Search

The H atom tunneling dissociation dynamics of the S1 state of meta- or para-cresol has been investigated by using the picosecond time-resolved pump-probe spectroscopy in a state-specific manner. The S1 state lifetime (mainly due to the H atom tunneling reaction) is found to be mode-dependent whereas it quickly converges and remains constant as the rapid intramolecular vibrational energy redistribution (IVR) starts to participate in the S1 state relaxation with the increase of the S1 internal energy (Eint). The IVR rate and its change with increasing Eint have been reflected in the parent ion transients taken by tuning the total energy (hνpump + hνprobe) just above the adiabatic ionization threshold (so that the dissipation of the initial mode-character could be monitored as a function of the reaction time), indicating that the mode randomization rate into the S1 isoenergetic manifolds exceeds the tunneling rate quite early in terms of Eint for m-cresol (≤∼1200 cm−1) or p-cresol (≤∼800 cm−1) compared to the case of phenol (≤∼1800 cm−1). Though the H atom tunneling dynamics of phenol (S1) seems to be little influenced by the methyl substitution on the either m- or p-position, the IVR rate has been found to be strongly accelerated due to the sharply-increasing (S1) density of states with increasing Eint due to the pivotal role of the low-frequency CH3 torsional mode. [ABSTRACT FROM AUTHOR]

Out of practicality, ambient air rather than oxygen is preferred as a fuel in electrochemical systems, but CO2 and H2O present in air cause severe irreversible reactions, such as the formation of carbonates and hydroxides, which typically degrades performance. Herein, we report on a Na-air battery enabled by a reversible carbonate reaction (Na2CO3·xH2O, x = 0 or 1) in Nasicon solid electrolyte (Na3Zr2Si2PO12) that delivers a much higher discharge potential of 3.4 V than other metal-air batteries resulting in high energy density and achieves > 86 % energy efficiency at 0.1 mA cm−2 over 100 cycles. This cell design takes advantage of moisture in ambient air to form an in-situ catholyte via the deliquescent property of NaOH. As a result, not only reversible electrochemical reaction of Na2CO3·xH2O is activated but also its kinetics is facilitated. Our results demonstrate the reversible use of free ambient air as a fuel, enabled by the reversible electrochemical reaction of carbonates with a solid electrolyte. Metal-air batteries, operated in ambient air, suffer from irreversible redox reactions, limiting their energy density. Herein, the authors present a solid electrolyte-based sodium-air battery with a reversible carbonate reaction, facilitated by the in-situ formed catholyte enabled by moisture. [ABSTRACT FROM AUTHOR]

Background: Machine perfusion is an organ preservation strategy used to improve function over simple storage in a cold environment. This article presents an updated systematic review and meta-analysis of machine perfusion in deceased donor kidneys. Methods: RCTs from November 2018 to July 2023 comparing machine perfusion versus static cold storage in kidney transplantation were evaluated for systematic review. The primary outcome in meta-analysis was delayed graft function. Results: A total 19 studies were included, and 16 comparing hypothermic machine perfusion with static cold storage were analysed. The risk of delayed graft function was lower with hypothermic machine perfusion (risk ratio (RR) 0.77, 95% c.i. 0.69 to 0.86), even in kidneys after circulatory death (RR 0.78, 0.68 to 0.90) or brain death (RR 0.73, 0.63 to 0.84). Full hypothermic machine perfusion decreased the risk of delayed graft function (RR 0.69, 0.60 to 0.79), whereas partial hypothermic machine perfusion did not (RR 0.92, 0.69 to 1.22). Normothermic machine perfusion or short-term oxygenated hypothermic machine perfusion preservation after static cold storage was equivalent to static cold storage in terms of delayed graft function and 1-year graft survival. Conclusion: Hypothermic machine perfusion reduces delayed graft function risks and normothermic approaches show promise. This study is an extension of the study of Tingle et al. (2019), confirming previous findings with a larger number of participants. In kidney transplantation, hypothermic machine perfusion (HMP) reduces the incidence of delayed graft function, irrespective of donor type, cold ischaemia time, or machine type. Further investigation is needed to understand the impact of short-term HMP. The evidence for a more practical and novel method of perfusing deceased donor kidneys is now being investigated in clinical trials. [ABSTRACT FROM AUTHOR]

A practical, efficient approach for the synthesis of C4‐arylated 2‐quinolones from propargylic chlorides and anilines has been developed. The synthesis process involves subsequent oxidations of the initial products, tetrahydroquinolines and quinolinium ions, eventually leading to desired quinolones. A mechanism for the transformation is proposed based on a meticulous examination of intermediates and comprehensive control experiments. With a thorough understanding of the reaction mechanism, the applicability of the reaction scope is expanded. [ABSTRACT FROM AUTHOR]

Surface electromyography (sEMG) sensors play a critical role in diagnosing muscle conditions and enabling prosthetic device control, especially for lower extremity robotic legs. However, challenges arise when utilizing such sensors on residual limbs within a silicon liner worn by amputees, where dynamic pressure, narrow space, and perspiration can negatively affect sensor performance. Existing commercial sEMG sensors and newly developed sensors are unsuitable due to size and thickness, or susceptible to damage in this environment. In this paper, our sEMG sensors are tailored for amputees wearing sockets, prioritizing breathability, durability, and reliable recording performance. By employing porous PDMS and Silbione substrates, our design achieves exceptional permeability and adhesive properties. The serpentine electrode pattern and design are optimized to improve stretchability, durability, and effective contact area, resulting in a higher signal-to-noise ratio (SNR) than conventional electrodes. Notably, our proposed sensors wirelessly enable to control of a robotic leg for amputees, demonstrating its practical feasibility and expecting to drive forward neuro-prosthetic control in the clinical research field near future. [ABSTRACT FROM AUTHOR]

