Sensors International最新文献

{"title":"A method to detect enzymatic reactions with field effect transistor","authors":"","doi":"10.1016/j.sintl.2024.100302","DOIUrl":"10.1016/j.sintl.2024.100302","url":null,"abstract":"<div><div>Study of enzyme-substrate interactions is a task of great practical and scientific importance. This paper describes the application of ion-sensitive field effect transistors in quasi-equilibrium state for examination of enzymatic reactions. A reaction occurring in the liquid gate affects the chemical potential of electrons in this gate, and this phenomenon may be used to explore biochemical interactions. This strategy can be applied to detect interactions of enzymes with substrates, inhibitors and activators regardless of their optical and electrochemical properties. Using the developed method, the reactions catalyzed by the enzymes belonging to six different EC classes were analyzed, and Michaelis constants for their substrates were determibed. <em>K</em>_<em>m</em> values obtained using the proposed method were in good agreement with those obtained with standard colorimetric and fluorimentric assays. Practical potential of the described method was demonstrated by studying the interactions of a diagnostically significant enzyme α-D-galactosidase with its natural and artificial substrates and its inhibitor. <em>K</em>_<em>m</em> values for α-D-galactosidase using melibiose and raffinose as substrates and IC50 value for the enzyme inhibitor 1-deoxygalactonojirimycin were determined. The described method allows rapid and label-free investigation of enzyme interactions with substrates, inhibitors and activators for a wide range of biocatalysts.</div></div>","PeriodicalId":21733,"journal":{"name":"Sensors International","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S266635112400024X/pdfft?md5=4d52ee86a1d882d955efddee7d99e5d4&pid=1-s2.0-S266635112400024X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142312781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Blue luminescent carbon quantum dots derived from diverse banana peels for selective sensing of Fe(III) ions","authors":"","doi":"10.1016/j.sintl.2024.100301","DOIUrl":"10.1016/j.sintl.2024.100301","url":null,"abstract":"<div><p>The eco-friendly production of carbon quantum dots (CQDs) from natural resources remains appealing owing to their superior optical properties. This work presents the synthesis of highly fluorescent CQDs from peels of different varieties of Musa (yellow, green, and red) through a straightforward one-step hydrothermal process, without needing a bit of metal salt or oxidizing agent. The proposed method resulted in quantum yields (QY) of 18.06 %, and 13.06 %, for CQDs from normal yellow banana and green banana, respectively compared to other CQDs derived from natural sources. The QY for the CQDs extracted from the small yellow banana was 7.72 %, while the red banana had a much lower value of 2.6 %. The optical properties of CQDs of different banana peels are also compared. All the CQDs produced a blue color upon exposure to 360 nm UV radiation, and the fluorescence was excitation-dependent. Moreover, each of the four types of CQDs is proven to be an efficient fluorescent probe capable of selectively detecting Fe³⁺ ions. The linear variation of fluorescence with the analyte amount allowed quantification of ions, with a limit of the detection value of 6 μM, across a concentration range of 37–277 μM. Above all, the real-world applications aimed at sensing Fe³⁺ ions in tap water achieved excellent recoveries ranging from 96 to 100 %. Therefore, these tuneable CQDs with good optical properties present an auspicious avenue for developing nano-sensors in real-time applications.</p></div>","PeriodicalId":21733,"journal":{"name":"Sensors International","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666351124000238/pdfft?md5=048be3cb09037da0abdfa379b16ba763&pid=1-s2.0-S2666351124000238-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142163401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A capacitive sensor-based approach for type-2 diabetes detection via bio-impedance analysis of erythrocytes","authors":"","doi":"10.1016/j.sintl.2024.100300","DOIUrl":"10.1016/j.sintl.2024.100300","url":null,"abstract":"<div><p>This paper presents a novel capacitive sensor-based device for detecting type-2 diabetes through blood analysis. The proposed methodology measures changes in the complex permittivity of red blood cells (RBCs) caused by elevated glucose levels, affecting their rheological and electrical properties, such as viscosity, volume, relative permittivity, dielectric loss, and AC conductivity. These changes, well-documented in the literature, alter the bio-impedance signature of RBCs, serving as an indicator for type-2 diabetes. The study examines various concentrations of normal and diabetic RBCs within a frequency range of 50 kHz to 200 kHz, chosen for its relevance to bio-impedance responses. Experimental results show that healthy RBCs in a 200 <span><math><mi>μ</mi></math></span>L PBS solution have a complex permittivity (<span><math><msub><mrow><mi>ɛ</mi></mrow><mrow><mtext>mix</mtext></mrow></msub></math></span>) of 65.12 and conductivity (<span><math><msub><mrow><mi>σ</mi></mrow><mrow><mtext>mix</mtext></mrow></msub></math></span>) of 0.63 S/m, while diabetic RBCs measure 73.44 and 0.68 S/m, respectively. Additionally, the