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Electron transfer through the mitochondrial electron transport chain (ETC) can be critically blocked by the dysfunction of protein complexes. Redox-active molecules have been used to mediate the electron transfer in place of the dysfunctional complexes; however, they are limited to replacing complex I and are known to be toxic. Here we report artificial mitochondrial electron transfer pathways that enhance ETC activity by exploiting inner-membrane-bound gold nanoparticles (GNPs) as efficient electron transfer mediators. The hybridization of mitochondria with GNPs, driven by electrostatic interaction, is successfully visualized in real time at the level of a single mitochondrion. By observing quantized quenching dips via plasmon resonance energy transfer, we reveal that the hybridized GNPs are bound to the inner membrane of mitochondria irrespective of the presence of the outer membrane. The ETC activity of mitochondria with GNPs such as membrane potential, oxygen consumption, and ATP production is remarkably increasediin vitro/i.

Dynamics of release and cellular uptake of aqueous CO from CO-releasing molecules (CORMs) significantly affect signaling and cell viability. So far, it has been mainly observed by IR, UV-visible, and fluorescence techniques, which suffer from poor sensitivity and slow response time. Here, we show how to directly probe the mass transfer of aqueous CO from CORMs to cells using a fluidic chamber integrated with live cells and Raman reporters of large-area Au@Pd core-shell nanoparticle assembly to emulate a physiologically relevant microenvironment. We sensitively and directly detect CO release from trace CORMs of as low as 100 nM by measuring the Raman transitions of CO via rapid chemisorption onto the surface of the Au@Pd nanoparticles. By using our method, we successfully observe the dynamics of CO release from CORM-2 despite its very short half-life. We also reveal that the initial rate of CO release from CORM-3 is dramatically decreased by tens to hundreds of times when exposed to physiologically relevant pH variations from 7.4 to 2.5, which can be attributed to the acid hydrolysis of the CO ligand. CORM-2 tends to quickly release CO regardless of pH, probably because of its rapid cleavage into two monomeric Ru complexes by the co-solvent. The decrease in the initial rate at lower temperatures is more significant for CORM-3 than for CORM-2. Finally, we observe that the cellular uptake of aqueous CO from CORM-3 by lung cancer cells is approximately 2 times higher than that of normal lung cells.

Forecasting global food production is of growing importance in the context of globalizing food supply chains and observed increases in the frequency of climate extremes. The National Agriculture and Food Research Organization–Asia-Pacific Economic Cooperation Climate Center (NARO-APCC) Crop Forecasting Service provides yield forecasts for global cropland on a monthly basis using seasonal temperature and precipitation forecasts as the main inputs, and 1 year of testing the operation of the service was recently completed. Here we evaluate the forecasts for the 2019 yields of major commodity crops by comparing with the reported yields and forecasts from the European Commission’s Joint Research Centre (JRC) and the U.S. Department of Agriculture (USDA). Forecasts for maize, wheat, soybean, and rice were evaluated for 20 countries located in the Northern Hemisphere, including 39 crop-producing states in the United States, for which 2019 reported yields were already publicly available. The NARO-APCC forecasts are available several months earlier than the JRC and USDA forecasts. The skill of the NARO-APCC forecasts was good in absolute terms, but the forecast errors in the NARO-APCC forecasts were almost always larger than those of the JRC and USDA forecasts. The forecast errors in the JRC and USDA forecasts decreased as the harvest approached, whereas those in the NARO-APCC forecasts were rather stable over the season, with some exceptions. Although this feature seems to be a disadvantage, it may turn into an advantage if skillful forecasts are achievable in the earlier stages of a season. We conclude by discussing relative advantages and disadvantages and potential ways to improve global yield forecasting.

