Correlations between Properties of Pore-Filling Ion Exchange Membranes and Performance of a Reverse Electrodialysis Stack for High Power Density

The reverse electrodialysis (RED) stack-harnessing salinity gradient power mainly consists of ion exchange membranes (IEMs). Among the various types of IEMs used in RED stacks, pore-filling ion exchange membranes (PIEMs) have been considered promising IEMs to improve the power density of RED stacks. The compositions of PIEMs affect the electrical resistance and permselectivity of PIEMs; however, their effect on the performance of large RED stacks have not yet been considered. In this study, PIEMs of various compositions with respect to the RED stack were adopted to evaluate the performance of the RED stack according to stack size (electrode area: 5 × 5 cm2 vs. 15 × 15 cm2). By increasing the stack size, the gross power per membrane area decreased despite the increase in gross power on a single RED stack. The electrical resistance of the PIEMs was the most important factor for enhancing the power production of the RED stack. Moreover, power production was less sensitive to permselectivities over 90%. By increasing the RED stack size, the contributions of non-ohmic resistances were significantly increased. Thus, we determined that reducing the salinity gradients across PIEMs by ion transport increased the non-ohmic resistance of large RED stacks. These results will aid in designing pilot-scale RED stacks

Techno-Economic Comparative Analysis of Two Hybrid Renewable Energy Systems for Powering a Simulated House, including a Hydrogen Vehicle Load at Jeju Island

This work undertakes a techno-economic comparative analysis of the design of photovoltaic panel/wind turbine/electrolyzer-H2 tank–fuel cell/electrolyzer-H2 tank (configuration 1) and photovoltaic panel/wind turbine/battery/electrolyzer-H2 tank (configuration 2) to supply electricity to a simulated house and a hydrogen-powered vehicle on Jeju Island. The aim is to find a system that will make optimum use of the excess energy produced by renewable energies to power the hydrogen vehicle while guaranteeing the reliability and cost-effectiveness of the entire system. In addition to evaluating the Loss of Power Supply Probability (LPSP) and the Levelized Cost of Energy (LCOE), the search for achieving that objective leads to the evaluation of two new performance indicators: Loss of Hydrogen Supply Probability (LHSP) and Levelized Cost of Hydrogen (LCOH). After analysis, for 0 < LPSP < 1 and 0 < LHSP < 1 used as the constraints in a multi-objective genetic algorithm, configuration 1 turns out to be the most efficient loads feeder with an LCOE of 0.3322 USD/kWh, an LPSP of 0% concerning the simulated house load, an LCOH of 11.5671 USD/kg for a 5 kg hydrogen storage, and an LHSP of 0.0043% regarding the hydrogen vehicle load

Analysis of RGB Plant Images to Identify Root Rot Disease in Korean Ginseng Plants Using Deep Learning

Ginseng is an important medicinal plant in Korea. The roots of the ginseng plant have medicinal properties; thus, it is very important to maintain the quality of ginseng roots. Root rot disease is a major disease that affects the quality of ginseng roots. It is important to predict this disease before it causes severe damage to the plants. Hence, there is a need for a non-destructive method to identify root rot disease in ginseng plants. In this paper, a method to identify the root rot disease by analyzing the RGB plant images using image processing and deep learning is proposed. Initially, plant segmentation is performed, and then the noise regions are removed in the plant images. These images are given as input to the proposed linear deep learning model to identify root rot disease in ginseng plants. Transfer learning models are also applied to these images. The performance of the proposed method is promising in identifying root rot disease

Statistical Analysis of Electrical Properties of Octanemonothiol versus Octanedithol in PEDOT:PSS-Electrode Molecular Junctions

We fabricated a large number of octanemonothiol (C8) and octanedithol (DC8) molecular electronic devices with PEDOT:PSS (3,4-ethylenedioxythiophene) interlayer and performed a statistical analysis on the electronic properties of these devices. From the analysis, we obtained the Gaussian plot of histograms of Logic, (current density (J)) and several statistical estimates such as arithmetic mean, median, Gaussian mean, arithmetic standard deviation, adjusted absolute median deviation, and Gaussian standard deviation. We determined the current density-voltage (J-V) characteristics from the statistically representative data for C8 and DC8 devices and found that the conductivity of C8 is higher than that of DC8 by a factor of similar to 10. The difference of the conductivity of C8 and DC8 devices is attributed to the difference of the contact properties between the C8 and DC8 PEDOT:PSS-interlayer molecular junctions

Analysis of RGB Plant Images to Identify Root Rot Disease in Korean Ginseng Plants Using Deep Learning

Ginseng is an important medicinal plant in Korea. The roots of the ginseng plant have medicinal properties; thus, it is very important to maintain the quality of ginseng roots. Root rot disease is a major disease that affects the quality of ginseng roots. It is important to predict this disease before it causes severe damage to the plants. Hence, there is a need for a non-destructive method to identify root rot disease in ginseng plants. In this paper, a method to identify the root rot disease by analyzing the RGB plant images using image processing and deep learning is proposed. Initially, plant segmentation is performed, and then the noise regions are removed in the plant images. These images are given as input to the proposed linear deep learning model to identify root rot disease in ginseng plants. Transfer learning models are also applied to these images. The performance of the proposed method is promising in identifying root rot disease

