River discharge is a crucial indicator of climate change and requires accurate and continuous estimation for effective water resource management and environmental monitoring. This study used satellite gravimetry data to estimate river discharge in major basins with high discharge volumes, specifically the Congo and Orinoco basins. By enhancing the spatial resolution of gravity data through advanced post-processing techniques, including forward modeling and river routing schemes, we effectively detected changes in the water mass stored within river channels. Additionally, signals from surrounding regions were statistically removed using the Empirical Orthogonal Function (EOF) analysis to isolate river-specific discharge signals. These refined signals were then converted into river discharge data through seasonal calibration using the modeled discharge data. Our results demonstrate that this method yields accurate and reliable discharge estimates comparable to in-situ measurements from gauge stations, even without ground-based surveys such as an Acoustic Doppler Current Profiler (ADCP) field campaigns. This research highlights the significant potential of satellite-based gravity data as an alternative to traditional ground surveys, providing practical information on the hydrological status of regions associated with large-scale river systems.

최근 늘어나고 있는 이상 기상 현상으로 산사태 위험이 점차 증가하고 있다. 산사태는 막대한 인명 피해와 재산 피해를 초래할 수 있기에 이러한 위험을 사전에 평가함은 매우 중요하다. 최근 기술 발전으로 인해 능동형 원격탐사 방법을 사용하여 더 정확하고 상세한 지표 변위 및 강수 데이터를 얻을 수 있게 되었다. 그러나 이러한 데이터를 활용하여 산사태 예측 모델을 개발하는 연구는 찾기 힘들다. 따라서 본 연구에서는 합성개구레이더 간섭법(InSAR)을 사용한 지표 변위 자료와 하이브리드 고도면 강우(HSR) 추정 기법을 통한 강수 정보를 활용하여 산사태 민감도를 예측하는 기계학습 모델을 제시하고 있다. 나아가 기계학습의 블랙박스 문제를 극복할 수 있는 해석가능한 기계학습 방법인 SHAP을 이용하여 산사태 민감도의 영향 변수에 대한 중요도를 체계적으로 평가하였다. 경상북도 울진군을 대상으로 사례 연구를 수행한 결과, XGBoost가 가장 좋은 예측 성능을 보이며, 도로로부터의 거리, 지표 고도, 일 최대 강우 강도, 48시간 선행 누적 강우량, 사면 경사, 지형습윤지수, 단층으로 부터의 거리, 경사도, 지표 변위, 하천으로부터의 거리가 산사태 예측에 영향을 미치는 주요 변수로 밝혀졌다. 특히, 능동형 원격탐사를 통해 얻은 자료인 강우 강도와 지표 변위의 절댓값이 높을수록 산사태 발생 확률이 높음을 확인하였다. 본 연구는 능동형 원격탐사 자료의 산사태 민감도 연구에서의 활용 가능성을 실증적으로 보여주고 있으며, 해당 자료를 바탕으로 시공간적 으로 변하는 산사태 민감도를 도출함으로써 향후 산사태 민감도 모니터링에 효과적으로 활용될 수 있을 것으로 기대된다.

A phenylboric acid functionalized carbon dot (2-FPBA-CD) for rapid fluorescent sensing of glucose in blood was synthesized by simply mixing N, S-doped carbon dots (CDs) with phenylboric acid at room temperature. At pH 7.4, the response of 2-FPBA-CD to glucose could reach equilibrium in a very short time (10 min), with a wide responsive linear range of 19.70 μM to 2.54 mM, which can be applied to the detection of glucose in serum. The mechanism studies showed that the layered carbon film of 2-FPBA-CD aggregated after adding glucose, thereby leading to the fluorescence quenching of 2-FPBA-CD.

최근 해상 교통량 증가 및 연안 중심의 레저활동으로 인해 다양한 해양사고가 발생하고 있다. 그 중 선박사고는 인 명 및 재산 피해를 유발할 뿐만 아니라 기름 및 위험·유해물질 유출을 동반한 해양 오염사고로 이어질 가능성이 크다. 따 라서 해양사고 대비 및 대응을 위한 지속적인 선박 모니터링이 필요하다. 본 연구에서는 해상 선박 모니터링 체계 구축을 위한 초분광 원격탐사 기반의 항공 실험 수행 및 선박탐지 결과를 제시하였다. 한반도 서해 궁평항 인근 해역을 대상으로 초분광 항공관측을 수행하였으며, 사전에 다양한 선박 갑판에 대한 분광 라이브러리를 구축하였다. 탐지 방법으로는 spectral correlation similarity (SCS) 기법을 사용하였으며 초분광 영상과 선박 스펙트럼 사이의 공간 유사도 분포를 분석하 였다. 그 결과 초분광 영상에 존재하는 총 15개의 선박을 탐지하였으며 최대 유사도에 기반한 선박 갑판의 색상도 분류하 였다. 탐지 선박들은 고해상도 digital mapping camera (DMC) 영상과의 매칭을 통해 검증하였다. 본 연구는 해상 선박탐지 를 위한 항공 초분광 센서 활용의 기초로서 향후 원격탐사 기반의 선박 모니터링 시스템에 주요 역할을 할 것으로 기대된 다.