complex permittivity decreases as the cell concentration increases for both normal and diabetic RBCs. At 100% cell concentration, the average bio-impedance for diabetic blood cells is 50.3 k<span><math><mi>Ω</mi></math></span>, compared to 56.7 k<span><math><mi>Ω</mi></math></span> for healthy blood cells over the entire frequency range. The standard deviation of bio-impedance (<span><math><msub><mrow><mi>Z</mi></mrow><mrow><mtext>mix</mtext></mrow></msub></math></span>) between 50 kHz and 200 kHz highlights the difference between healthy and diabetic RBCs, with 200 kHz measurements proving more reliable. To detect these bio-impedance changes, an interdigitated electrode (IDE) capacitive sensor with 40 capacitive elements was simulated. The complex bio-impedance (<span><math><msub><mrow><mi>Z</mi></mrow><mrow><mtext>mix</mtext></mrow></msub></math></span>) was measured within the 50 kHz–200 kHz frequency range, providing clear differentiation between healthy and diabetic blood cells. Simulation using Finite Element Method (FEM) through COMSOL® software supports these findings, showcasing the sensor’s efficacy in type-2 diabetes detection.</p></div>","PeriodicalId":21733,"journal":{"name":"Sensors International","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666351124000226/pdfft?md5=0226af151d2c9f55fe118223b4378c18&pid=1-s2.0-S2666351124000226-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142157556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The application of ultrasonic measurement and machine learning technique to identify flow regime in a bubble column reactor","authors":"","doi":"10.1016/j.sintl.2024.100294","DOIUrl":"10.1016/j.sintl.2024.100294","url":null,"abstract":"<div><p>This paper presents a novel technique to classify the flow regimes in bubble columns. The ultrasonic velocity profiler is employed to detect the velocity deviation and echo characteristic of bubbles rising in the column. This information is set as attribute data for the machine learning algorithm. Classification-based machine learning is utilized to classify the flow regimes: bubbly, transition, and churn turbulent, which are defined as categories of the algorithm. Several classifiers were applied in this work, such as K-nearest neighbors, Decision tree, Support vector machines, Naive bayes, and Logical regression. The experimental demonstration was conducted to verify the performance of the proposed technique. Three kinds of two-phase flow with stagnant liquid that had various viscosities were used for the experiment. The air within the superficial velocity range was injected to alter the flow regime. The flow regime classification model was set. The proposed method was applicable to identify the flow regimes. The classifiers were tested, and their accuracy was evaluated.</p></div>","PeriodicalId":21733,"journal":{"name":"Sensors International","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666351124000160/pdfft?md5=9d84de0129f6d8575eb79192d50010b6&pid=1-s2.0-S2666351124000160-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142150758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GA-mADAM-IIoT: A new lightweight threats detection in the industrial IoT via genetic algorithm with attention mechanism and LSTM on multivariate time series sensor data","authors":"","doi":"10.1016/j.sintl.2024.100297","DOIUrl":"10.1016/j.sintl.2024.100297","url":null,"abstract":"&lt;div&gt;&lt;p&gt;The Industrial Internet of Things (IIoT) is undergoing rapid development, and as a result, security threats have emerged as a significant concern. IIoT networks, while enhancing service quality, are particularly susceptible to security risks because of their intrinsic interconnectedness and the use of low-power devices. The data produced by millions of sensors in the IIoT is highly dynamic, diverse, and of massive magnitude. The risk of dangers to IoT gadgets in a nuclear plant or a petroleum refinery is significantly greater when compared to that of home appliances. Often connected to the internet, IIoT devices and systems lack robust security measures, rendering them susceptible to cyberattacks. A breach in IIoT security could result in data theft, equipment damage, or even physical harm. To mitigate these risks, IIoT systems require secure authentication and encryption protocols, regular software updates, and proactive monitoring and response capabilities. These methods' primary disadvantages are their difficulty in implementation and inability to ensure effective security. Hence, a second line of protection, such as intrusion threat detection in IIoT, is required. In this research, we propose a new threat intrusion detection model in the IIoT through a genetic algorithm with attention mechanism and modified Adam optimized LSTM (GA-mADAM-IIoT). The GA-mADAM-IIoT consists of six modules: the activity receiver, communication module (CM), attention module (AM), intrusion detection module, mitigation module, and alert module. The GA was designed for feature dimensionality and selection trained on network flow data via a Long Short-Term Memory (LSTM) network. The adaptive moment estimation (Adam) optimizer was modified in order to optimize the LSTM (mADAM-LSTM) networks. To enhance the performance of our model, the categorical cross-entropy (CCE) cost function was used to calculate the difference between the predicted output and the actual