test. The present system is now being tested by the Korea Coast Guard and we believe that it will be very powerful to prevent the environmental damage due to the oil spills.

Gastrointestinal AA Amyloidosis following Recurrent SARS-CoV-2 Infection: A Case Report.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has been associated with the overproduction of serum amyloid A protein, resulting in systemic AA amyloidosis. In this report, we describe a case of gastrointestinal (GI) AA amyloidosis following SARS-CoV-2 infection. A 75-year-old male presented to the emergency department with upper abdominal pain 6 weeks post kidney transplantation. He had a history of SARS-CoV-2 infection 4 weeks prior. On day 7 of hospitalization, while receiving conservative management, the patient developed symptoms of cough and fever, leading to a diagnosis of SARS-CoV-2 reinfection. The patient's abdominal pain persisted, and hematochezia developed on day 30 of hospitalization. Esophagogastroduodenoscopy and colonoscopy revealed multiple ulcers in the stomach and colon, with histologic findings revealing the presence of amyloid A. The patient was managed conservatively and was also given remdesivir for the SARS-CoV-2 infection. His clinical symptoms subsequently improved, and endoscopic findings demonstrated improvement in multiple gastric ulcers. GI amyloidosis may be a subacute complication following SARS-CoV-2 infection in immunocompromised patients.

Gas composition measurements in randomly distributed and fast moving gas bubbles in two-phase fluids.

Gas composition in randomly distributed and fast-moving bubbles was optically measured aided by laser-induced breakdown spectroscopy (LIBS). Laser pulses were focused at a point in a stream of bubbles to induce plasmas for the LIBS measurements. The distance between the laser focal point and liquid-gas interface, or 'depth,' plays a major role in determining the plasma emission spectrum in two-phase fluids. However, the 'depth' effect has not been investigated in previous studies. Therefore, we evaluated the 'depth' effect in a calibration experiment near a still and flat liquid-gas interface using proper orthogonal decomposition, and a support vector regression model was trained to exclude the influence of the interfacing liquid and extract gas composition information from the spectra. The gaseous molecular oxygen mole fraction in the bubbles was accurately measured under realistic two-phase fluid conditions.

Characterization of the physical and weathering properties of low sulfur fuel oil (LSFO) and its spreading on water surface.

Effective countermeasures against the marine pollution caused by spilled oil are enabled based on the understanding of its physical and weathering characteristics. In that sense, our knowledge of the newly enforced low-sulfur fuel oil (LSFO) needs to be secured urgently. First, we show that the oil viscosity increases with decreasing temperature, following the William-Landel-Ferry law developed for bunker oil. The meso-stable emulsion is achieved from the emulsion test, of which the viscosity is 10-100 times larger than the normal one. On the other hand, the portion of the evaporation of LSFO was insignificant (less than 3%), and thus, its effect on the oil properties is not substantial except the increase of the viscosity. In addition, we experimentally examine the spreading features (e.g., spreading area and rate) of LSFO on the water surface in the circulating water bath. We find that initially, the oil spreading area increases quite fast but saturates, of which the details are explained in terms of the driving and retarding forces involved in the spreading processes. Finally, considering the procured properties of the LSFO, we performed a numerical simulation of spreading LSFO on the water surface with a scale of hundred meters, which shows that our analysis can be extended to larger scales.

Bubble velocimetry using the conventional and CNN-based optical flow algorithms.

In the present study, we introduce new bubble velocimetry methods based on the optical flow, which were validated (compared) with the conventional particle tracking velocimetry (PTV) for various gas-liquid two-phase flows. For the optical flow algorithms, the convolutional neural network (CNN)-based models as well as the original schemes like the Lucas-Kanade and Farnebäck methods are considered. In particular, the CNN-based method was re-trained (fine-tuned) using the synthetic bubble images produced by varying the density, diameter, and velocity distribution. While all models accurately measured the unsteady velocities of a single bubble rising with a lateral oscillation, the pre-trained CNN-based method showed the discrepancy in the averaged velocities in both directions for the dilute bubble plume. In terms of the fluctuating velocity components, the fine-tuned CNN-based model produced the closest results to that from PTV, while the conventional optical flow methods under- or over-estimated them owing to the intensity assumption. When the void fraction increases much higher (e.g., over 10%) in the bubble plume, the PTV failed to evaluate the bubble velocities because of the overlapped bubble images and significant bubble deformation, which is clearly overcome by the optical flow bubble velocimetry. This is quite encouraging in experimentally investigating the gas-liquid two-phase flows of a high void fraction. Furthermore, the fine-tuned CNN-based model captures the individual motion of overlapped bubbles most faithfully while saving the computing time, compared to the Farnebäck method.

