The contamination of water with herbicides poses a serious threat to the environment as a result of their widespread use in the agricultural field. Herein, mesoporous silica nanoparticles (MSNs) were ...synthesised and grafted with poly(2-(tert-butylamino)ethyl methacrylate) brushes (MSN-PTBAEMA) using the SI-ATRP technique on the inner and outer surface of the solid particles. The porous structure of the MSNs along with thepH-responsive feature of the polymer brush allowed it to efficiently remove the targeted herbicide, 2,4,5-trichlorophenoxyacetic acid (TCA), with steady extraction efficiency over a wide pH range of 3-7. A maximum adsorption capacity of 290 mg/g was achieved, which was much higher than other adsorbents for the removal of organic pollutants. The adsorption process followed the Freundlich isotherm model, which indicates that a multilayer adsorption mechanism occurred on the surface of the adsorbent. The kinetic study results show that the adsorption of TCA occurred in two-stage adsorption kinetics with the intraparticle diffusion process being the rate-determining step in the adsorption process. Furthermore, the adsorption kinetics were found to fit better to the pseudosecond-order model than the pseudofirst-order model. The present study proved that MSN-PTBAEMA could be potentially applied for the effective removal of herbicides from aqueous environments.
The development of diagnostic devices based on memetic molecular recognitions are becoming highly promising due to high specificity, sensitivity, stability, and low-cost comparing to natural ...molecular recognition. During the last decade, molecular imprinted polymers (MIPs) and aptamer have shown dramatic enhancement in the molecular recognition characteristics for bio(chemical) sensing applications. Recently, MIP-aptamer, as an emerging hybrid recognition element, merged the advantages of the both recognition components. This dual recognition-based sensor has shown improved properties and desirable features, such as high sensitivity, low limit of detection, high stability under harsh environmental conditions, high binding affinity, and superior selectivity. Hybrid MIP-aptamer as dual recognition element, was used in the real sample analysis, such as detection of proteins, neurotransmitters, environmental pollutants, biogenic compounds, small ions, explosives, virus detections and pharmaceuticals. This review focuses on a comprehensive overview of the preparation strategies of various MIP-aptamer recognition elements, mechanism of formation of MIP-aptamer, and detection of various target molecules in different matrices.
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•Review the most important properties of MIP-aptamer as dual recognition elements in biochemical sensing.•Strategies for preparation of MIP-aptamer sensors.•Comparison of the figures of merits of MIP-aptamer biosensor to the MIP and/or aptamer biosensors.•Challenges that confront this new dual recognition elements-based biosensors.
Abstract
Cesium tin chloride (CsSnCl
3
) is a potential and competitive absorber material for lead-free perovskite solar cells (PSCs). The full potential of CsSnCl
3
not yet been realized owing to ...the possible challenges of defect-free device fabrication, non-optimized alignment of the electron transport layer (ETL), hole transport layer (HTL), and the favorable device configuration. In this work, we proposed several CsSnCl
3
-based solar cell (SC) configurations using one dimensional solar cell capacitance simulator (SCAPS-1D) with different competent ETLs like indium–gallium–zinc–oxide (IGZO), tin-dioxide (SnO
2
), tungsten disulfide (WS
2
), ceric dioxide (CeO
2
), titanium dioxide (TiO
2
), zinc oxide (ZnO), C
60
, PCBM, and HTLs of cuprous oxide (Cu
2
O), cupric oxide (CuO), nickel oxide (NiO), vanadium oxide (V
2
O
5
), copper iodide (CuI), CuSCN, CuSbS
2
, Spiro MeOTAD, CBTS, CFTS, P3HT, PEDOT:PSS. Simulation results revealed that ZnO, TiO
2
, IGZO, WS
2
, PCBM, and C
60
ETLs-based halide perovskites with ITO/ETLs/CsSnCl
3
/CBTS/Au heterostructure exhibited outstanding photoconversion efficiency retaining nearest photovoltaic parameters values among 96 different configurations. Further, for the six best-performing configurations, the effect of the CsSnCl