In this study, laser-induced graphene oxide (LIGO) was synthesized through a facile liquid-based process involving the introduction of deionized (DI) water onto polyimide (PI) film and subsequent direct laser irradiation using a CO2 laser (λ = 10.6 μm). The synthesized LIGO was then evaluated as a sensing material for monitoring changes in humidity levels. The synthesis conditions were optimized by precisely controlling the laser scribing speed, leading to the synthesis of LIGO with different structural characteristics and varying oxygen contents. The increased number of oxygen-containing functional groups contributed to the hydrophilic properties of LIGO, resulting in a superior humidity sensing capabilities compared with laser-induced graphene (LIG). The LIGO-based sensors outperformed LIG-based sensors, demonstrating approximately tenfold higher sensing responsivity when detecting changes at each humidity level, along with 1.25 to 1.75 times faster response/recovery times, making LIGO-based sensors more promising for humidity-monitoring applications. This study demonstrated laser ablation in a renewable and natural precursor as an eco-friendly and energy-efficient approach to directly synthesize LIGO with controllable oxidation levels.

Climate change has made outbreaks of insect-transmitted plant viruses increasingly unpredictable. Understanding spatio-temporal dynamics of insect vector migration can help forecast virus outbreaks, but the relationship is often poorly characterized. The incidence of Beet curly top virus (BCTV) was examined in 2,196 tomato fields in California from 2013-2022. In addition, we experimentally showed dispersal of the beet leafhopper, the only known vector of BCTV is negatively correlated with plant greenness, and we estimated spring migration timing using a vegetation greenness-based model. Potential environmental factors and spring migration time of beet leafhoppers were associated with BCTV incidence. We found BCTV incidence is strongly associated with spring migration timing rather than environmental factors themselves. In addition, the vegetation greenness-based model was able to accurately predict the severe BCTV outbreaks in 2013 and 2021 in California. The predictive model for spring migration time was implemented into a web-based mapping system, serving as a decision support tool for management purposes.

다양한 원인으로 콘크리트 구조물에 하중이 작용되며, 이에 대한 적절한 대응이 이루어지지 않으면 구조물에 열화가 발생하고, 붕괴와 같은 대규모 재난을 초래할 수 있다. 구조물에 발생하는 하중을 감 지하는 연구는 지속적으로 이루어지고 있지만, 안전성 모니터링을 위한 혁신적인 시스템에는 여전히 부족함이 존재한다. 탄소나노튜브/폴리우레탄 복합체는 다양한 공학 분야에서 구조물 건전성 모니터링 을 위한 센서로 활용되어 센싱 효과가 뛰어난 것으로 알려져 있다. 따라서 본 연구에서는 다양한 공학 분야에서 구조물 건전성 모니터링 센서로 활용되고 있는 탄소나노튜브/폴리우레탄 복합체를 제작하여 모니터링 시스템을 개발하였다. 다양한 하중에 대한 센싱 성능을 파악하기 위해 인장, 압축, 충격 시험 을 진행하였고, 동시에 센서의 전기적 변화를 분석하였다. 추가적으로 본 센서가 구조물 표면에 적용 됨에 따라 온도, 습도와 같은 환경적 영향성을 분석하여 활용 가능성을 평가하였다. 또한, 최대 48행, 48열의 다중 계측이 가능한 IoT 기반 다중 모니터링 시스템을 개발하고, 이를 구조물에 적용된 센서 와 연계하여 스마트 모니터링 시스템으로서의 성능을 평가하였다. 이를 통해 탄소나노튜브/폴리우레탄 복합체 기반 센서는 구조물 하중 감지 시스템으로 활용이 가능할 것으로 판단되었다.