Detection of trace carbon monoxide (CO) dissolved in an aqueous phase is key for monitoring and optimizing biological and chemical gas conversions. So far, irrespective of the nonequilibrium nature of these conversion processes, because of low water solubility of CO, such detection has been performed indirectly, under the assumption of thermodynamic equilibrium, by the combination of chromatographic measurement of relatively abundant CO in a gas phase and Henry's law. Direct and sensitive detection of dissolved CO under nonequilibrium has not been explored yet. Here, we report the direct, ultrasensitive, and real-time monitoring of nonequilibrium dynamics of CO in an aqueous phase during biochemical conversions by devising miniaturized fluidic reactors with built-in CO-specific optical probes via surface-enhanced Raman spectroscopy. As the sensitive and selective probes, we fabricate ligand-free Au@Pd core-shell nanoparticle monolayers to maximize the Raman signal of single CO in the aqueous phase. We confirm that under equilibrium conditions, aqueous and gaseous CO concentrations estimated by our method are in good agreement with those measured directly and indirectly by gas chromatography (GC). We show that our probe can detect the aqueous CO concentrations as low as ca. 0.01% with high signal reproducibility, which is 200-fold more sensitive than that achieved by infrared spectroscopy. Finally, we successfully observe the nonequilibrium dynamics of the aqueous CO during biochemical reactions, which cannot be sensed by other detection methods including even indirect measurement by GC. We anticipate that our method can be widely applied not only for monitoring of biochemical gas reactions on multiple scales from a large reactor to a single-molecule level but also for molecular imaging of biological systems.

A rapid, precise method for identifying waterborne pathogens is critically needed for effective disinfection and better treatment. However, conventional methods, such as culture-based counting, generally suffer from slow detection times and low sensitivities. Here, we developed a rapid detection method for tracing waterborne pathogens by an innovative optofluidic platform, a plasmonic bacteria on a nanoporous mirror, that allows effective hydrodynamic cell trapping, enrichment of pathogens, and optical signal amplifications. We designed and simulated the integrated optofluidic platform to maximize the enrichment of the bacteria and to align bacteria on the nanopores and plasmonic mirror via hydrodynamic cell trapping. Gold nanoparticles are self-assembled to form antenna arrays on the surface of bacteria, such as Escherichia coli and Pseudomonas aeruginosa, by replacing citrate with hydroxylamine hydrochloride in order to amplify the signal of the plasmonic optical array. Owing to the synergistic contributions of focused light via the nanopore geometry, self-assembled nanoplasmonic optical antennas on the surface of bacteria, and plasmonic mirror, we obtain a sensitivity of detecting E. coli as low as 102 cells/ml via surface-enhanced Raman spectroscopy. We believe that our label-free strategy via an integrated optofluidic platform will pave the way for the rapid, precise identification of various pathogens., Nanoparticles: making it easier to detect waterborne pathogens A novel method using nanotechnology to rapidly identify bacteria in water samples has been developed by scientists in the Republic of Korea and the US. Waterborne pathogens kill millions of people each year, but detection methods can be time-consuming, lack sensitivity, and only work with small samples. Taewook Kang at Sogang University, Seoul, and co-workers fabricated a gold-coated mirror filled with nano-sized holes smaller than an individual bacterium, and added especially modified gold nanoparticles to their water samples. The nanoparticles stuck onto the surface of bacteria, such as Escherichia coli, which in turn made the bacteria likely to cluster around the mirror’s pores. These measures greatly enhanced the interactions between the bacteria and light, so that even very low cell concentrations could be detected using spectroscopy, and different species of bacteria could be distinguished.

Here, we report the direct and precise determination of volumetric mass transfer coefficient (kLa) of Carbon monoxide (CO) in miniaturized gas-liquid reactors via sensitive probing of the Raman transitions of aqueous trace CO without sampling. We confirm that weak Raman signals of aqueous CO can be significantly amplified by using Au@Pd core-shell nanoparticle monolayer via surface-enhanced Raman scattering and the amplified Raman intensity is linearly proportional to the concentration of aqueous CO in the range of 20 to 200 μM that is indirectly estimated by gas chromatography. We successfully determine kLa of CO in a miniaturized column-type gas-liquid reactor with a working volume of 2 ml which is not determined by sampling and subsequent gas chromatography measurement for gaseous CO due to small headspace volume. We find that the kLa values in miniaturized column-type and plate-type reactors are up to two orders of magnitude lower than those in large-scale reactors, presumably due to the absence of mechanical stirring. The lower kLa revealed by our method is also validated by fluid dynamic simulation. In addition, our method allows to determine kLa in miniaturized reactors, either with internal baffles or at different gas flow rates and temperatures. The kLa values in the miniaturized reactors are found to be more sensitive to changes in the temperature and flow rate than in the large-scale reactors, which is likely attributable to both improved mixing due to higher flow rates and faster heating rate due to smaller working volume. We believe that our method has a huge impact on CO gas conversion ranging from design and scale-up of gas-liquid reactors, process monitoring and optimization to high-throughput screening of strains or catalysts.