Optimized mechanism for fast removal of infectious pathogen-laden aerosols in the negative-pressure unit.

It has been frequently emphasized that highly contagious respiratory disease pathogens (such as SARS-CoV-2) are transmitted to the other hosts in the form of micro-sized aerosols (< 5 µm) in the air without physical contacts. Hospital environments such as negative-pressure unit are considered being consistently exposed to pathogens, so it is essential to quickly discharge them through the effective ventilation system. To achieve that, in the present study, we propose the optimized ventilation mechanism and design for the fastest removal of pathogen-laden aerosol using numerical simulations. We quantitatively evaluated the aerosol removal performance of various ventilation configurations (combinations of air exhaust and supply ducts), and found that the key mechanism is to form the coherent (preferentially upward) airflow structure to surround the respiratory flow containing the aerosol cluster. We believe that the present findings will play a critical role in developing the high-efficiency negative-pressure facility irrespective of its size and environments.

Particle leakage through the exhalation valve on a face mask under flow conditions mimicking human breathing: A critical assessment.

In today's era of active personal protections against airborne respiratory disease, general interest in the multiphase flow physics underlying face masks is greater than ever. The exhalation valves, installed on some masks to mitigate the breathing resistance, have also received more attention. However, the current certification protocol of evaluating airflow leakage only when suction pressure is applied is insufficient to capture practical aspects (particle penetration or leakage). Here, we experimentally measure two-phase flow across valve-type masks under conditions mimicking actual breathing. During exhalation, a high-speed jet through the valve accelerates the transmission of particles from inside while reasonable protection from external pollutants is achieved during inhalation, which supports the warnings from various public health officials. Based on the mechanism of particle penetration found here, we hope a novel design that both achieves high-efficiency shielding and facilitates easy breathing can be developed.

Deep learning-based automated and universal bubble detection and mask extraction in complex two-phase flows.

While investigating multiphase flows experimentally, the spatiotemporal variation in the interfacial shape between different phases must be measured to analyze the transport phenomena. For this, numerous image processing techniques have been proposed, showing good performance. However, they require trial-and-error optimization of thresholding parameters, which are not universal for all experimental conditions; thus, their accuracy is highly dependent on human experience, and the overall processing cost is high. Motivated by the remarkable improvements in deep learning-based image processing, we trained the Mask R-CNN to develop an automated bubble detection and mask extraction tool that works universally in gas-liquid two-phase flows. The training dataset was rigorously optimized to improve the model performance and delay overfitting with a finite amount of data. The range of detectable bubble size (particularly smaller bubbles) could be extended using a customized weighted loss function. Validation with different bubbly flows yields promising results, with AP50 reaching 98%. Even while testing with bubble-swarm flows not included in the training set, the model detects more than 95% of the bubbles, which is equivalent or superior to conventional image processing methods. The pure processing speed for mask extraction is more than twice as fast as conventional approaches, even without counting the time required for tedious threshold parameter tuning. The present bubble detection and mask extraction tool is available online ( https://github.com/ywflow/BubMask ).

Value probability analysis for linear phase estimation in sinusoidal structured-light range imaging.

Linear phase estimation is crucial for accuracy of sinusoidal structured-light range imaging. This Letter presents value probability analysis for a continuously differentiable function and shows that the probability of a value of the function is closely related to the derivative of the function. We apply the value probability analysis to the intensity, phase, and intermediate values in sinusoidal structured light, and we show that the probability adjustment of phase is more effective than those of other values for linear phase estimation. The phase probability adjustment is applied to synthetic and real scenarios of sinusoidal structured-light range imaging to show the effectiveness of the presented analysis and adjustment.

Tracking by Risky Particle Filtering over Sensor Networks.

The system of wireless sensor networks is high of interest due to a large number of demanded applications, such as the Internet of Things (IoT). The positioning of targets is one of crucial problems in wireless sensor networks. Particularly, in this paper, we propose minimax particle filtering (PF) for tracking a target in wireless sensor networks where multiple-RSS-measurements of received signal strength (RSS) are available at networked-sensors. The minimax PF adopts the maximum risk when computing the weights of particles, which results in the decreased variance of the weights and the immunity against the degeneracy problem of generic PF. Via the proposed approach, we can obtain improved tracking performance beyond the asymptotic-optimal performance of PF from a probabilistic perspective. We show the validity of the employed strategy in the applications of various PF variants, such as auxiliary-PF (APF), regularized-PF (RPF), Kullback-Leibler divergence-PF (KLDPF), and Gaussian-PF (GPF), besides the standard PF (SPF) in the problem of tracking a target in wireless sensor networks.

Association Between Gastric Emptying Time and Incidence of Cardiovascular Diseases in Subjects With Diabetes.