The Sun-Earth Lagrange point L4, which is called a parking space of space, is considered one of the unique places where solar activity and the heliospheric environment can be observed continuously and comprehensively. The L4 mission affords a clear and wide-angle view of the Sun-Earth line for the study of Sun-Earth connections from remote-sensing observations. The L4 mission will significantly contribute to advancing heliophysics science, improving space weather forecasting capability, extending space weather studies far beyond near-Earth space, and reducing risk from solar radiation hazards on human missions to the Moon and Mars. Our paper outlines the importance of L4 observations by using remote-sensing instruments and advocates comprehensive and coordinated observations of the heliosphere at multi-points including other planned L1 and L5 missions. We mainly discuss scientific perspectives on three topics in view of remote sensing observations: (1) solar magnetic field structure and evolution, (2) source regions of geoeffective solar energetic particles (SEPs), and (3) stereoscopic views of solar corona and coronal mass ejections (CMEs).

Zeolitic imidazolate frameworks (ZIFs) along with carbon nanofibers and polyaniline composite have been explored as an electrochemical sensing platform in nitrite measurement at trace level. Owing to their topology, high surface area and porous structure, these metal–organic frameworks (MOFs) find widespread utility in different application domains. Nitrites are widely used as preservatives in dairy, meat products, and packaged food stuffs. They form N-nitrosamines, which are potential carcinogens and cause detrimental health effects. These ZIF-based MOFs along with carbon nanofibers and polyaniline have emerged as an efficient electrochemical sensing material. The composite has been characterized by X-ray diffraction, Fourier transform infrared spectroscopy, Raman spectroscopy, scanning electron microscopy, energy-dispersive X-ray spectroscopy, X-ray photoelectron spectroscopy, and BET surface area studies. The electrochemical performance of the composite has been evaluated by forming as a thin film of composite on the surface of glassy carbon electrode and studying its impedance as well as electrochemical sensing behavior. The sensor exhibited good analytical response in nitrite measurement with a limit of detection of 8.1 μM. The developed sensing platform has been successfully applied to quantify the nitrite levels from water samples. The results obtained are in good agreement with the results of standard protocol.

Achieving cost-effective and defect-free graphene sheets is highly desirable for sensor devices. Aiming this, few-layer graphene (~ 3) sheets are prepared by an electrochemical exfoliation with [NMP] [ HSO4] electrolyte (i.e., Bronsted acidic ionic liquid). A novel approach for the effective exfoliation of graphene sheets is demonstrated by (i) simultaneously applying a constant potential through an electrochemical cell (with different electrolyte concentrations) and (ii) together with sonication. The exfoliated graphene sheets are characterized through state-of-the-art techniques and sprayed on a glass substrate at optimum conditions. Thus, the transparent conducting sensor device is fabricated with a suitable contact electrode and used for ammonia vapor sensing and the sensor performances are highly dependent on the concentration of the ionic liquid used during the electrochemical exfoliation. The sensing response and limit of detection for the exfoliated graphene-based film were calculated as 3.56% and 432 ppb, respectively. Further studies indicated that the fabricated sensors are more selective towards ammonia molecules with quick response and recovery times.

The nanostructured dysprosium oxide ( Dy2O3) was synthesized by the co-precipitation method and incorporated with graphitic carbon nitride (g-C3N4) using the ultrasonication method. The resultant product is denoted as Dy2O3/ g-C3N4 nanocomposite which was further used for electrochemical sensing of riboflavin (RF). The physicochemical properties of Dy2O3/ g-C3N4 nanocomposite were examined using several characterization techniques. The obtained results exhibit the nanocomposite formation with the preferred elemental compositions, functional groups, crystalline phase and desired surface morphology. The electrocatalytic performance of Dy2O3/ g-C3N4 nanocomposite was scrutinized with a glassy carbon electrode (GCE) via differential pulse voltammetry (DPV) and cyclic voltammetry (CV) techniques with the conventional three-electrode system. The modified electrode distributes more active surface area suggesting high electrocatalytic activity for the RF detection with two linear ranges (0.001–40 μM and 40–150 μM), a low detection limit of 48 nM and sound sensitivity (2.5261 μA μM−1 cm− 2). Further, the designed sensor possesses high selectivity, excellent stability, repeatability and reproducibility. Finally, the fabricated sensor was successfully estimated for the detection of RF in actual food sample analysis using honey and milk with better recovery.

