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This study reports the development of a fast and facile route for the synthesis of novel TiO2-CeO2 nanocomposite film using sol-gel spin coating method with the mixture of commercial CeO2, titanium-iso-propoxide (TTIP) and aqueous ammonia. Solutions of TTIP in ethanol were mixed with CeO2 nanoparticles to form a mixed sol-gel. The sol containing Ti...
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... microliters (mL) of 1:1 M mixture of urease and GLDH (1.0 mg/mL, in PB, 50 mM and pH 7.0) was immobilized onto a TiO 2 -CeO 2 nanocomposite film by the Physisorption method. The biochemical reaction using the mixed enzyme system is shown below. The general schematic of enzyme immobilized over the electrode surface is shown below (Fig. ...
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... effect of the scan rate on the electrochemical performance of the sensors was evaluated by conducting the CV experiments at various scan rates between 10 and 300 mV s-1. The scan rate vs. oxidation current graph is shown in Fig. 14. It was found that the oxidation current of Urs-GLDH/ TiO 2 -CeO 2 /ITO sensors measured at 0.8 V increased linearly with the increasing scan rate as shown in Fig. 15, demonstrating that the oxidation of H 2 O 2 on the surface of the sensor is a surface controlled electrochemical ...
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... presentation of the constructed biosensors was assessed utilizing chronoamperometric technique directed in 0.01 M PBS at the pH of 7.4. The CV aftereffects of the sensors were considered so as to decide the ideal working potential. As appeared in Fig. 14, the oxidation of H 2 O 2 began at the capability of 0.3 V, and a further increment in the connected voltage yielded higher oxidation current. In spite of the fact that the expansion in the connected voltage brought about a noteworthy increment in the reaction current up to 0.6 V, further increment in the voltage did not influence the ...
Citations
... Assessment via CV revealed the enhanced sensitivity and expanded linear range of the nanocomposite film. These findings underscore the innovative properties of the combined enzyme and TiO2−CeO2 material for uric acid assessment in real blood, particularly in the context of arthritic conditions [82]. ...
Nanostructured metal oxides (NMOs) provide electrical properties such as high surface−to−volume ratio, reaction activity, and good adsorption strength. Furthermore, they serve as a conductive substrate for the immobilization of biomolecules, exhibiting notable biological activity. Capitalizing on these characteristics, they find utility in the development of various electrochemical biosensing devices, elevating the sensitivity and selectivity of such diagnostic platforms. In this review, different types of NMOs, including zinc oxide (ZnO), titanium dioxide (TiO2), iron (II, III) oxide (Fe3O4), nickel oxide (NiO), and copper oxide (CuO); their synthesis methods; and how they can be integrated into biosensors used for medical diagnosis are examined. It also includes a detailed table for the last 10 years covering the morphologies, analysis techniques, analytes, and analytical performances of electrochemical biosensors developed for medical diagnosis.
... Jian Shang and colleagues used crystallisation techniques to elucidate the structural underpinnings of receptor recognition by SARS-CoV-2, specifically focusing on the RBD-ACE2 complex. 18,22,23 The detection of SARS-CoV-2 in people is now accomplished by the use of enzyme-linked immunosorbent assays (ELISA) and realtime polymerase chain reaction (RT-PCR) techniques for testing IgG antibodies. In an ELISA test, rather than detecting the virus itself, the test looks for associated antibodies in the patient's blood serum. ...
By means of a dielectric modulation method, this research offers the first ever 2D analytical model for the surface potential of a dual material gate Ferroelectric-tunnel-field effect transistor (DMG-Fe-TFET) device used in an enzyme-free biosensor. Compared to a device with a single material gate, the sensitivity of a device with a gate made of two distinct metals (M1-M2) is improved by an increase in tunnelling width at the secondary tunnelling junction. This model accounts for the change in surface potential caused by varying the value, position, and fill factor of the target biomolecules. Several distinct device architectures are used to enhance the efficiency of the envisaged Fe-TFET in the nanoscale range. The DMG-Fe-TFET is one of many cutting-edge FET topologies that can reduce the impact of short-channel effects because of its adaptability. The surface potential can be expressed by computing the two-dimensional Poisson's equation using the parabolic-potential approach. The critical voltage is determined by using the minimal surface potential model. The percent change in the threshold voltage is used to determine the sensitivity of the model. Researchers have investigated how the dimensions of the Nano cavity and other parts of the device affect its sensitivity.