Owing to its high sensitivity and high selectivity along with rapid response time, plasmonic detection has gained considerable interest in a wide variety of sensing applications. To improve the fieldwork applicability and reliability of plasmonic detection, the integration of plasmonic nanoparticles into optical devices is desirable. Herein, we propose an integrated label-free detection platform comprising a plasmonic cavity that allows sensitive molecular detection via either surface-enhanced Raman scattering (SERS) or plasmon resonance energy transfer (PRET). A small droplet of metal ion solution spontaneously produces a plasmonic cavity on the surface of uncured poly(dimethylsiloxane) (PDMS), and as PDMS is cured, the metal ions are reduced to form a plasmonic antennae array on the cavity surface. Unique spherical feature and the integrated metallic nanoparticles of the cavity provide excellent optical functions to focus the incident light in the cavity and to rescatter the light absorbed by the nanoparticles. The optical properties of the plasmonic cavity for SERS or PRET are optimized by controlling the composition, size, and density of the metal nanoparticles. By using the cavity, we accomplish both 1000-fold sensitive detection and real-time monitoring of reactive oxygen species secreted by live cells via PRET. In addition, we achieve sensitive detection of trace amounts of toxic environmental molecules such as 5-chloro-2-methyl-4-isothiazolin-3-one/2-methyl-4-isothiazol-3-one (CMIT/MIT) and bisphenol A, as well as several small biomolecules such as glucose, adenine, and tryptophan, via SERS.

We report the synthesis of colloidal plasmonic microspheres by taking advantage of emulsions of polydimethylsiloxane (PDMS) in metal precursor solution. Within the emulsion, both the spontaneous formation and threedimensional (3D) assembly of metal nanoparticles take place at room temperature. The number of the nanoparticles being assembled in the microsphere is controllable according to the concentration of a metal precursor. In addition, owing to the surface charge and porosity of PDMS, positively charged and neutral molecules can be more concentrated in the plasmonic microsphere. We use this plasmonic microsphere for the detection of environmentally and biologically important molecules via surface-enhanced Raman spectroscopy, since 3D assembly of metal nanoparticles in the microsphere is size-comparable to a probed volume of incident light.

Recently, seasonal climate forecasts (SCFs) and their advances have gained increasing attention in agricultural communities, specifically because of their potential to improve climate risk management by increasing preparedness and thus enhance agricultural and economic outcomes. Seasonal predictions of crop diseases and insect pests that provide timely and accurate forecasts are especially valuable not only to farmers and extension workers (i.e., to inform their crop management decisions) but also to governments (i.e., to increase national-level disaster preparedness). In this study, we used a case study in Bicol, Philippines, to introduce an array of implementation strategies to facilitate the use of SCFs in the agricultural sector. To demonstrate the full potential of SCFs in the Bicol region, we developed and applied seasonal disease predictions for rice, with sequential activities that included a baseline study on disease epidemics in the target area, the examination of available SCFs, the development of a decision support system for seasonal disease predictions, and an evaluation of this system using SCF hindcasts. Finally, we disseminated the resulting seasonal disease predictions in the target area using an agro-met bulletin. The present study demonstrated a successful example of a developmental framework for the application of SCFs to agricultural decision-making with the support of relevant SCF-linked agricultural models. These implementation strategies, in combination with the lessons learned, can help guide prospective efforts of establishing similar climate services that utilize SCFs in developing countries to improve the outcomes and thus lead to enhanced and sustainable food security.

Here we propose facile and scalable synthesis of two-dimensional (2D) dendritic platinum nanoparticle at room temperature by exploiting an oil-in-water emulsion. The interfacial synthesis selectively provides platinum nanoparticle with 2D structure in high yield by controlling key reactants such as the amount of oleic acid and the concentration of block copolymer. Electrocatalytic activity of 2D dendritic platinum nanoparticle for oxygen reduction and methanol oxidation reaction is also examined.

We assessed the impacts of climate change and agricultural autonomous adaptation measures (changes in crop variety and planting dates) on food consumption and risk of hunger considering uncertainties in socioeconomic and climate conditions by using a new scenario framework. We combined a global computable general equilibrium model and a crop model (M-GAEZ), and estimated the impacts through 2050 based on future assumptions of socioeconomic and climate conditions. We used three Shared Socioeconomic Pathways as future population and gross domestic products, four Representative Concentration Pathways as a greenhouse gas emissions constraint, and eight General Circulation Models to estimate climate conditions. We found that (i) the adaptation measures are expected to significantly lower the risk of hunger resulting from climate change under various socioeconomic and climate conditions. (ii) population and economic development had a greater impact than climate conditions for risk of hunger at least throughout 2050, but climate change was projected to have notable impacts, even in the strong emission mitigation scenarios. (iii) The impact on hunger risk varied across regions because levels of calorie intake, climate change impacts and land scarcity varied by region.

