654 research outputs found
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Functionalized fluorescent nanomaterials for sensing pollutants in the environment: A critical review
No full textQuantitation of environmental pollutants has gained momentum due to its widespread requirement in the fields of clinical research, occupational hygiene, public health, and societal welfare. The use of functionalized fluorescent nanomaterials (FFNMs: e.g., metal nanoparticles, semiconductor quantum dots, carbon dots, nanotubes, and nanocrystals) has opened a new avenue for creating simple, selective, and non-invasive real-time analysis, as they can satisfy the growing demand for rapid and cost-effective quantitation. Here, we discuss novel strategies for the qualitative and quantitative analysis of a variety of organic and inorganic environmental pollutants by detecting changes in photo-physical or optical properties (e.g., fluorescence, absorbance, and color) of FFNMs used as probes. Particularly, we emphasize potential approaches for the synthesis and characterization of FFNMs and their underlying interactions with environmental pollutants. The simplification of design and enhancement of specificity towards target analytes should be pursued further to upgrade their real-world applicability in diverse fields
Effect of Mn2+ and Cu2+ co-doping on structural and luminescent properties of ZnS nanoparticles
No full textUndoped and transition metal (Cu, Mn, Cu:Mn) doped ZnS nanoparticles are synthesized by chemical co-precipitation method via an aqueous synthesis route. Synthesized samples are characterized by various techniques for their structural and optical properties. Crystallite size obtained from X-Ray Diffraction (XRD) is 1.68, 1.87, 1.50, 1.42 nm for undoped, Cu, Mn, Cu:Mn doped ZnS nanoparticles. The XRD, High Resolution Transmission Electron Microscopy, and Selected Area Electron Diffraction confirm the evolution of stable hexagonal phase of ZnS nanoparticles at low temperature. Energy Dispersive Spectroscopy confirms the doping of nanoparticles. Blue shift in UV absorbance shows the increase in optical bandgap with decrease in particle size. The Photoluminescence studies exhibit blue, yellow and red emission in visible region. Surface functionalization of nanoparticles is confirmed from Fourier Transform Infra Red spectroscopy. The present samples are tunable in wider range of emission and are prospective candidates for biological labels due to their fluorescent properties
Organic-inorganic hybrid matrix for electrochemical biosensing of tyrosine
No full textThe manuscript presents synthesis and application of organic-inorganic hybrid matrix, consisting of polypyrrole (PPy) and gold nanoparticles (AuNPs). The polypyrrole acts as conducting matrix and gold nanostructures play role of electro-catalysts. The composite of PPy-AuNPs was electrochemically synthesized on screen printed electrodes in single step and was characterized thoroughly using analytical techniques. The composite was used as matrix for immobilization of tyrosinase enzyme for tyrosine and catechin biosensing. The electrochemical measurements were performed using cyclic voltammetry (CV) and amperometry. For tyrosine, the composite based biosensor showed dynamic linearity from 10 to 100 nM, having sensitivity of 1.0 × 10−2 μAcm−2/nM, and LOD of 0.3 nM. For catechin, the dynamic linearity range was from 1 to 20 nM. The study showed that the biosensor exhibited more sensitivity towards tyrosine estimation as compared to catechin, which can be due to their structural difference. The biosensor was also used for sensing tyrosine and catechin in real samples and the study showed motivating results
A pilot study for segmentation of pharyngeal and sino-nasal airway subregions by automatic contour initialization
No full textPurpose
The objective of the present study is to put forward a novel automatic segmentation algorithm to segment pharyngeal and sino-nasal airway subregions on 3D CBCT imaging datasets.
Methods
A fully automatic segmentation of sino-nasal and pharyngeal airway subregions was implemented in MATLAB programing environment. The novelty of the algorithm is automatic initialization of contours in upper airway subregions. The algorithm is based on boundary definitions of the human anatomy along with shape constraints with an automatic initialization of contours to develop a complete algorithm which has a potential to enhance utility at clinical level. Post-initialization; five segmentation techniques: Chan-Vese level set (CVL), localized Chan-Vese level set (LCVL), Bhattacharya distance level set (BDL), Grow Cut (GC), and Sparse Field method (SFM) were used to test the robustness of automatic initialization.
Results
Precision and F-score were found to be greater than 80% for all the regions with all five segmentation methods. High precision and low recall were observed with BDL and GC techniques indicating an under segmentation. Low precision and high recall values were observed with CVL and SFM methods indicating an over segmentation. A Larger F-score value was observed with SFM method for all the subregions. Minimum F-score value was observed for naso-ethmoidal and sphenoidal air sinus region, whereas a maximum F-score was observed in maxillary air sinuses region. The contour initialization was more accurate for maxillary air sinuses region in comparison with sphenoidal and naso-ethmoid regions.