... Understanding the origins, modes of transmission, and pathogenicity-altering mutations of SARS-CoV-2 necessitates molecular classification of full-length SARS-CoV-2 sequences. Genetic sequence data investigation also has significant allegations for the development of new medicines and vaccines [4][5][6]. The COVID-19 pandemic saw the emergence and fast spread of novel SARS-CoV-2 subtypes. ...
... cDNA synthesis requires RNA for use as a template. When the Fig. 1 General schematic of COVID-19 with spike protein and nucleocapsid protein [6] Content courtesy of Springer Nature, terms of use apply. Rights reserved. ...
The rapid mutation that is taking place in the genome of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may have as an unintended consequence a growth in the charges of both transmission and mortality. It is shown how to use a vertical tunnel field-effect transistor (VTFET) biosensor to detect SARS-CoV-2 spike proteins in clinical samples. These proteins are discovered in the virus’s capsids. Measurements of the modification in the current drain have been capable of examining the readiness of the currently proposed detector. As a stand-in for the biomolecules that have internal hybridization nanogaps, the dielectric coefficient analogue of the viral proteins is utilised here. The fact that the suggested detector has a high sensitivity (on a scale ranging from 0 to 115) displays that the device has the potential to be used as a premium sensing instrument. DNA density of charge sensitivity studies is conducted to search for changes in the virus that could affect its capacity to disseminate and infect humans. The genotypes of SARS-CoV-2 are disclosed. Christian Medical College in Vellore, Tamil Nadu, India, analysed samples of SARS-CoV-2 and is capable of sequencing their entire genomes and examining mutation patterns and clade distribution. Two hundred and fifty distinct mutations were discovered among the 600 sequences that were investigated. One hundred fifty missense mutations, eighty synonymous mutations, fifteen mutations in noncoding regions, and five deletions make up the 250 unique mutations found in this sequencing data, which is essential for understanding genomic diversity. Finally, a variety of previously reported FET-based biosensors are linked to the suggested detector and its analysis of genetic mutation.
Graphical Abstract
... Moreover, this approach can help to mitigate concerns related to electronic waste by reducing the amount of material used in sensor production and facilitating their easy disposal. In the end, the creation of adaptable and affordable humidity sensors has the potential to greatly raise the standard of living and encourage environmental sustainability across a range of sectors and applications [8]. ...
The detection of humidity is crucial for various applications in industry, healthcare, and the environment. To meet the needs of many of these applications, humidity sensors must be flexible, disposable, and easily fabricated. This article introduces a cost-effective and flexible humidity sensor created on a paper substrate, using graphene-polypyrrole-carbon black ink. The sensor shows excellent sensing capabilities, with a resistance change of approximately 12.2 Ω/%RH when exposed to humidity ranging from 23%RH to 92.7%RH. Additionally, the sensor is highly flexible, stable, and repeatable for over 50 cycles, with a short response/recovery time of approximately 5 s/7 s for respiration rate monitoring. Furthermore, the sensor demonstrates good reproducibility, with minor variations of approximately ± 1 Ω/%RH. The performance of the produced humidity sensor is assessed for monitoring humidity in a spatial setting as well as monitoring soil moisture. As a result, these findings indicate that the proposed humidity sensor is resilient enough to be used in wearable and flexible electronic devices.
... Because the achieved parameters are estimated based on approximation, the sensitivity and model parameters may vary from patient to patient. [9]. ...