output. Additionally, the CCE cost function optimized the model's parameters to minimize the difference between predicted and actual values in terms of probability distributions. The Modified Adam (mADAM) optimization algorithm updates the weights and biases of the LSTM to minimize the cost function. Due to the limited availability of real-world datasets containing accurately labelled anomalies, particularly for industrial facilities and manufacturing facilities, we have utilized two sensor datasets derived from physical test-bed systems for water treatment: Secure Water Treatment (SWaT) and Water Distribution (WADI). In these datasets, operators have simulated attack scenarios that occur in real-world water treatment plants and have recorded these instances as the ground truth anomalies. A regularization parameter was added to the cost function to prevent LSTM from overfitting. In order to improve the model's performance, the AM integrates a succinct yet effective attention mechanism that enhances signif","PeriodicalId":21733,"journal":{"name":"Sensors International","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666351124000196/pdfft?md5=0f668b7a84f563684bd248606646127e&pid=1-s2.0-S2666351124000196-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142150759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PCR-free and minute-scale electrochemical analysis of porcine DNA adulteration via molecularly amplified DNA sandwich assay","authors":"","doi":"10.1016/j.sintl.2024.100299","DOIUrl":"10.1016/j.sintl.2024.100299","url":null,"abstract":"<div><p>The increasing incidence of meat adulteration and mislabeling poses significant challenges in terms of food safety and consumer trust. This study proposes an electrochemical DNA biosensor for detecting porcine mitochondrial DNA in tainted meat products, offering a novel approach to address the above challenges. Unlike conventional nucleic acid amplification tests that rely on polymerase chain reactions (PCRs), the proposed biosensor employs a molecularly amplified DNA strategy with DNA tracers that bind to two regions of the target DNA, creating an elongated hybridization structure with multiple redox-tagging molecules. This design catalyzes detection signals autonomously, eliminating the need for PCR amplification. One-step DNA probe immobilization using poly-adenine (poly-A) oligonucleotides significantly improves hybridization efficiency and reduces the necessity for extensive sample purification, thereby simplifying the detection process. The proposed biosensor exhibits a linear detection range of 10¹–10⁶ pM and a limit of detection (LOD) of 2.2 pM in controlled settings. Furthermore, the proposed biosensor distinguishes pork from beef in adulterated samples with a LOD of 1 % w/w. With its stability exceeding 9 weeks and a cost of less than 0.5 USD per test, the proposed biosensor offers a highly sensitive, economically viable solution with significant potential for widespread use in the meat industry and by end-users, effectively combating porcine adulteration.</p></div>","PeriodicalId":21733,"journal":{"name":"Sensors International","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666351124000214/pdfft?md5=868fc1769960450c6e946164df78a50f&pid=1-s2.0-S2666351124000214-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142167658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fabrication, catalytic activity, metal sensing ability and electrochemical evaluation of nano silver particles for supercapacitor applications","authors":"","doi":"10.1016/j.sintl.2024.100298","DOIUrl":"10.1016/j.sintl.2024.100298","url":null,"abstract":"<div><p>In this work, stable, spherical silver nanoparticles (MAgNp) were prepared via a green synthesis method using flowers of Myristica fragrans (nutmeg). This flower is abundant in phytochemicals such as saponins that can be utilized as reductants to produce silver nanoparticles. The synthesized nanoparticles were examined using a variety of physico-chemical methods, including transmission electron microscopy (TEM), Dynamic light scattering (DLS), elemental dispersive X-ray spectroscopy (EDX), powder X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), and UV–VIS spectrometer. EDX study confirmed the crystalline and face-centered cubic (FCC) structure of AgNP. The majority of particles are present with a higher percentage intensity at an average size of 58.77 nm as revealed in the TEM image, PDI was found to be 0.055. MAgNPs demonstrated perfect activity in the catalytic degradation of methylene blue dye (88 %) and para-nitrophenol (98 %), both anthropogenic pollutants. These nanoparticles were further used as plasmonic sensors to detect heavy metals like Fe(II) and Hg(II) in an aqueous solution. The minimum detection limit was found to be 0.2 mM for Hg(II) and 10  μM for Fe(II) with good linearity. The electrochemical properties of MAgNPs were studied using a carbon supercapacitor electrode coated with MAgNPs. Results from cyclic voltammetry were also determined, and they showed a high specific capacitance of 41 F/gm at 5 mV/s scan rate.