High-tech markets are unpredictable owing to rapid technology innovation, diverse customer needs, high competition, and other elements. Many scholars have attempted to explain the uncertainty in high-tech markets using their own various approaches. However, sufficiently clear ways to predict diverse changes and trends in high-tech markets have yet to be presented. Thus, this paper proposes a new approach model, that is, systematic market segmentation, to give more accurate information. Using an empirical dataset from the mobile handset market in the Republic of Korea, we conduct our research model consisting of three steps. First, we categorize nine basic segments. Second, we test the stability of these segments. Finally, we profile the characteristics of the customers and products. We conclude that the approach is able to offer more diagnostic information to both practitioners and scholars. It is expected to provide rich information for an appropriate marketing mix in practice.

Programmable liposomes are designed to selectively produce various liposome-nanoparticle hybrids., Hybrid liposome/metal nanoparticles are promising candidate materials for biomedical applications. However, the poor selectivity and low yield of the desired hybrid during synthesis pose a challenge. We designed a programmable liposome by selective encoding of a reducing agent, which allows self-crystallization of metal nanoparticles within the liposome to produce stable liposome/metal nanoparticles alone. We synthesized seven types of liposome/monometallic and more complex liposome/bimetallic hybrids. The resulting nanoparticles are tunable in size and metal composition, and their surface plasmon resonance bands are controllable in visible and near infrared. Owing to outer lipid bilayer, our liposome/Au nanoparticle shows better colloidal stability in biologically relevant solutions as well as higher endocytosis efficiency than gold nanoparticles without the liposome. We used this hybrid in intracellular imaging of living cells via surface-enhanced Raman spectroscopy, taking advantage of its improved physicochemical properties. We believe that our method greatly increases the utility of metal nanoparticles in in vivo applications.

Self-formation of colloidal oil droplets in water or water droplets in oil not only has been regarded as fascinating fundamental science but also has been utilized in an enormous number of applications in everyday life. However, the creation of three-dimensional (3D) architectures by a liquid droplet and an immiscible liquid interface has been less investigated than other applications. Here, we report interfacial energy-driven spontaneous self-formation of a 3D plasmonic optical structure at room temperature without an external force. Based on the densities and interfacial energies of two liquids, we simulated the spontaneous formation of a plasmonic optical structure when a water droplet containing metal ions meets an immiscible liquid polydimethylsiloxane (PDMS) interface. At the interface, the metal ions in the droplet are automatically reduced to form an interfacial plasmonic layer as the liquid PDMS cures. The self-formation of both an optical cavity and integrated plasmonic nanostructure significantly enhances the fluorescence by a magnitude of 1000. Our findings will have a huge impact on the development of various photonic and plasmonic materials as well as metamaterials and devices.

We suggest a value market segmentation method for high-tech markets. Our research scope is the mobile handset market, which has the technology characteristics of a high-tech industry such as short cycle innovations, short technology development periods, and quick changes in customer needs. Thus, researchers and company strategists would use value or benefit segmentation method for high-tech market segmenting, because the characteristics may react to frequent changes. A value based market segmenting items are stable items for a long time, and so precisely explain customer needs. Specially, values related with product’s attributes have been shown to be more powerful items. In this paper, we try to show the superiority of a value market segmentation method through a Korean mobile handset market empirical case study.

Convergence has recently become a key word in all industries including telecommunications. The most noted case is the media and IT convergence in Korea. The reason for this is that broadcasting is under the influence of IT technology development, such as broadband, digitalized, and interactive trajectories. Mobile Internet Protocol Television (IPTV) is one of the converging technologies, which also includes mobile handsets and IPTV. Mobile IPTV will offer TV content via a mobile IP network such as WiMax or 4G all-IP[1]. It is important to forecast and understand new technology developments, because precise forecasting ensures the successful market entrance of new technologies. In the case of Mobile IPTV, a market study is more important because technology development to realize service will be completed in a few years.In this paper, we study mobile IPTV adoption using the suggested model, namely CE-TAM that evaluates convergent technology. We expect to get some implications; new adoption model for convergent evolved technology will be verified and managerial strategies of mobile IPTV will be set up