The Effect of Fermented Kefir as Functional Feed Additive in Post-Weaned Pigs

The control of the immune system of pigs after weaning is important in pig farming because productivity depends on the survival of the post-weaned pigs. Previously, antibiotics would have been administered in the case of infectious diseases to increase the survival rate of post-weaned pigs, but now, the use of antibiotics is strictly restricted in order to prevent other problems such as the occurrence of antibiotic-resistant pathogens. In this study, the effect of fermented kefir as a functional feed additive as a replacement to antibiotics was evaluated in terms of the microbial profile in fecal samples, immunological factors in the blood of pigs, growth performance measured as average daily gain (ADG) and the feed conversion rate (FCR) of post-weaned pigs. In the kefir-treated group, the number of lactic acid bacteria and Bacillus spp. in the fecal samples of the pigs increased with the kefir treatments. Interestingly, the number of coliform groups as opportunistic pathogens was reduced in the fecal samples of pigs treated with kefir. We found out that treatment with kefir enhanced the innate immunity of post-weaned pigs though the reduction of IL-6 as a proinflammatory cytokine and an increase in IgG as an immunoglobulin, enhancing immunological defense against pathogens. Finally, after treatment with kefir, we observed that the ADG of post-weaned pigs increased to 135.6% but FCR decreased to 92.2%. Therefore, this study shows that fermented kefir can be used as a functional feed additive and an antibiotic alternative in order to improve both the innate immune system and growth performance of post-weaned pigs

Antithrombotic Effect of the Ethanol Extract of Angelica gigas Nakai (AGE 232)

Cardiovascular diseases, such as stroke, are the most common causes of death in developed countries. Ischemic stroke accounts for 85% of the total cases and is caused by abnormal thrombus formation in the vessels, causing deficient blood and oxygen supply to the brain. Prophylactic treatments include the prevention of thrombus formation, of which the most used is acetylsalicylic acid (ASA); however, it is associated with a high incidence of side effects. Angelica gigas Nakai (AG) is a natural herb used to improve blood circulation via anti-platelet aggregation, one of the key processes involved in thrombus formation. We examined the antithrombotic effects of AGE 232, the ethanol extract of A. gigas Nakai. AGE 232 showed a significant reduction in death or paralysis in mice caused by collagen/epinephrine-induced thromboembolism in a dose-dependent manner and inhibition of collagen-induced human platelet aggregation in a concentration-dependent manner. Additionally, AGE 232-treated mice did not show severe bleeding in the gut compared to ASA-treated mice. AGE 232 resulted in a decrease in the number of neutrophils attached to the human umbilical vein endothelial cells (HUVECs) and lower inhibition of COX-1 in response to bleeding and damage to blood vessels, a major side effect of ASA. Therefore, AGE 232 can prevent thrombus formation and stroke

Flexible Molecular-Scale Electronic Devices Composed of Diarylethene Photoswitching Molecules

The electrical properties of diarylethene photoswitching molecular devices on flexible substrates are studied. When exposed to UV or visible light, diarylethene molecular devices show two electrical states (a high and a low conductance state) with a discrepancy of an order of magnitude in the level of current between the two states. The diarylethene flexible molecular devices exhibit excellent long-time stability and reliable electrical characteristics in both conductance states when subjected to various mechanical stresses

Decursin Alleviates Mechanical Allodynia in a Paclitaxel-Induced Neuropathic Pain Mouse Model

Chemotherapy-induced neuropathic pain (CINP) is a severe adverse effect of platinum- and taxane-derived anticancer drugs. The pathophysiology of CINP includes damage to neuronal networks and dysregulation of signal transduction due to abnormal Ca2+ levels. Therefore, methods that aid the recovery of neuronal networks could represent a potential treatment for CINP. We developed a mouse model of paclitaxel-induced peripheral neuropathy, representing CINP, to examine whether intrathecal injection of decursin could be effective in treating CINP. We found that decursin reduced capsaicin-induced intracellular Ca2+ levels in F11 cells and stimulated neurite outgrowth in a concentration-dependent manner. Decursin directly reduced mechanical allodynia, and this improvement was even greater with a higher frequency of injections. Subsequently, we investigated whether decursin interacts with the transient receptor potential vanilloid 1 (TRPV1). The web server SwissTargetPrediction predicted that TRPV1 is one of the target proteins that may enable the effective treatment of CINP. Furthermore, we discovered that decursin acts as a TRPV1 antagonist. Therefore, we demonstrated that decursin may be an important compound for the treatment of paclitaxel-induced neuropathic pain that functions via TRPV1 inhibition and recovery of damaged neuronal networks