</p></div>","PeriodicalId":21733,"journal":{"name":"Sensors International","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666351124000202/pdfft?md5=227c07a67bdb3411c5e8c034606070b6&pid=1-s2.0-S2666351124000202-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142167777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Wireless temperature calibration for medical centrifuge","authors":"","doi":"10.1016/j.sintl.2024.100296","DOIUrl":"10.1016/j.sintl.2024.100296","url":null,"abstract":"<div><p>Based on the complexity and metrological requirements of temperature calibration within the rotor of a medical low-temperature centrifuge, a wireless temperature calibration device for medical centrifuges has been designed and developed. The temperature probe is integrated into the centrifuge tube, and the entire device can be placed inside the rotor of the centrifuge, allowing for the measurement and analysis of the actual temperature of the test solution inside the centrifuge tube under dynamic rotation conditions. Furthermore, the force situation during dynamic calibration is analyzed and performance tested. The calibration device can consistently and dependably achieve dynamic temperature data acquisition under high-speed conditions of medical low-temperature centrifuges, facilitating dynamic temperature calibration within the centrifuge rotor and offering support for centrifuge temperature control processes.</p></div>","PeriodicalId":21733,"journal":{"name":"Sensors International","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666351124000184/pdfft?md5=082303b4d730f38f5435b6ecd2576988&pid=1-s2.0-S2666351124000184-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142117262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Synthesis of varied oleic acid-coated Fe3O4 nanoparticles using the co-precipitation technique for biosensor applications","authors":"","doi":"10.1016/j.sintl.2024.100295","DOIUrl":"10.1016/j.sintl.2024.100295","url":null,"abstract":"<div><div>This study successfully synthesized oleic acid (OA)-coated Fe₃O₄ nanoparticles using the coprecipitation method for the needs of biosensor applications, as shown through the characterization of structure and morphology using XRD and TEM. This observation used 0.75 ml of OA (Fe₃O₄-OA(0.75)) and 1.25 ml of OA (Fe₃O₄-OA(1.25). A decrease in particle size distribution from 18.55 nm to 16.30 nm was observed, which means a reduction in agglomeration and increased dispersibility. Vibrating Sample Magnetometer (VSM) observations showed that the saturation magnetization of Fe₃O₄ particles modified with OA decreased from 47.71 emu/g to 45.90 emu/g at Fe₃O₄-OA(0.75) and decreased again to 42.29 emu/g at Fe₃O₄-OA(1.25). But they all show soft ferromagnetic properties with very low coercivity, making them suitable for Giant Magnetoresistance (GMR) biosensor applications. A series of concentrations in ethanol solution were performed to evaluate the detection sensitivity of GMR for these pure and oleic acid-modified Fe₃O₄ samples. Concentrations of 2, 5, 10, 15, 25, and 35 mg/ml were integrated at 2 μL each onto the surface of the GMR chip. A decrease in sensitivity was observed due to the change in saturation. Pure Fe₃O₄ with a sensitivity of 5.07 mV (mg/ml) decreased to 4.49 mV (mg/ml) and 3.35 mV (mg/ml) after oleic acid coating. Thus, although adding a proportional amount of oleic acid can slightly decrease the saturation magnetization, it can be a valuable method for applications such as GMR biosensors that demand high dispersibility and sensitivity that remains strong.</div></div>","PeriodicalId":21733,"journal":{"name":"Sensors International","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666351124000172/pdfft?md5=27f840d98140cf4ee2740134943de20e&pid=1-s2.0-S2666351124000172-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142312633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evolution of SnO2 nanoparticles for the electrochemical sensing of dopamine including photocatalytic toxic dyes degradation","authors":"S.R. Kiran Kumar ,&nbsp;Harisha S ,&nbsp;Jalaja P ,&nbsp;B.K. Jayanna ,&nbsp;K. Yogesh Kumar ,&nbsp;M.S. Anantha","doi":"10.1016/j.sintl.2023.100278","DOIUrl":"https://doi.org/10.1016/j.sintl.2023.100278","url":null,"abstract":"<div><p>In the present study, SnO₂ nanoparticles were synthesized, and their structural features were evaluated by X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive X-ray analysis (EDX) and transmission electron microscopy (TEM) techniques. Modified electrodes (MCPE) were prepared and utilized to access the electrochemical behaviour of dopamine. This study was conducted in a phosphate buffer solution with a pH value of 7.2. The results indicate that the modified carbon paste electrode (MCPE), with a high active surface area, exhibited excellent electrochemical sensing properties and demonstrated good reproducibility and high sensitivity for the electrochemical determination of DA. Potentially interfering compounds were tested at the surface of the proposed sensor, confirming that, they did not interfere with the determination of DA under optimum condition. Additionally, the photocatalytic properties of SnO₂ were evaluated in degradation of cationic and anionic dyes. It was concluded that the higher photocatalytic activity in SnO₂ nanocomposites was attributed to their porosity and high surface area.</p></div>","PeriodicalId":21733,"journal":{"name":"Sensors International","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666351123000529/pdfft?md5=fe8198267d52c9ea6876da508bce1d60&pid=1-s2.0-S2666351123000529-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139434488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}