Conclusion
The overall F-score was found to be greater than 80% for all the airway subregions using five segmentation techniques, indicating accurate contour initialization. Robustness of the algorithm needs to be further tested on severely deformed cases and on cases with different races and ethnicity for it to have global acceptance in Katradental radKatraiology workflow
Craniofacial and upper airway morphology in adult obstructive sleep apnea patients: A systematic review and meta-analysis of cephalometric studies
No full textObstructive sleep apnea (OSA) is one of the common sleep breathing disorders in adults, characterised by frequent episodes of upper airway collapse during sleep. Craniofacial disharmony is an important risk factor for OSA. Overnight polysomnography (PSG) study is considered to be the most reliable confirmatory investigation for OSA diagnosis, whereas the precise localization of site of obstruction to the airflow cannot be detected. Identifying the cause of OSA in a particular ethnic population/individual subject helps to understand the etiological factors and effective management of OSA. The objective of the meta-analysis is to elucidate altered craniofacial anatomy on lateral cephalograms in adult subjects with established OSA. Significant weighted mean difference with insignificant heterogeneity was found for the following parameters: anterior lower facial height (ALFH: 2.48 mm), position of hyoid bone (Go-H: 5.45 mm, S–H: 6.89 mm, GoGn-H: 11.84°, GoGn-H: 7.22 mm, N–S–H: 2.14°), and pharyngeal airway space (PNS-Phw: −1.55 mm, pharyngeal space: −495.74 mm2 and oro-pharyngeal area: −151.15 mm2). Significant weighted mean difference with significant heterogeneity was found for the following parameters: cranial base (SN: −2.25 mm, S–N–Ba: −1.45°), position and length of mandible (SNB: −1.49° and Go-Me: −5.66 mm) respectively, maxillary length (ANS-PNS: −1.76 mm), tongue area (T: 366.51 mm2), soft palate area (UV: 125.02 mm2), and upper airway length (UAL: 5.39 mm). This meta-analysis supports the relationship between craniofacial disharmony and obstructive sleep apnea. There is a strong evidence for reduced pharyngeal airway space, inferiorly placed hyoid bone and increased anterior facial heights in adult OSA patients compared to control subjects. The cephalometric analysis provides insight into anatomical basis of the etiology of OSA that can influence making a choice of appropriate therapy
A “Turn-On” thiol functionalized fluorescent carbon quantum dot based chemosensory system for arsenite detection
No full textCarbon quantum dots (CQDs) have emerged out as promising fluorescent probes for hazardous heavy metals detection in recent past. In this study, water soluble CQDs were synthesized by facile microwave pyrolysis of citric acid & cysteamine, and functionalized with ditheritheritol to impart thiol functionalities at surface for selective detection of toxic arsenite in water. Microscopic analysis reveals that the synthesized CQDs are of uniform size (diameter ∼5 nm) and confirmed to have surface SH groups by FT-IR. The functionalized probe is then demonstrated for arsenite detection in water by “Turn-On” read out mechanism, which reduces the possibility of false positive signals associated with “turn off’ probes reported earlier. The blue luminescent functionalized CQDs exhibit increase in fluorescence intensity on arsenite addition in 5–100 ppb wide detection range. The probe can be used for sensitive detection of arsenite in environmental water to a theoretical detection limit (3s) of 0.086 ppb (R2 = 0.9547) with good reproducibility at 2.6% relative standard deviation. The presented reliable, sensitive, rapid fCQDs probe demonstrated to exhibit high selectivity towards arsenite and exemplified for real water samples as well. The analytical performance of the presented probe is comparable to existing organic & semiconductor based optical probes
Characterization of Chickpea Flour by Near Infrared Spectroscopy and Chemometrics
No full textNear infrared (NIR) spectrometry was used for the rapid characterization of quality parameters in desi chickpea flour (besan). Partial least square regression, principal component regression (PCR), interval partial least squares (iPLS), and synergy interval partial least squares (siPLS) were used to determine the protein, carbohydrate, fat, and moisture concentrations of besan. Spectra were collected in reflectance mode using a lab-built predispersive filter-based instrument from 700 to 2500 nm. The quality parameters were also determined by standard methods. The root mean square error (RMSE) for the calibration and validation sets was used to evaluate the performance of the models. The correlation coefficients for moisture, fat, protein, and carbohydrates in chickpea flour exceeded 0.96 using PLS and PCR models using the full spectral range. Wavelengths from 2100 to 2345 nm had the lowest RMSE for quality parameters by iPLS. The error was further decreased by 0.41, 0.1, and 1.1% for carbohydrates, fats, and proteins by siPLS. The NIR spectral regions yielding the lowest RMSE of prediction were 1620–2345 nm for carbohydrates, 1180–1590 nm and 1860–2094 nm for fat, and 1700–2345 nm for proteins. The study shows that chickpea flour quality parameters were accurately determined using the optimized wavelengths