Owing to the rapid rise of global energy demands, the operation of nuclear power plants is still indispensable. However, following the nuclear accident at Fukushima-Daiichi in 2011, the secure sequestration of radioactive waste has become critical for ensuring safe operations. Among various forms of nuclear wastes, capturing radioactive organic iodide (ROIs, e.g., methyl iodide, ethyl iodide, and propyl iodide) as one of the important species in gas phase waste has been challenged owing to the insufficient sorbent materials. The environmental release of ROIs with high volatility can give rise to adverse effects, including the accumulation of these substances in the thyroid and the development of conditions such as hypothyroidism and thyroid cancer. Compared to an iodine molecule, ROIs exhibit low affinity for conventional sorbents such as Ag@mordenite zeolite and triethylenediamine-impregnated activated carbon (TED@AC), resulting in lower sorption rates and capacities. Furthermore, in conditions resembling practical adsorption environments with high humidity, the presence of H2O significantly impedes the adsorption process, leading to a nearly complete cessation of adsorption. To address these issues, metal-organic frameworks (MOFs) can be effective alternative sorbents owing to their high surface area and designable and tailorable pore properties. In addition, the wellfined crystalline structures of MOFs render in-depth study on the structure-properties relationship. However, there has been limited research on the adsorption of ROIs using MOFs, with the majority of adsorption processes relying on highly reversible physisorption. This type of ROIs adsorption not only exists in a precarious state that is susceptible to volatilization but also exhibits significantly reduced adsorption capabilities in humid environments. Thus, for the secure adsorption of the volatile ROIs, the development of sorbents capable of chemisorption is highly desirable. In this study, we focused on ROIs adsorption by electrophilic aromatic substitution with the electron-rich m-DOBDC4− (m-DOBDC4− = 4,6-dioxo-1,3-benzenedicarboxylate) present in Co2(m -DOBDC). The chemisorption of ROIs via electrophilic aromatic substitution not only leads to the formation of C-C bonds, ensuring stability but also triggers color changes in the crystal by interacting with open-metal sites and iodide ions. Leveraging these advantages, we developed an infrared radiation-based sensing method that demonstrates superior performance, exhibiting high adsorption capacities and rates, even under the challenging conditions of high-humidity practical environments.

An optical fluorescence quenching sensor based on functionally modified iron-doped carbon nanoparticles was designed for the selective and sensitive Cr(VI) ion detection. Multifunctional iron-doped carbon nanoparticles were enclosed in the scaffolds of a promising stable nanocarrier system called hyperbranched polyglycerol (HPG), which has been fluorescently modified with 1-pyrene butyric acid using the Steglich esterification procedure. The therapeutic and diagnostic capabilities were boosted when these nanoparticles were enclosed in the fluorescently modified dendritic structure, HPG. Iron-doped carbon nanoparticles coupled with fluorescently modified hyperbranched polyglycerol can be used as a sensor for metal ions and can then be used to successfully remove them from a sample. Moreover, the synthesised nanoparticles demonstrated promising antimicrobial efficacy against bacteria and fungi. These results are also discussed in detail.

In this work, norepinephrine (NE) was determined by an electrochemical sensor represented by a carbon paste electrode boosted using nitrogen-doped porous carbon (NDPC) derived from Spirulina Platensis microalga anchored CoFe2O4@ NiO and 1-Ethyl-3-methylimidazolium acetate (EMIM Ac) ionic liquid. The morphological characteristics of the catalyst were recorded by field emission scanning electron microscope (FE-SEM) images. Moreover, the electrochemical behavior of norepinephrine on the fabricated electrode was checked using various voltammetric methods. All tests were done at pH 7.0 as the optimized condition in phosphate buffer solution. The results from linear sweep voltammetry revealed that the electro-oxidation of norepinephrine was diffusion, and the diffusion coefficient value was obtained by chronoamperometry (D⁓6.195 × 10– 4). The linear concentration of the modified electrode was obtained from 10 to 500 μM with a limit of detection of 2.26 μM using the square wave voltammetry (SWV) method. The sensor selectivity was investigated using various species, and the results from stability and reproducibility tests showed acceptable values. The sensor's efficiency was tested in urine and pharmaceutical as real samples with recovery percentages between 97.1% and 102.82%.