Osteoarthritis (OA) affects >500 million people globally, and this number is expected to increase. OA management primarily focuses on symptom alleviation, using non-steroidal anti-inflammatory drugs, including Celecoxib. However, such medication has serious side effects, emphasizing the need for disease-specific treatment. The meniscectomy and cranial cruciate ligament transection (CCLx)-treated beagle dog was used to investigate the efficacy of a modified-release formulation of SKI306X (SKCPT) from Clematis mandshurica, Prunella vulgaris, and Trichosanthes kirilowii in managing arthritis. SKCPT's anti-inflammatory and analgesic properties have been assessed via stifle circumference, gait, incapacitance, histopathology, and ELISA tests. The different SKCPT concentrations and formulations also affected the outcome. SKCPT improved the gait, histopathological, and ELISA OA assessment parameters compared to the control group. Pro-inflammatory cytokines and matrix metalloproteinases were significantly lower in the SKCPT-treated groups than in the control group. This study found that SKCPT reduces arthritic lesions and improves abnormal gait. The 300 mg modified-release formulation was more efficacious than others, suggesting a promising approach for managing OA symptoms and addressing disease pathogenesis. A high active ingredient level and a release pattern make this formulation effective for twice-daily arthritis treatment. [ABSTRACT FROM AUTHOR]

Human skeletal muscle is widely considered to be the most efficient actuator, leading to extensive research on developing artificial muscles. Bioinspired technologies such as soft robotics and biomimetics are used to produce artificial muscles with performance characteristics similar to those of their biological counterpart. Despite the complexity of human skeletal muscle, advanced engineering materials and unique approaches can help develop an artificial muscle that replicates its kinematic motions. Herein, biomimetic modular artificial muscle (BiMAM), which is the culmination of different design strategies, is presented, and fabrication methods aimed at developing this BiMAM. This chemically driven modular artificial muscle uses shape memory alloy coated with nanomaterials and nano‐catalysts. Herein, a high‐energy density fuel is employed to actuate this artificial muscle, enabling fast and efficient outputs. Multiple performance characteristics are determined by conducting controlled experiments. Various methods are demonstrated to control the fuel‐based valve system and the actuation of the chemically driven artificial muscle. Lastly, to evaluate its functionality, the curling movement of a robotic finger using BiMAM is demonstrated. [ABSTRACT FROM AUTHOR]

This study attempts to validate an infiltration model, the Soil Conservation Service–Curve Number (SCS–CN) method, using the nonofficial intermittent occurrence data of Eongtto Falls on Jeju Island, Korea. Simply due to the limited official continuous runoff data concerning Jeju Island, the validation of a newly set SCS-CN method for Jeju Island was practically impossible. Instead, this study tries to use nonofficial data for this purpose. This study focuses on the intermittent occurrence of Eongtto Falls, which is one of the most famous tourist attractions on the island. Various records of Eongtto Falls can be collected from newspapers, personal homepages, and various social networking services. The SCS-CN method is, in this study, used to check if effective rainfall occurs or not. In fact, this approach is quite effective on Jeju Island, as most streams are fully dry during non-rain periods. Evaluation of the SCS-CN method is based on the analysis of a contingency table, which measures the consistency of the occurrence of effective rainfall events and waterfall records. Additionally, to quantify the results of the contingency table, some measures such as accuracy, hit ratio, and false alarm ratio are used. This analysis is carried out using all the rainfall events from 2011 to 2019, and the derived results confirm that the newly set SCS-CN method is far better than the conventional one used thus far. [ABSTRACT FROM AUTHOR]

Wetlands are the largest natural source of methane (CH4) to the atmosphere. The eddy covariance method provides robust measurements of net ecosystem exchange of CH4, but interpreting its spatiotemporal variations is challenging due to the co‐occurrence of CH4 production, oxidation, and transport dynamics. Here, we estimate these three processes using a data‐model fusion approach across 25 wetlands in temperate, boreal, and Arctic regions. Our data‐constrained model—iPEACE—reasonably reproduced CH4 emissions at 19 of the 25 sites with normalized root mean square error of 0.59, correlation coefficient of 0.82, and normalized standard deviation of 0.87. Among the three processes, CH4 production appeared to be the most important process, followed by oxidation in explaining inter‐site variations in CH4 emissions. Based on a sensitivity analysis, CH4 emissions were generally more sensitive to decreased water table than to increased gross primary productivity or soil temperature. For periods with leaf area index (LAI) of ≥20% of its annual peak, plant‐mediated transport appeared to be the major pathway for CH4 transport. Contributions from ebullition and diffusion were relatively high during low LAI (<20%) periods. The lag time between CH4 production and CH4 emissions tended to be short in fen sites (3 ± 2 days) and long in bog sites (13 ± 10 days). Based on a principal component analysis, we found that parameters for CH4 production, plant‐mediated transport, and diffusion through water explained 77% of the variance in the parameters across the 19 sites, highlighting the importance of these parameters for predicting wetland CH4 emissions across biomes. These processes and associated parameters for CH4 emissions among and within the wetlands provide useful insights for interpreting observed net CH4 fluxes, estimating sensitivities to biophysical variables, and modeling global CH4 fluxes. [ABSTRACT FROM AUTHOR]

This paper presents the HybridSynchAADL modeling language and formal analysis tool for virtually synchronous cyber-physical systems with complex control programs, continuous behaviors, and bounded clock skews, network delays, and execution times. We leverage the Hybrid PALS methodology, so that it is sufficient to model and verify the much simpler underlying synchronous designs. We define the HybridSynchAADL language as a sublanguage of the avionics modeling standard AADL for modeling such synchronous designs in AADL. We define the formal semantics of HybridSynchAADL using Maude with SMT solving, which allows us to represent advanced control programs and communication features in Maude, while capturing timing uncertainties and continuous behaviors symbolically with SMT solving. We have developed new general methods for optimizing the performance of such symbolic rewriting, which makes the analysis of HybridSynchAADL models feasible. We have integrated the formal modeling and analysis of HybridSynchAADL models into the OSATE tool environment for AADL. Finally, we demonstrate the effectiveness of the Hybrid PALS methodology and HybridSynchAADL on a number of applications, including autonomous drones that collaborate to achieve common goals, and compare the performance of our tool with other state-of-the-art formal tools for hybrid systems. [ABSTRACT FROM AUTHOR]