BACKGROUND/AIMS: Delayed gastric emptying (GE) is associated with high morbidity and mortality in subjects with diabetes. The aim of this study is to investigate associations between GE time and the major cardiovascular events (coronary heart diseases and ischemic stroke) in diabetic subjects with upper gastrointestinal (UGI) symptoms. METHODS: Among 259 subjects with chronic UGI symptoms who underwent gastric emptying study (GES) over 13 years, 122 diabetic subjects without gastric surgery and/or rapid GE were enrolled in this study. We also gathered data about baseline demographics, clinical characteristics, estimated GE half-time (GE T½) and incidence of cardiovascular events following GES. RESULTS: The mean age of subjects was 64.0 ± 17.4 years. There were 86 women and 104 subjects with type 2 diabetes. There were 52 (42.6%) subjects with normal GE, 50 (41.0.%) subjects with mild delayed GE, and 20 (16.4%) subjects with marked delayed GE. During follow-up (median, 207 weeks), cardiovascular events occurred in 7 (13.5%) subjects with normal GE, 4 (8.0%) subjects with mild delayed GE and 7 (35.0%) subjects with marked GE ( P = 0.015). Univariate analysis showed that GE T½ was significantly associated with incidence of cardiovascular events (crude OR, 1.74; 95% CI, 1.12-2.69; P = 0.014). In a multivariate model, association between GE T½ and incidence of cardiovascular events remained statistically significant after adjustment for baseline characteristics and comorbidities (adjusted OR, 1.94; 95% CI, 1.21-3.12; P = 0.006). CONCLUSION: A delay of GE was associated with an increased incidence of cardiovascular events in diabetic subjects with chronic UGI symptoms.

Evolution of Cavitation Bubble in Tap Water by Continuous-Wave Laser Focused on a Metallic Surface.

As an example of photon-matter interaction, we experimentally investigate the temporal evolution of a millimeter-sized cavitation bubble, induced by focusing a continuous-wave laser on a metallic plate in tap water. Our major interests are to understand the mechanism of bubble growth/shrinkage for a long time duration up to O(102) seconds and to draw the time-dependency relation of a bubble size, depending on the incident laser power. With the time passed after the laser with different power is focused, it is found that the phase change and/or transport of dissolved gas into the bubble play a dominant role in determining the bubble growth and shrinkage. Thus, we propose two stages in terms of time and three regimes depending on the incident energy, in which the evolutions of cavitation bubble in short and long time durations are distinctively identified. In regime I (lower incident power), the water nearby the focal point undergoes a phase change, resulting in an initial rapid growth of a bubble (first stage), but the convection flow due to locally heated surface causes the bubble to shrink at later times (second stage). As the laser power increases (regime III), more dissolved gas in the surrounding water enters the growing bubble and prevents the water phase from being absorbed into the bubble. Thus, the bubble growth is dominated by the dissolved gas. Between regimes I and III, there is a transitional regime II in which both the phase change of water and the dissolved gas contribute to the bubble evolution. We further our understandings by developing the relations about the time-dependency of bubble size for each stage and regime, which agree well with the measured data. The scaling relations are also validated with different conditions of liquid such as degassed water and NaCl solution. While previous studies have mostly focused on the nano- and/or microsized bubble generation in a very short time (less than 1 s), we think that the present results will extend our knowledge on how to predict and control the size of laser-induced cavitation bubble for longer time duration.

Outcomes of liver resection in patients with colorectal liver metastases by laparoscopic or open surgery.

BACKGROUNDS/AIMS: Colorectal cancer is found with liver metastases about 20-25% due to characteristics of cancer itself. Approximately 20% of liver metastases are found to be resectable. The objective of this study was to evaluate short-term outcomes of patients who received liver resection with colorectal cancer operation in our center by laparoscopic surgery or open surgery. METHODS: Short-term outcomes of laparoscopic surgery of liver resection (LSLR) group who underwent liver resection for colorectal liver metastases (CRLM) at a single institute from 2013 to 2016 were compared to those of open surgery of liver resection (OSLR) group. RESULTS: A total of 123 patients underwent liver resection for CRLM, including 101 (82.1%) patients in the OSLR group and 22 (17.9%) patients in the LSLR group. There were significant differences in tumor characteristics between the two groups, including synchronous and metachronous (p=0.004), tumor number (p<0.001), and tumor margin (p=0.002). For postoperative outcomes, only the length of hospital stay (LOS) was significantly different between the two groups (8.5 days in LSLR vs. 11 days in OSLR, p<0.001). There was no significant difference in overall rate of postoperative complications between the two groups (9.1% in LSLR vs. 23.8% in OSLR, p=0.158). CONCLUSIONS: There are no significant differences in postoperative outcomes between LSLR and OSLR except LOS, liver metastasis number, and resection margin. LSLR may be favorable for highly selected patients with CRLM.