Electrochemical aspects of photocatalysis: Au@FeS2 nanocomposite for removal of industrial pollutant
No full textA wide range of endeavors have been dedicated to building up an impetus in the field of catalysis to enhance the removal of toxic contaminants from water. This study characterizes an efficient photocatalyst for water treatment technique. Herein, the synthesis of a photocatalyst Au@FeS2 for the degradation of textile dye NOVACRON Red Huntsman (NRH) has been demonstrated. Photocatalysis under visible light with varying concentrations of catalyst have been explored along with the degradation kinetics to determine the synergistic impact on degradation technique. The Au@FeS2 exhibits excellent photocatalytic activity and good reusability under visible light irradiation. The efficiency of Au@FeS2 (1 g L−1) in the degradation of the textile dye NRH (1 mg L−1) is found to be 96.02% in just 60 minutes, which is considerably higher than that of FeS2 (1 g L−1) (95.63% in 120 minutes). The electrochemical performance also supports the enhanced photocatalytic activity of Au@FeS2. The photocatalytic and electrochemical activity of Au@FeS2 offers an innovative platform for environmental remediation applications
Leukocyte Classification using Adaptive Neuro-Fuzzy Inference System in Microscopic Blood Images
No full textMicroscopic pathology is still a meticulous and biased task for hematologist, which leads to the misclassification of cells and vagueness prediction of abnormal cells due to variability in the morphological structure of leukocytes. Therefore, to enhance the detection precision and diminishing the time factor, an automatic classification system for leukocytes has been proposed. In routine clinical practice, expert hematologists observed that the nucleus plays a crucial role in the identification of the blood disorders. Accordingly, in this work, the localization of leukocyte nucleus is performed by using Chan–Vase level-set method for the design of a classification framework that differentiates between four classes of the leukocytes, i.e., eosinophils, polymorphs, monocytes and lymphocytes based on the nucleus. A dataset consisting of 162 leukocyte microscopic images is used. The images in the dataset are classified on the basis of texture, shape and color features. The feature selection method based on the linguistic hedge is applied on evaluated feature space of 92. The selected features are fed to an adaptive neuro-fuzzy classifier for the classification. The proposed framework obtained an accuracy of 98.7% after applying the adaptive neuro-fuzzy classification on selected 46 informative features. The correlation of best features and data extorted from the different microscopic images may yield a dramatic increase in diagnostic consistency in clinical pathology. The results obtained by utilization of selected optimal features and adaptive neuro-fuzzy classification system indicate that it can be routinely used in clinical environment for differential diagnosis between different classes of leukocytes
Quantum-sized nanomaterials for solar cell applications
No full textTo date, the development of clean and sustainable energy sources has been a central focal point of research, supporting the worldwide rising demand for energy along with associated environmental concerns. The abundance of solar energy on the surface of the earth and its popular appeal makes it a promising candidate to comply with long-term energy demands. In this article, we provide a comprehensive review on different generations of solar cell based on the technological and economic aspects. The focus is on nanomaterial-based solar cells such as quantum dot sensitized solar cells (QDSSCs), a new PV mechanism that offers a new pathway for controlling energy flow. Over the past few years, a significant improvement has been achieved in the energy conversion efficiency (ECE) of QDSSCs (e.g., from 1% to beyond 11%). As such, they are a very promising alternative to conventional crystalline and thin film PV technologies due to their low cost, easy fabrication, and high performance. This review highlights the progress of QDSSCs along with future scope of innovative graphene structures, e.g., graphene-semiconductor nanomaterial (G-SNM), graphene-carbon nanotubes (G-CNT), and graphene-metal nanomaterial (G-MNM) hybrids in PV cells. In addition to graphene, we discuss other 2D materials that have remarkable optoelectronic properties for PV devices. The ECE of green QDSSCs (~11.61% certified) is now approaching that of dye-sensitized solar cells (~13%) through the technical advancement of many counterparts (e.g., photo-electrodes, sensitizers, electrolytes, and counter electrodes). Therefore, QDSSCs exhibit sufficient potential for future research focusing on the development of highly efficient solar cells