Array pattern synthesis (APS) aims to create the desired array pattern as closely as possible to the prescribed mask template by varying the element excitations of the array. Herein, an efficient approach for the APS to control the sidelobe level is proposed. After designing the mask template to meet the prescribed sidelobe requirements and the waveform pattern, a set of element excitations is calculated through the Fourier transform performed on the projection the waveform pattern onto the mask template. Then, a desired array pattern can be synthesized from this updated set of excitation coefficients. The proposed APS approach directly presents a mathematical formulation of the exact set of excitations without any iterative optimization process. The proposed method is particularly suited for many array elements in linear antenna array. Thus, the proposed APS achieves substantial improvements in terms of computation complexity, performance, and ease of implementation in the algorithm when compared with conventional methods. Several simulation results are provided to verify the efficacy and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The πσ*‐mediated photochemistry of heteroaromatic molecules has provoked the investigation of the conical intersection dynamics. The Born–Oppenheimer approximation fails at the conical intersection where the S1 (ππ*) and S2 (πσ*) states cross. The nonadiabatic transitions are much influenced by the nuclear configuration of the reactive flux particularly in the curve‐crossing region encountered along the reaction pathway. In this article, we focus on the tunneling dynamics of phenols and thiophenols. The O (S)H bond cleavage occurs via tunneling through the barrier which is dynamically shaped by the upper‐lying S1/S2 conical intersection in terms of the couplings at the individual branching planes as well as along the (3N‐8) dimensional seam coordinates. State‐specific tunneling rates and their interpretation are given for phenol, substituted phenols, thiophenol, ortho‐substituted thiophenols, and benzenediols including their 1:1 water clusters. The completely orthogonal modes to the tunneling coordinate are very critical in the dynamic shaping of the reaction barrier. [ABSTRACT FROM AUTHOR]

Background: While hypertension is the most common comorbid condition in patients with coronavirus disease 2019 (COVID-19) in Korea, there is a lack of studies investigating risk factors in COVID-19 patients with hypertension in Korea. In this study, we aimed to examine the effects risk factors in hypertensive Korean COVID-19 patients.Methods: We selected patients from the database of the project #OpenData4Covid19. This information was linked to their 3-year historical healthcare data. The severity of the disease was classified into five levels. We also clustered the levels into two grades.Results: The risk factors associated with COVID-19 severity were old age, diabetes mellitus, cerebrovascular disease, chronic obstructive pulmonary disease (COPD), malignancy, and renal replacement therapy. The use of angiotensin converting enzyme inhibitors (ACEIs) or angiotensin receptor blockers (ARBs) both before and after a diagnosis of COVID-19 were not associated with COVID-19 severity. A multivariate analysis revealed that old age, male sex, diabetes mellitus, and renal replacement therapy were risk factors for severe COVID-19.Conclusion: The results suggest that in hypertensive patients with COVID-19, older age, male sex, a diagnosis of diabetes mellitus, and renal replacement therapy were risk factors for a severe clinical course. In addition, the use of ARBs and ACEIs before or after COVID-19 infection did not affect a patient's risk of contracting COVID-19 nor did it contribute to a worse prognosis for the disease. These results highlighted that precautions should be considered for hypertensive patients with those risk factors and do not support discontinuation of ARBs and ACEIs during COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Neuromodulation is a multi-interdisciplinary field of neuroscience, neural engineering, and medicine in a complex, but a way of understanding. Recently, the interest and researches in this field have been attracted due to its promising applications such as bionic limbs and bioelectronic medicine. For easier entry into this field, in this review, we approach the basic mechanism, methods, and applications of peripheral neuromodulation sequentially. Firstly, the overall structure and functions of the human nervous system are introduced, especially in the peripheral nervous system (PNS). Specifically, the fundamental neurophysiology regarding action potentials and neural signals is introduced to understand the communication between the neurons. Thereafter, two main methods for peripheral neuromodulation, which are electrical and optogenetic approaches, are introduced with the principles of the state-of-art devices. Finally, advanced applications of neuromodulation combined with the sensor, stimulator, and controller, called a closed-loop system are introduced with an example of bionic limbs. [ABSTRACT FROM AUTHOR]

13-kV 4H-SiC MOSFETs were successfully fabricated on a 125-μm -thick epitaxial layer on 6-in, N+ SiC substrates. Both lateral and longitudinal straggles from the P-well implant were investigated to optimize the JFET width and thus to avoid channel pinching in the JFET region. Channel lengths and channel mobilities were varied to investigate the effect of channel portions in determining the ON-state resistance of the 13-kV MOSFETs. It was discovered that the low channel mobility limits the transconductance, such that the MOSFETs cannot offer full current at reasonable gate voltages (Vgs = ~ 20 V). Even in high voltage MOSFETs, it is essential to have a reasonably high channel mobility to reduce ON-state power loss. Therefore, channel design and process are also important aspects of high voltage devices. A superior blocking capability of 13.2 kV was demonstrated using a ring-based edge termination structure. It is important to note that the straggling effect due to ion implantations should also be taken into account when designing an edge termination structure. Static electrical characteristics, scanning electron microscope (SEM) imaging, secondary ion mass spectrometry (SIMS) analysis, and 2-D simulation of the 13-kV MOSFETs were employed to support this reasoning. [ABSTRACT FROM AUTHOR]