Theoretical prediction and validation of cell recovery rates in preparing platelet-rich plasma through a centrifugation.

In the present study, we propose a theoretical framework to predict the recovery rates of platelets and white blood cells in the process of centrifugal separation of whole blood contained in a tube for the preparation of platelet-rich plasma. Compared to previous efforts to optimize or standardize the protocols of centrifugation, we try to further the physical background (i.e., based on the multiphase flow phenomena) of analysis to develop a universal approach that can be applied to widely different conditions. That is, one-dimensional quasi-linear partial differential equation to describe the centrifugal sedimentation of dispersed phase (red and white blood cells) in continuous phase (plasma) is derived based on the kinematic-wave theory. With the information of whole blood volume and tube geometry considered, it is possible to determine the positions of interfaces between supernatant/suspension and suspension/sediment, i.e., the particle concentration gradient in a tube, for a wide range of centrifugation parameters (time and acceleration). While establishing a theory to predict the recovery rates of the platelet and white blood cell from the pre-determined interface positions, we also propose a new correlation model between the recovery rates of plasma and platelets, which is found to be a function of the whole blood volume, centrifugal time and acceleration, and tube geometry. The present predictions for optimal condition show good agreements with available human clinical data, obtained from different conditions, indicating the universal applicability of our method. Furthermore, the dependence of recovery rates on centrifugal conditions reveals that there exist a different critical acceleration and time for the maximum recovery rate of platelets and white blood cells, respectively. The other parameters such as hematocrit, whole blood volume and tube geometry are also found to strongly affect the maximum recovery rates of blood cells, and finally, as a strategy for increasing the efficiency, we suggest to dilute the whole blood, increase the whole blood volume with a tube geometry fixed.

Generalized Redox-Responsive Assembly of Carbon-Sheathed Metallic and Semiconducting Nanowire Heterostructures.

One-dimensional metallic/semiconducting materials have demonstrated as building blocks for various potential applications. Here, we report on a unique synthesis technique for redox-responsive assembled carbon-sheathed metal/semiconducting nanowire heterostructures that does not require a metal catalyst. In our approach, germanium nanowires are grown by the reduction of germanium oxide particles and subsequent self-catalytic growth during the thermal decomposition of natural gas, and simultaneously, carbon sheath layers are uniformly coated on the nanowire surface. This process is a simple, reproducible, size-controllable, and cost-effective process whereby most metal oxides can be transformed into metallic/semiconducting nanowires. Furthermore, the germanium nanowires exhibit stable chemical/thermal stability and outstanding electrochemical performance including a capacity retention of ∼96% after 1200 cycles at the 0.5-1C rate as lithium-ion battery anode.

Hierarchical multiscale hyperporous block copolymer membranes via tunable dual-phase separation.

The rational design and realization of revolutionary porous structures have been long-standing challenges in membrane science. We demonstrate a new class of amphiphilic polystyrene-block-poly(4-vinylpyridine) block copolymer (BCP)-based porous membranes featuring hierarchical multiscale hyperporous structures. The introduction of surface energy-modifying agents and the control of major phase separation parameters (such as nonsolvent polarity and solvent drying time) enable tunable dual-phase separation of BCPs, eventually leading to macro/nanoscale porous structures and chemical functionalities far beyond those accessible with conventional approaches. Application of this BCP membrane to a lithium-ion battery separator affords exceptional improvement in electrochemical performance. The dual-phase separation-driven macro/nanopore construction strategy, owing to its simplicity and tunability, is expected to be readily applicable to a rich variety of membrane fields including molecular separation, water purification, and energy-related devices.

Electrostatic Force Microscopic Characterization of Early Stage Carbon Deposition on Nickel Anodes in Solid Oxide Fuel Cells.

Carbon deposition on nickel anodes degrades the performance of solid oxide fuel cells that utilize hydrocarbon fuels. Nickel anodes with BaO nanoclusters deposited on the surface exhibit improved performance by delaying carbon deposition (i.e., coking). The goal of this research was to visualize early stage deposition of carbon on nickel surface and to identify the role BaO nanoclusters play in coking resistance. Electrostatic force microscopy was employed to spatially map carbon deposition on nickel foils patterned with BaO nanoclusters. Image analysis reveals that upon propane exposure initial carbon deposition occurs on the Ni surface at a distance from the BaO features. With continued exposure, carbon deposits penetrate into the BaO-modified regions. After extended exposure, carbon accumulates on and covers BaO. The morphology and spatial distribution of deposited carbon was found to be sensitive to experimental conditions.