As information technology rapidly develops and the period required to enter new technology shortens, there emerges a wide variety of alternatives for consumers. When there are many alternatives in the market, users choose after making comparisons. This process of making comparisons is our research key. We established a research model to find a mixed effect that comes from new attitudes to technology adoption and alternative’s continuous usage intention. The effect is revealed through a relative attractiveness (RA) factor to explain a user’s process of comparison. We empirically test our research model in the new media services, such as mobile TV, web TV, and mobile IPTV. According to our research results, a continuous usage intention of an existing technology is an important factor to explain the adoption of a new technology. So, the contribution of our research is in finding a role for the RA factor in research in new technology adoption.

Leaf area index (LAI) is an important parameter to identify the water balance in forested watershed as a biological factor influencing directly on the evapotranspiration in the forest area. The purpose of this study was to estimate the LAI in a small forested watershed in summer and winter by applying the Terra/Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data to the LAI estimation method. In this study, the estimation was based on the absorption and scattering processes of the solar radiation in the vegetation canopy and the spectral reflectance characteristics of soil vegetation. First, we estimated LAI based on Price’s model by application of ASTER data on the forested watershed located in the Tenzan Mountains of Saga, Japan. To validate the results of LAI estimation, secondly, we compared them to the measured LAI obtained by a plant canopy analyzer (LAI-2000) on the observation area inside the target region. This study showed that the LAI estimation method was a feasible and accurate method as indicated by the high relationship (r = 0.97) between LAI derived from ASTER data and LAI measured by LAI-2000. This paper is the first report on LAI estimation using Terra/ASTER data based on Price’s model and field investigation. This LAI estimation method is a reliable and applicable method.

Climate change and mitigation measures have three major impacts on food consumption and the risk of hunger: (1) changes in crop yields caused by climate change; (2) competition for land between food crops and energy crops driven by the use of bioenergy; and (3) costs associated with mitigation measures taken to meet an emissions reduction target that keeps the global average temperature increase to 2 °C. In this study, we combined a global computable general equilibrium model and a crop model (M-GAEZ), and we quantified the three impacts on risk of hunger through 2050 based on the uncertainty range associated with 12 climate models and one economic and demographic scenario. The strong mitigation measures aimed at attaining the 2 °C target reduce the negative effects of climate change on yields but have large negative impacts on the risk of hunger due to mitigation costs in the low-income countries. We also found that in a strongly carbon-constrained world, the change in food consumption resulting from mitigation measures depends more strongly on the change in incomes than the change in food prices.

Two-dimensional (2D) gold nanoparticles can possess novel physical and chemical properties, which will greatly expand the utility of gold nanoparticles in a wide variety of applications ranging from catalysis to biomedicine. However, colloidal synthesis of such particles generally requires sophisticated synthetic techniques to carefully guide anisotropic growth. Here we report that 2D hyper-branched gold nanoparticles in the lateral size range of about 50 ~ 120 nm can be synthesized selectively on a 2D immiscible oil/water interface in a few minutes at room temperature without structure-directing agents. An oleic acid/water interface can provide diffusion-controlled growth conditions, leading to the structural evolution of a smaller gold nucleus to 2D nanodendrimer and nanourchin at the interface. Simulations based on the phase field crystal model match well with experimental observations on the 2D branching of the nucleus, which occurs at the early stage of growth. Branching results in higher surface area and stronger near-field enhancement of 2D gold nanoparticles. This interfacial synthesis can be scaled up by creating an emulsion and the recovery of oleic acid is also achievable by centrifugation.

Leaf area index (LAI) is an important factor to identify the water balance in the area of forest as a biological factor influencing directly on the evapotranspiration occurs in the forest area. This study is purposed to estimate the LAI on the forest area in summer and winter by applying the Terra-Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data to the LAI estimation method based on the absorption and scattering process of the vertical element of electromagnetic waves and the characteristics of reflection spectrum of soil-vegetation. Estimated LAI was derived from application of ASTER data on the northern forest area of Saga City as the target region in this study. LAI measured directly by means of LAI-2000 on the observation point inside the target region was compared to the estimated LAI derived from the ASTER data. This study proved that LAI estimation method was a feasible and accurate method as indicated by the high relationship (r=0.91) between LAI derived from ASTER data and LAI measured directly.