This paper proposes a full body virtual try‐on which handles both top and bottom garments and generates realistic try‐on images. For the full body virtual try‐on, this paper addresses lack of suitable training data to align and fit top and bottom naturally. The proposed system consists of three modules: Clothing Guide Module (CGM), Geometric Matching Module (GMM), and Try‐On Module (TOM). CGM is introduced to generate a clothing guide map (CGMap) which describes the shape of a garment on a model. Unlike the single‐garment virtual try‐on scheme, it is impractical to collect meaningful data at a large scale for the multi‐garment system. To address this problem, two novel training strategies are proposed to leverage the existing training data. First, a pseudo triplet of model‐top‐bottom is generated from a pair of model‐top or model‐bottom which are already secured. Second, the CGM network is arranged to be exposed to both top and bottom garments during training. Then, the following GMM networks warp and align the top and bottom garments. Finally, TOM synthesizes a realistic try‐on image with the aligned garment and the CGMap. Experimental results prove remarkable performance of the proposed method in the full body virtual try‐on. [ABSTRACT FROM AUTHOR]

Methane flux (FCH4) measurements using the eddy covariance technique have increased over the past decade. FCH4 measurements commonly include data gaps, as is the case with CO2 and energy fluxes. However, gap‐filling FCH4 data are more challenging than other fluxes due to its unique characteristics including multidriver dependency, variabilities across multiple timescales, nonstationarity, spatial heterogeneity of flux footprints, and lagged influence of biophysical drivers. Some researchers have applied a marginal distribution sampling (MDS) algorithm, a standard gap‐filling method for other fluxes, to FCH4 datasets, and others have applied artificial neural networks (ANN) to resolve the challenging characteristics of FCH4. However, there is still no consensus regarding FCH4 gap‐filling methods due to limited comparative research. We are not aware of the applications of machine learning (ML) algorithms beyond ANN to FCH4 datasets. Here, we compare the performance of MDS and three ML algorithms (ANN, random forest [RF], and support vector machine [SVM]) using multiple combinations of ancillary variables. In addition, we applied principal component analysis (PCA) as an input to the algorithms to address multidriver dependency of FCH4 and reduce the internal complexity of the algorithmic structures. We applied this approach to five benchmark FCH4 datasets from both natural and managed systems located in temperate and tropical wetlands and rice paddies. Results indicate that PCA improved the performance of MDS compared to traditional inputs. ML algorithms performed better when using all available biophysical variables compared to using PCA‐derived inputs. Overall, RF was found to outperform other techniques for all sites. We found gap‐filling uncertainty is much larger than measurement uncertainty in accumulated CH4 budget. Therefore, the approach used for FCH4 gap filling can have important implications for characterizing annual ecosystem‐scale methane budgets, the accuracy of which is important for evaluating natural and managed systems and their interactions with global change processes. [ABSTRACT FROM AUTHOR]

Artificial Muscles Pritish Nagwade, Sanghoon Lee, and co‐workers present BiMAM – a biomimetic modular artificial muscle driven by chemical power and controlled by electronic signals (see article number 2300200). The bioinspired design of the nanoparticle‐coated artificial muscle unit in BiMAM enables larger chemical‐based actuation strokes. Additionally, an electromechanical system developed to facilitate chemical fuel control allows electronic manipulation of BiMAM. By demonstrating electromyography‐based control of BiMAM, this article glances at the future of chemical‐driven bionics and robotics. [ABSTRACT FROM AUTHOR]

Ecosystems can be characterized as complex systems that traverse a variety of functional and structural states in response to changing bioclimatic forcings. A central challenge of global change biology is the robust empirical description of these states and state transitions. An ecosystem's functional state can be empirically described using Process Networks (PN) that use timeseries observations to determine the strength of process‐level functional couplings between ecosystem components. A globally extensive source of in‐situ observations of terrestrial ecosystem dynamics is the FLUXNET eddy‐covariance network that provides standardized observations of micrometeorology and carbon, water, and energy flux dynamics. We employ the LaThuile FLUXNET synthesis dataset to delineate each month's functional state for 204 sites, yielding the LaThuile PN version 1.0 database that describes the strength of an ecosystem's functional couplings from air temperature and precipitation to carbon fluxes during each site‐month. Then we calculate the elasticity of these couplings to seasonal scale forcings: air temperature, precipitation, solar radiation, and phenophase. Finally, we train artificial neural networks to extrapolate these elasticities from 204 sites to the globe, yielding maps of the estimated functional elasticity of every terrestrial ecosystem's functional states to changing seasonal bioclimatic forcings. These maps provide theoretically novel resource that can be used to anticipate ecological state transitions in response to climate change and to validate process‐based models of ecological change. These elasticity maps show that each ecosystem can be expected to respond uniquely to changing forcings. Tropical forests, hot deserts, savannas, and high elevations are most elastic to climate change, and elasticity of ecosystems to seasonal air temperature is on average an order of magnitude higher than elasticity to other bioclimatic forcings. We also observed a reasonable amount of moderate relationships between functional elasticity and structural state change across different ecosystems. [ABSTRACT FROM AUTHOR]

The continuous measurement of H2O fluxes using the eddy covariance (EC) technique is still challenging for forests because of large amounts of wet canopy evaporation (EWC/, which occur during and following rain events when the EC systems rarely work correctly. We propose a new gap-filling and partitioning technique for the H2O fluxes: a model-statistics hybrid (MSH) method. It enables the recovery of the missing EWC in the traditional gap-filling method and the partitioning of the evapotranspiration (ET) into transpiration and (wet canopy) evaporation. We tested and validated the new method using the data sets from two flux towers, which are located at forests in hilly and complex terrains. The MSH reasonably recovered the missing EWC of 16-41mmyr-1 and separated it from the ET (14-23% of the annual ET). Additionally, we illustrated certain advantages of the proposed technique which enable us to understand better how ET responds to environmental changes and how the water cycle is connected to the carbon cycle in a forest ecosystem. [ABSTRACT FROM AUTHOR]