... The tuning of cascade strategy has two stages in its structure. Initially, the secondary loop tuning initiated to accomplish the optimum performance of the controller [ ( ) ( ) ] and predicted data need to verify and analyze based on the primary process (BP), and the principal function as defined in [Equation (9)] and primary controller tuning [ ( ) ( )] is [Equation (10)] tuned based on primary loop prediction. The controller scheme designed with fuzzy logic and the tuning has achieved using regularized tuning methods. ...
This paper presents a cascade methodology towards the control of blood pressure for perioperative patients with a diabetic continuum. Recent clinical research confirms that blood pressure and diabetes have possible overlap on their substantial and may occur together as per their disease etiology. Postoperative stress and hasty diabetic variation will make pressure distinctions, leading to cardiovascular catastrophe, hypo, hyperinsulinemia, and osmotic diuresis. To avoid anomalies, blood pressure and diabetes need to monitor simultaneously. Based on the distinctions, blood pressure has to control the optimal drug delivery system. This proposal adopts a cascade control modelling and control scheme strategy adopted with two different parameters in control. The control loop is overseen and eliminates the disturbances generated by diabetic variations, and the primary control loop supervises and controls drug delivery. In particular, the difference of the control is to produce automated correction of the drug SNP (sodium nitroprusside) infusion to maintain the Mean Arterial pressure (MAP) as prescribed. The proposed advisory process is based on FLC (Fuzzy logic) controller to optimize appropriate and optimal drug delivery. The cascade control studies' simulations demonstrated, that the proposed approach provides proper estimating drug delivery and regulates hypertension as per the recommended levels.
... The topic of nanotechnology has attracted numerous researchers to employ them in a range of applications as the use of nanoscale materials becomes more widespread. The recovery of metals from ewaste at the nanoscale has been the subject of several scientific articles [101,102] . For example, a study [103] reported a low-temperature technique in which WPCBs were ball-milled into nanosized particles with improving downstream component recovery. ...
... However, they have limitations in solar cell and self-cleaning applications due to the metastability of hydrogenated amorphous silicon under light and the weak infrared light absorption of hydrogenated microcrystalline silicon [167]. To avert this, expensive substrates such as indium tin oxides [168], fluorine tin oxide [169], and different types of fabrics are now frequently used. The use of cotton fabrics as a substrate also posed some challenges due to the hydrophilicity and porosity of cotton fabrics. ...
This paper reviewed the deposition of thin films of TiO2 for self-cleaning applications deposited using the spin coater. The overwhelming global demand for electricity pushes power producers to develop substitute energy sources. Renewable energy sources such as solar, wind, tidal, geothermal, and hydroelectric are now considered to create alternative power sources. The most abundant form on earth is solar energy, converted to electrical energy using a solar panel. Regrettably, solar panels attract contaminants once exposed to the atmosphere, causing their efficiency to drop. Self-cleaning is one of the researched technologies to help maintain clean photovoltaic surfaces. Titanium dioxide (TiO2) is among the materials studied for self-cleaning, and the spin-coating method offers great promise. This paper presented the background and working principle of the spin coater, precautions to be taken with the spin-coating process, and the merits and demerits of the process. The paper highlighted the self-cleaning mechanism and the spin-coating method to create self-cleaning TiO2 thin films for application on several surfaces, including the solar panel. Commonly used self-cleaning materials were also reviewed, including materials used to dope or create TiO2 composite for better self-cleaning capability. Effects of process parameters, available substrates, surfactants, solvents, and stabilizing agents on the final TiO2 thin film performance and recent innovative efforts to improve the spin-coating process and the self-cleaning abilities of TiO2 are reviewed. This will contribute to the body of knowledge on spin-coating techniques, self-cleaning thin films, and TiO2.
... An SNN (spiking neural networks) model has been presented in to build a timely crop yield forecast. In this work, historical crop yield data and spatial accumulation of blocks of MODIS-NDVI (Moderate Resolution Imaging Spectroradiometer-normalized difference vegetation index) 250-m resolution data was employed to the examination [18][19][20]. The SNNs promising techniques were utilized in remote sensing for analysis, spatiotemporal data model, and crop prediction. ...