Assertions in current academic research and practical discourse that promote agility reduce the importance or prominence given to organizational strategic planning. While firms today are required to become agile and thus quickly and timely respond to emerging market challenges, the strategic planning process is perceived as rigid, slow, and somehow obsolete and may contradict agility. These present practitioners with a dilemma regarding the relevance of planning in this era. This study examines the pertinence of strategy planning in this agile age and its effect on firms’ business performance. In addition, since the environment in which firms operate play a significant role in determining strategies, when maintaining strategic planning, organizations need to consider internal and external factors that may change the effect of planning on performance. Hence, the study also explores market scanning (an external condition) and fault tolerance climate (an internal condition) under which the relationship planning-performance varies. Based on a quantitative research, data from organizations, and insights from fit-as-moderation approach, a conceptual model and research hypotheses are designed and tested. Common and acceptable analysis methods were employed to test the hypotheses. Initial findings indicate that strategy planning should not be deemphasized in contemporary days since it is associated with better financial (e.g., sales growth) and nonfinancial (e.g., new customer acquirement) outcomes. Additionally, performance consequences of planning are dependent on firm external and internal conditions. While the positive planning-performance relationship is associated with higher levels of market sensing, it is negatively associated with higher levels of fault tolerance. The findings have well-timed theoretical and practical implications for the business and strategy literature. Managers considering the necessity of planning strategies should recognize its relevance and take into account contingencies examined in this research.

본 연구는 간 담도기 이미지에서 CAIPIRINHA, 압축 센싱(CS), 딥러닝(DL) 기법을 비교하여 주관적 영상의 질과 국소병변 을 평가하였다. 후향적 연구로 간 담도기 이미지를(획득 시간, CAIPIRINHA 16초, DL 11초, CS 15초; 절편두께, 3mm, 3mm, 1.5mm) 포함한 가도세틱산 조영증강 자기공명영상을 시행한 51명의 환자에서 3개의 이미지와 국소 간 병변은 주관적 이미지 질 평가를 분석하였다. 간 가장자리 선명도는 CAIPIRINHA(3.9±0.8), DL(4.5±0.6), CS(4.5±0.8), 호흡에 의한 운동 허상은 CAIPIRINHA(4.3±0.9), DL(4.7±0.6), CS(4.5±0.8)를 보였다. 21명 환자의 48개 병변에서, 가장자리 선예 도는 CAIPIRINHA(4.3±0.7), DL(4.5±0.6), CS(4.6±0.5), 선명도는 CAIPIRINHA(4.4±0.7), DL(4.7±0.5), CS (4.7±0.5)을 보였다. DL은 검사 시간을 줄이면서 CAIPIRINHA와 비슷한 질을 보이고 호흡 허상을 줄일 수 있다. CS는 얇은 절편 영상의 획득이 가능하여 비슷한 영상의 질을 보여 선택적으로 유용하게 사용할 수 있다.

Micro-electronic gas sensor devices were developed for the detection of carbon monoxide (CO), nitrogen oxides (NOx), ammonia (NH3), and formaldehyde (HCHO), as well as binary mixed-gas systems. Four gas sensing materials for different target gases, Pd-SnO2 for CO, In2O3 for NOx, Ru-WO3 for NH3, and SnO2-ZnO for HCHO, were synthesized using a sol-gel method, and sensor devices were then fabricated using a micro sensor platform. The gas sensing behavior and sensor response to the gas mixture were examined for six mixed gas systems using the experimental data in MEMS gas sensor arrays in sole gases and their mixtures. The gas sensing behavior with the mixed gas system suggests that specific adsorption and selective activation of the adsorption sites might occur in gas mixtures, and allow selectivity for the adsorption of a particular gas. The careful pattern recognition of sensing data obtained by the sensor array made it possible to distinguish a gas species from a gas mixture and to measure its concentration.

Forest destruction is an inevitable result of the development processes. According to the environmental impact assessment, over 10% of the destroyed trees need to be recycled and transplanted to minimize the impact of forest destruction. However, the rate of successful transplantation is low, leading to a high rate of tree death. This is attributable to a lack of consideration for environmental factors when choosing a temporary site for transplantation and inadequate management. To monitor transplanted trees, a field survey is essential; however, the spatio-temporal aspect is limited. This study evaluated the applicability of remote sensing for the effective monitoring of transplanted trees. Vegetation indices based on satellite remote sensing were derived to detect time-series changes in the status of the transplanted trees at three temporary transplantation sites. The mortality rate and vitality of transplanted trees before and after the transplant have a similar tendency to the changes in the vegetation indicators. The findings of this study showed that vegetation indices increased after transplantation of trees and decreased as the death rate increased and vitality decreased over time. This study presents a method for assessing newly transplanted trees using satellite images. The approach of utilizing satellite photos and the vegetation index is expected to detect changes in trees that have been transplanted across the country and help to manage tree transplantation for the environmental impact assessment.