In the land surface models predicting vegetation growth and decay, representation of the seasonality of land surface energy and mass fluxes largely depends on how to describe the vegetation dynamics. In this study, we developed a new parameterization scheme to characterize allocation of the assimilated carbon to plant parts, including leaves and fine roots. The amount of carbon allocation in this scheme depends on the climatological net primary production (NPP) of the plants. The newly developed scheme is implemented in the augmented Noah land surface model with multiple parameterization options (Noah-MP) along with other biophysical processes related to variations in photosynthetic capacity. The scheme and the augmented biophysical processes are evaluated against tower measurements of vegetation from four forest sites in various regions-two for the deciduous broadleaf and two for the needleleaf evergreen forest. Results from the augmented Noah-MP showed good agreement with the observations and demonstrated improvements in representing the seasonality of leaf area index (LAI), gross primary production (GPP), ecosystem respiration (ER), and latent heat flux. In particular, significant improvements are found in simulating amplitudes and phase shift timing in the LAI seasonal cycle, and the amount of GPP and ER in the growing season. Furthermore, the augmented Noah-MP performed reasonably well in simulating the spatial distributions of LAI, GPP, and NPP in East Asia, consistent with the satellite observations. [ABSTRACT FROM AUTHOR]

The portion of clock power in system is rapidly increasing with the continuous increasing of clock frequency and clock resources. Last two decades, a great research attention has been paid to minimizing the clock power. Recently, it is shown that the structure of resonant clock networks is very effective in saving power since it can store electric energy to the inserted inductors rather than dissipate. On the other side, it has been known that dynamic voltage-frequency scaling (DVFS) is one of the most effectively and widely used power reduction techniques. However, so far no works have addressed the design methodology problem of synthesizing resonant clock networks that are able to operate under the designs with DVFS capability even though the problem is potentially very important to maximize the synergy effect on saving power. In this context, this paper proposes a comprehensive solution to the problem. Precisely, we propose a two-phase synthesis algorithm: 1) formulating the problem of inductor allocation, placement, and adjustable-sizing to support DVFS into a weighted set cover problem with the objective of minimizing total area of inductors and 2) followed by performing the task of resizing of adjustable driving buffers to support the switch of driving strength according to the clock frequencies by DVFS. Through experiments with benchmark circuits, it is shown that for designs with DVFS using 1 and 3 GHz, our algorithm synthesizes resonant clock networks with 25.9% less power on the execution of the clock frequency, which is not supported by resonant clocking in the previous no-DVFS aware resonant clock synthesis algorithm. [ABSTRACT FROM PUBLISHER]

Towards a better understanding of hydrological interactions between the land surface and atmosphere, land surface models are routinely used to simulate hydro-meteorological fluxes. However, there is a lack of observations available for model forcing, to estimate the hydro-meteorological fluxes in East Asia. In this study, Common Land Model (CLM) was used in offline-mode during the summer monsoon period of 2006 in East Asia, with different forcings from Asiaflux, Korea Land Data Assimilation System (KLDAS), and Global Land Data Assimilation System (GLDAS), at point and regional scales, separately. The CLM results were compared with observations from Asiaflux sites. The estimated net radiation showed good agreement, with r =0.99 for the point scale and 0.85 for the regional scale. The estimated sensible and latent heat fluxes using Asiaflux and KLDAS data indicated reasonable agreement, with r = 0.70. The estimated soil moisture and soil temperature showed similar patterns to observations, although the estimated water fluxes using KLDAS showed larger discrepancies than those of Asiaflux because of scale mismatch. The spatial distribution of hydro-meteorological fluxes according to KLDAS for East Asia were compared to the CLM results with GLDAS, and the GLDAS provided online. The spatial distributions of CLM with KLDAS were analogous to CLM with GLDAS, and the standalone GLDAS data. The results indicate that KLDAS is a good potential source of high spatial resolution forcing data. Therefore, the KLDAS is a promising alternative product, capable of compensating for the lack of observations and low resolution grid data for East Asia. [ABSTRACT FROM AUTHOR]

Context: Prediction of climate impacts on terrestrial ecosystems is limited by the complexity of the couplings between biosphere and atmosphere-what we define here as eco-climate. Critical transitions in ecosystem function and structure must be conceptualized, modeled, and ultimately predicted. Eco-climate system macrostate is a pattern of physical couplings between subsystems; each macrostate must be modeled differently because different physical processes are important. Critical transitions are less likely where the elasticity of macrostate is weak or absent. This motivates a fundamentally new complex systems approach. Objective: To model eco-climate macrostate, and its elasticity to seasonal climate forcing (air temperature and precipitation) and ecosystem biophysical state (phenophase). Methods: This Dynamical Process Network approach uses information flow to model an eco-climate system structure using timeseries observations from seven eddy-covariance tower sites in the United States. An aggregate power-law model estimates the elasticity of each location's macrostate to seasonal climate and phenophase. Results: Macrostate varies by both season and ecosystem type. Evergreen forests are highly elastic to air temperature and are more likely than agricultural or deciduous systems to experience state changes as the climate warms. Precipitation and phenophase elasticity is stronger in some agricultural, grassland, and deciduous forest systems. Conclusions: Different empirical model structures are needed based on season and location, to simulate ecosystem carbon dynamics and critical state transitions. Phenophase directly controls macrostate in some ecosystems. Flux data co-located with in situ ecological monitoring are essential for eco-climate model development and prediction using complex systems approaches. [ABSTRACT FROM AUTHOR]