Big data analysis is the process of gathering, managing and analyzing a large volume of data to determine patterns and other valuable information. Agricultural data can be a significant area of big data applications. The big data analysis for agricultural data can comprise the various data from both internal systems and outside sources like weather data, soil data, and crop data. Though big data analysis has led to advances in different industries, it has not yet been extensively used in agriculture. Several machine learning techniques are developed to cluster the data for the prediction of crop yield. However, it has low accuracy and low quality of the clustering. To improve clustering accuracy with less complexity, a Proximity Likelihood Maximization Data Clustering (PLMDC) technique is developed for both sparse and densely distributed agricultural big data to enhance the accuracy of crop yield prediction for farmers. In this process, unnecessary data is cleansed from the sparse and dense based agricultural data using a logical linear regression model. After that, the presented clustering method is executed depending on the similarity and weight-based Manhattan distance. The genetic algorithm (GA) is applied with a good fitness function to select the features from the clustered data. Finally, the decision support system is computed by the A-FP growth algorithm to predict the crop yields according to their selected features such as weather features and crop features. The results of the proposed PLMDC technique are better in case of clustering accuracy of both spare and densely distributed data with minimum time and space complexity. Based on the results observations, the PLMDC technique is more efficient than the existing methods.
... The proposed method is the combination of SVD and ICA that processes the data to identify and remove irrelevant data. The conducted experiments confirm that the method proposed in this article is better than other methods [10][11][12][13]. ...
... Here the noise terminology is an angle ( ). The transformation matrix in Eq. (3) is used to rotate the point in two-dimensional discrete angle spaces [11]. The angle of rotation is measured in clockwise, and the values of X and Y coordinates are affected by that transformation. ...
... Rotation operation is applied more than once until all the sensitive attributes are transformed to preserve privacy. For every set of attributes, the rotation angle will be selected and rotated [11,12]. The rotation matrix R in 3D transformation is represented as follows: ...
Recent advancements in data mining have given rise to a new channel of research, coined as privacy-preserving data mining (PPDM). PPDM technology allows us to derive useful information from vast amounts of data while protecting privacy of individual records. This paper proposed a methodology based on the machine learning algorithm called singular value decomposition (SVD) and 3D rotation data perturbation (RDP) for preserving privacy of data. Decomposition and dimensionality reduction helps to eliminate sensitive information, and perturbed matrix is generated. The original and perturbed data are classified using different classifiers, and the performance is measured in terms of accuracy rate. Accuracy is the degree of correlation between the absolute observation and the actual observations. Experimental results revealed that the proposed scheme outperforms by achieving excellent accuracy for matrices of different sizes.
... Titania and ceria are naturally occurring oxides, that are cheap and easy to produce in a high amount and they are very liable to form stable and homogeneous mixtures with extraordinary redox [31] and interface [32] behavior that can be utilized mainly in (photo)catalytic applications [33][34][35] but also in electrochemical sensors and solar cells [36] and biosensors [37]. Numerous methods including sol-gel [38], solvothermal [39], hydrothermal [40] and co-precipitation [36,40], to name the most popular, were used to prepare TiO 2 /CeO 2 composites with diverse morphologies and for various applications. ...
TiO2/CeO2 nanocomposites were prepared by simple refluxing of peroxo titanium and cerium complexes in water at ambient air and they were used for degradation of several organophosphorus compounds (OPC). The combination of high surface reactivity of ceria with photoactivity of titania led to i) rapid reactive adsorption of bis-p-nitrophenyl phosphate (BNPP) forming p-nitrophenyl phosphate (NP) and ii) subsequent photo-induced degradation of both BNPP and NP. The composites were also three and four times more efficient for rapid degradation of chemical warfare agents (CWAs) soman and VX in nonane compared to bare ceria and titania, respectively. The strong interaction of Ti with Ce within the composites led to the formation of Ce³⁺ and Ti<4+ states, reduction of titania crystallite size, change of acid-base and surface properties and synergetic effects that are all responsible for highly improved degradation efficiency of these bifunctional nanocomposites with considerable potential of application for abatement of various toxic compounds.