1. SKI3301, a standardized dried 50% ethanolic extracts ofSophora tonkinensis, contains four marker compounds (trifolirhizin, TF; (–)-maackiain, Maack; (–)-sophoranone, SPN, and (2-(2,4-dihydroxyphenyl)-5,6-methylenedioxybenzofuran, ABF), is being developed as an herbal medicine for the treatment of asthma in Korea. This study investigates the pharmacokinetic properties of SKI3301 extract in rats. 2. The dose-proportional AUCs suggest linear pharmacokinetics of TF, Maack, SPN and ABF in the SKI3301 extract intravenous dose range of 5–20 mg/kg. After the oral administration of 200–1000 mg/kg of the extract, TF and Maack exhibited non-linearity due to the saturation of gastrointestinal absorption. However, linear pharmacokinetics of SPN and ABF were observed. 3. The absorptions of TF, Maack, SPN and ABF in the extract were increased relative to those of the respective pure forms due to the increased solubility and/or the decreased metabolism by other components in the SKI3301 extract. 4. No accumulation was observed after multiple dosing, and the steady-state pharmacokinetics of TF, Maack, SPN and ABF were not significantly different from those after a single oral administration of the extract. 5. The pharmacokinetics of TF, SPN and ABF were not significantly different between male and female rats after oral administration of the extract, but a significant gender difference in the pharmacokinetics of Maack in rats was observed. 6. Our findings may help to comprehensively elucidate the pharmacokinetic characteristics of TF, Maack, SPN and ABF and provide useful information for the clinical application of SKI3301 extract. [ABSTRACT FROM AUTHOR]

This study proposes an extended technology acceptance model to predict acceptance of synchronous e-learning by examining relationships among variables associated with factors influencing the technology acceptance of synchronous e-learning. Learners at an online university participated through an online survey; there were 251 respondents in all. Employing structural equation modeling, we tested a hypothesized model, and the resulting model was found to have a good fit. Self-efficacy, subjective norm, and system accessibility have an effect on learners’ technology acceptance of synchronous e-learning, whereas systematic lecture content does not affect it. In addition, the perceived ease of use also has an effect on behavioral intention, whereas perceived usefulness does not. This study examined the acceptance structure of synchronous e-learning. The findings are expected to enhance the understanding of synchronous e-learning for instructors and school administrators and also provide empirical evidence that can be used to establish effective strategies. [ABSTRACT FROM PUBLISHER]

We evaluated the effect of SKI3246, the 50 % ethanol extract of the rhizome of Atractylodes japonica, on visceral hypersensitivity, which is a major characteristic feature of IBS. We used various rat models of visceral hypersensitivity to assess the visceral pain responses to colorectal distension (CRD) in comparison with conventional IBS treatments. Oral administration of SKI3246 dose-dependently and significantly attenuated the abdominal withdrawal reflex (AWR) score in a model of acetic acid-induced visceral hypersensitivity. We also found that it reduced the number of abdominal contractions in response to CRD in a model of 2,4,6-trinitrobenzenesulfonic acid-induced visceral hypersensitivity, which was comparable to ramosetron or alosetron. Furthermore, treatment with SKI3246 also increased the pain threshold and abolished the elevated AWR scores to CRD in a rat model of neonatal maternal separation. We presumed that the modulation of the NK receptor is involved in the inhibitory activity of SKI3246 on the basis that it significantly inhibited the contraction of the distal colonic muscle induced by neurokinin A, the NK receptor agonist. The present results indicate that SKI3246 has the potential to be an effective therapeutic agent for IBS, especially insofar as it can relieve visceral hypersensitivity. [ABSTRACT FROM AUTHOR]

We report that time-dependent morphological changes of cortical vasculature, which would be associated with blood–brain barrier disruption, can be clearly visualized with high spatial resolution in a stroke mouse model using the multi-photon luminescence of long-circulating gold nanoparticles. [ABSTRACT FROM AUTHOR]

In the present study, we investigated the effects of 3- O-β- d-galactopyranosyl-(1 → 2)-[β- d-xylopyranosyl-(1 → 3)]-β- d-glucuronopyranosyl-28- O-[α- l-arabinopyranosyl-(1 → 4)-α- l-arabinopyranosyl-(1 → 3)-β- d-xylopyranosyl-(1 → 4)-α- l-rhamnopyranosyl-(1 → 2)-β- d-fucopyranosyl] quillaic acid, named compound 1, on the induction of apoptosis and autophagy in human gastric cancer AGS cells. Compound 1, a triterpenoid saponin isolated from the root of Adenophora triphylla var. japonica, effectively inhibited the growth of AGS cells by inducing apoptosis, as well as autophagy. Apoptosis by compound 1 treatment was associated with activation of caspases, release of cytochrome c, and increased ratio of Bax/Bcl-2. Autophagy by compound 1 treatment was indicated by LC3-II protein expression. We also found an increase in phosphorylation of p38 and JNK and a decrease in phosphorylation of ERK and Akt after compound 1 treatment. Furthermore, pretreatment with p38 inhibitor SB202190 completely inhibited compound 1-induced activation of caspases and cleavage of PARP1, whereas pretreatment with SB202190 synergistically increased the protein expression of LC3-II. These results suggest that compound 1 distinctly induces apoptotic and autophagic cell death and the increased autophagy by SB202190 protects compound 1-induced AGS cell death. Our findings provide an important clue for exploring the potential anticancer role of compound 1. [ABSTRACT FROM AUTHOR]

Surfaced enhanced Raman scattering (SERS) has been extensively exploited for label-free and non-destructive biochemical detections. Recently diverse SERS substrates have been reported to improve sensitivity of SERS. However, the current platforms still have technical limitation for in vivo applications. Here, we report a nanoplasmonic biopatch of plasmonic nanoparticles physically embedded in highly biocompatible and Raman inactive agarose hydrogel. Molecular diffusion of small molecules such as neurotransmitter through nanoplasmonic biopatch was quantitatively visualized without labeling by using real-time microscopic SERS. In particular, the nano/micro porous structures within agarose hydrogel allow the SERS detection of macromolecules such as amyloid fibrils. This soft SERS platform opens up new opportunities for in vivo SERS applications. [ABSTRACT FROM AUTHOR]

ABSTRACT Introduction The roots of Adenophorae species have been reported to exhibit anti-obese, anti-oxidant, anti-cancer, and anti-bacterial activities. However, there has been no single report regarding the preparative isolation and biological activities of the chemical components from Adenophora triphylla. Objective To develop an efficient method for the determination of the active fraction from the methanol extract from the roots of Adenophora triphylla and for the preparative isolation and purification of target compounds having cytotoxicity on carcinoma cells from the active fraction by high-speed counter-current chromatography (HSCCC). Methods The Plant (5 kg, dry weight) was extracted with methanol. Three hundred grams of the dried methanol extract (885 g) were fractionated by open-column chromatography with a stepwise gradient of water-methanol. Preparative isolation of bioactive components was performed by HSCCC with a two-phase solvent system composed of ethyl acetate- n-butanol-0.2% trifluoroacetic acid in water (5:5:10, v/v). The cytotoxicity of column fractions and isolated compounds was evaluated by 2-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazoliumbromide assay. Results The 70% MeOH column fraction showed inhibitory effects against three human carcinoma cells A549, AGS and HepG2. Two saponins were separated from 400 mg of the active fraction by HSCCC. After further purification with solid phase extraction column, 25 mg of peak fraction 1 and 20 mg of peak fraction 2 were obtained. Their structures were identified by 1 H-NMR, 13C-NMR, Fourier transform infrared, fast atom bombardment-MS and electrospray ionisation-MS/MS. They exhibited strong cytotoxic effects against three cancer cells. Conclusion Two cytotoxic saponins were isolated for the first time from the roots of Adenophora triphylla by HSCCC. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The datasets of net ecosystem CO exchange (NEE) were acquired from 21 forests, 3 grasslands, and 3 croplands in the eastern part of Asia based on the eddy covariance measurements of the international joint program, CarboEastAsia. The program was conducted by three networks in Asia, ChinaFLUX, JapanFlux, and KoFlux, to quantify, synthesize, and understand the carbon budget of the eastern part of Asia. An intercomparison was conducted for NEE estimated by three gap-filling procedures adopted by ChinaFLUX, JapanFlux, and KoFlux to test the range of uncertainty in the estimation of NEE. The overall comparison indicated good agreement among the procedures in the seasonal patterns of NEE, although a bias was observed in dormant seasons depending on the different criteria of data screening. Based on the gap-filled datasets, the magnitude and seasonality of the carbon budget were compared among various biome types, phenology, and stress conditions throughout Asia. The annual values of gross primary production and ecosystem respiration were almost proportional to the annual air temperature. Forest management, including clear-cutting, plantation, and artificial drainage, was significant and obviously affected the annual carbon uptake within the forests. Agricultural management resulted in notable seasonal patterns in the crop sites. The dataset obtained from a variety of biome types would be an essential source of knowledge for ecosystem science as well as a valuable validation dataset for modeling and remote sensing to upscale the carbon budget estimations in Asia. [ABSTRACT FROM AUTHOR]

Continuous and direct measurement of evapotranspiration (ET) by the eddy covariance (EC) technique is still a challenge under monsoon climate because of a considerable amount of missing data during the long rainy periods and the consequential gap-filling process. Under such wet canopy conditions, especially in forests, evaporation of the intercepted precipitation ( EWC) contributes significantly to the total ET. To quantify the role of EWC, leaf wetness has been measured at multiple levels in the canopy simultaneously with eddy covariance measurements at the KoFlux Gwangneung deciduous and coniferous forests for the entire year from September 2007 to August 2008. In this study, the measured EWC and the controlling mechanism during the wet canopy conditions have been scrutinized. Based on the evaluation of the four different algorithms of EWC estimation, that of the variable infiltration capacity (VIC) land surface model (LSM) has been adopted. All the missing EWC data are then recalculated by using the algorithm of VIC LSM and compared against the traditionally gap-filled EWC data based on the modified lookup table (MLT) method. The latter consistently underestimated EWC on average by 39% in deciduous forest and by 28% in coniferous forest. Major causes of such differences were due to the failure of considering aerodynamic coupling, advection of sensible heat, and heat storage in the MLT-based gap-filling method. Accordingly, a new gap-filling strategy for EWC is proposed that takes proper controlling mechanisms into account. [ABSTRACT FROM AUTHOR]

Platycosides (PSs), the saponins found in the root of Platycodon grandiflorum (Jacq.) A. DC. (Platycodi Radix), are typically composed of oleanene backbones with two side chains; one is a 3- O-glucose linked by a glycosidic bond, and the other is a 28- O-arabinose-rhamnose-xylose-apiose linked by an ester bond. Minor saponins, acetylated isomers of the major saponin on either the 2″ or 3″ position of rhamnose, were isolated from Platycodi Radix using a multi-step process including high-speed counter-current chromatography (HSCCC) and preparative reversed-phase high-performance liquid chromatography (RP-HPLC). After the separation of the major components, the enriched minor saponin fraction was used for this study. A two-phase solvent system consisting of chloroform-methanol-isopropanol-water (3:2:2:3, v/v) was used for HSCCC. HSCCC separation of the enriched minor saponin fraction yielded 2″- O-acetylplatycodin D, 3″- O-acetylpolygalacin D, 2″- O-acetylpolygalacin and a mixture of 3″- O-acetylplatycodin D and polygalacin D. The mixture fraction from HSCCC separation was further purified by preparative RP-HPLC, giving 3″- O-acetylplatycodin D and polygalacin D at a purity of over 98.9%. The developed method provides the preparative and rapid separation of minor saponins in the crude extract of Platycodi Radix. To the best of our knowledge, this is the first on the separation of acetylated PSs by HSCCC. [ABSTRACT FROM AUTHOR]

n expanded planar-fit (PF) method over complex terrain is presented and applied to coordinate rotation of the eddy-covariance (EC) flux and vertical velocity estimation. Theoretical analysis indicates that PF coefficients depend on wind direction, and an expression of vertical velocity is deduced. We applied the theory using 1 year of observations from the KoFlux site in the Gwangneung Forest in Korea and investigated the influence of wind direction on the PF method. Then, we performed an expansion of the PF method to consider dependence of PF coefficients on wind direction and applied the PF method to every sector. The results show that the PF coefficients and tilt angles over complex terrain vary with wind direction. Two hundred 30-min data sets are sufficient to derive stable PF coefficients over hilly terrain for each sector. The relative difference in eddy-covariance flux between the general planar fit (GPF) and sector planar fit (SPF) is less than 10% for the scalar flux and about 18% for friction velocity. Vertical velocity and vertical advection (VA) terms were also calculated and compared using SPF and GPF methods, and a normal distribution and diurnal trend of real vertical velocity on clear days are presented. [ABSTRACT FROM AUTHOR]

This article provides a detailed study of performance and reliability issues and trade-offs in silicon carbide (SiC) power MOSFETs. The reliability issues such as threshold voltage variation across devices from the same vendor, instability of threshold voltage under positive and negative gate bias, long-term reliability of gate oxide, screening of devices with extrinsic defects by means of gate voltage, body diode degradation, and short circuit withstand time are investigated through testing of commercial devices from different vendors and two-dimensional simulations. Price roadmap and foundry models of SiC MOSFETs are discussed. Future development of mixed-mode CMOS circuits with high voltage lateral MOSFETs along with 4−6× higher power handling capability compared to silicon circuits has been described. [ABSTRACT FROM AUTHOR]

This study evaluated the contribution of small agricultural reservoirs (the mool-tongs) to crop production on Udo, and the role they play. Agricultural water demand and deficit, water storage in the mool-tongs, and the amount of irrigation water were analyzed by applying the water balance model. In particular, the Blaney-Criddle method was used to estimate the agricultural water for crop growth. In this study, four typical crops of garlic, spring onion, peanut, and barley were considered, whose growing seasons were somewhat different from each other. A total of 47 years (1973–2019) of rainfall, temperature, and evaporation data were used in this study. As a result, it was confirmed that the crop coefficient, growing period of a crop, share of the cultivated area, and the seasonal distribution of rainfall affect the role of the mool-tongs. Comparison of the frequencies of occurrence of agricultural water deficit and irrigation interval before and after introducing the mool-tongs also confirms their usefulness. After the introduction of the mool-tongs for irrigation, the frequency of occurrence of agricultural water deficits changed significantly, from almost 30% of the entire simulation period to less than 20%. Even though the water supply capacity of the mool-tongs on Udo is insufficient to offset the entire agricultural water deficit, the water stored in the mool-tongs was found to considerably aid the survival of the crops and increase crop production. The results in this study can help to determine the capacity of rainwater collecting systems, especially on a small island where the available water resources are limited. [ABSTRACT FROM AUTHOR]

In this paper, a synthetic aperture radar (SAR) change detection approach is proposed based on a structural similarity index measure (SSIM) and multiple-window processing (MWP). The proposed scheme is performed in two steps: (1) generation of a coherence image based on MWP associated with SSIM and (2) gamma correction (GC) filtering. The proposed method is capable of providing a high-quality coherence image because the MWP operation based on SSIM has high sensitivity to the similarity measure for intensity between two SAR images. By finding an optimum value of order of GC, the proposed method can considerably reduce the effect of speckle noise on the coherence image, while retaining nearly all the information related to changed region involved in the change detection map. Several experimental results are presented to demonstrate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

This study investigates three issues regarding the application of the SCS–CN (Soil Conservation Service–Curve Number) method to a basin on the volcanic Jeju Island, Korea. The first issue is the possible relation between the initial abstraction and the maximum potential retention. The second is the determination of the maximum potential retention, which is also closely related to the estimation of CN. The third issue is the effect of the antecedent soil moisture condition (AMC) on the initial abstraction, maximum potential retention and CN. All of these issues are dealt with based on the analysis of several rainfall events observed in the Hancheon basin, a typical basin on Jeju Island. In summary, the results are that, firstly, estimates of initial abstraction, ratio λ , maximum potential retention, and CN were all found to be consistent with the SCS–CN model structure. That is, CN and the maximum potential retention showed a strong negative correlation, and the ratio λ and the maximum potential retention also showed a rather weak negative correlation. On the other hand, a significant positive correlation was found between CN and the ratio λ. Second, in the case where the accumulated number of days is four or five, the effect of antecedent precipitation amount is clear. The antecedent five-day rainfall amount for the AMC-III condition is higher than 400 mm, compared to the AMC-I condition of less than 100 mm. Third, an inverse proportional relationship is found between the AMC and the maximum potential retention. On the other hand, a clear linear proportional relation is found between the AMC and CN. Finally, the maximum potential retention for the Hancheon basin is around 200 mm, with the corresponding CN being around 65. The ratio between the initial abstraction and the maximum potential retention is around 0.3. Even though these results are derived by analyzing a limited number of rainfall events, they are believed to properly consider the soil characteristics of Jeju Island. [ABSTRACT FROM AUTHOR]

Many process-based models for carbon flux predictions have faced a wide range of uncertainty issues. The complex interactions between the atmosphere and the forest ecosystems can lead to uncertainties in the model result. On the other hand, artificial intelligence (AI) techniques, which are novel methods to resolve complex and nonlinear problems, have shown a possibility for forest ecological applications. This study is the first step to present an objective comparison between multiple AI models for the daily forest gross primary productivity (GPP) prediction using satellite remote sensing data. We built the AI models such as support vector machine (SVM), random forest (RF), artificial neural network (ANN), and deep neural network (DNN) using in-situ observations from an eddy covariance (EC) flux tower and satellite remote sensing data such as albedo, aerosol, temperature, and vegetation index. We focused on the Gwangneung site from the Korea Regional Flux Network (KoFlux) in South Korea, 2006–2015. As a result, the DNN model outperformed the other three models through an intensive hyperparameter optimization, with the correlation coefficient (CC) of 0.93 and the mean absolute error (MAE) of 0.68 g m−2 d−1 in a 10-fold blind test. We showed that the DNN model also performed well under conditions of cold waves, heavy rain, and an autumnal heatwave. As future work, a comprehensive comparison with the result of process-based models will be necessary using a more extensive EC database from various forest ecosystems. [ABSTRACT FROM AUTHOR]