3
absorber and ETL thickness, series and shunt resistance, working temperature, impact of capacitance, Mott–Schottky, generation and recombination rate, current–voltage properties, and quantum efficiency on performance were assessed. We found that ETLs like TiO
2
, ZnO, and IGZO, with CBTS HTL can act as outstanding materials for the fabrication of CsSnCl
3
-based high efficiency (
η
≥ 22%) heterojunction SCs with ITO/ETL/CsSnCl
3
/CBTS/Au structure. The simulation results obtained by the SCAPS-1D for the best six CsSnCl
3
-perovskites SC configurations were compared by the wxAMPS (widget provided analysis of microelectronic and photonic structures) tool for further validation. Furthermore, the structural, optical and electronic properties along with electron charge density, and Fermi surface of the CsSnCl
3
perovskite absorber layer were computed and analyzed using first-principle calculations based on density functional theory. Thus, this in-depth simulation paves a constructive research avenue to fabricate cost-effective, high-efficiency, and lead-free CsSnCl
3
perovskite-based high-performance SCs for a lead-free green and pollution-free environment.
Medical image segmentation is a crucial step in Computer-Aided Diagnosis systems, where accurate segmentation is vital for perfect disease diagnoses. This paper proposes a multilevel thresholding ...technique for 2D and 3D medical image segmentation using Otsu and Kapur's entropy methods as fitness functions to determine the optimum threshold values. The proposed algorithm applies the hybridization concept between the recent Coronavirus Optimization Algorithm (COVIDOA) and Harris Hawks Optimization Algorithm (HHOA) to benefit from both algorithms' strengths and overcome their limitations. The improved performance of the proposed algorithm over COVIDOA and HHOA algorithms is demonstrated by solving 5 test problems from IEEE CEC 2019 benchmark problems. Medical image segmentation is tested using two groups of images, including 2D medical images and volumetric (3D) medical images, to demonstrate its superior performance. The utilized test images are from different modalities such as Magnetic Resonance Imaging (MRI), Computed Tomography (CT), and X-ray images. The proposed algorithm is compared with seven well-known metaheuristic algorithms, where the performance is evaluated using four different metrics, including the best fitness values, Peak Signal to Noise Ratio (PSNR), Structural Similarity Index (SSIM), and Normalized Correlation Coefficient (NCC). The experimental results demonstrate the superior performance of the proposed algorithm in terms of convergence to the global optimum and making a good balance between exploration and exploitation properties. Moreover, the quality of the segmented images using the proposed algorithm at different threshold levels is better than the other methods according to PSNR, SSIM, and NCC values. Additionally, the Wilcoxon rank-sum test is conducted to prove the statistical significance of the proposed algorithm.
•We proposed a novel hybrid COVIDOA-HHO optimization algorithm.•The proposed algorithm is used in the multilevel segmentation of medical images.•The proposed algorithm is tested using Six IEEE CEC 2019 benchmark problems.•The COVIDOA-HHO outperformed the recent well-known metaheuristics algorithms.•Two datasets are used for testing, including 2D and 3D medical images.•Best fitness value, PSNR, SSIM, and NCC are used to evaluate the performance.
Studies conducted over the past eight years in Latin America (LA) have continued to produce new knowledge regarding health impacts of arsenic (As) in drinking water. We conducted a systematic review ...of 92 peer-reviewed English articles published between 2011 and 2018 to expand our understanding on these health effects. Majority of the LA studies on As have been conducted in Chile and Mexico. Additional data have emerged from As-exposed populations in Argentina, Bolivia, Brazil, Colombia, Ecuador, and Uruguay. The present review has documented recent data on the biomarkers of As exposure, genetic susceptibility and genotoxicity, and risk assessment to further characterize the health effects and exposed populations. Some recent findings on the associations of As with bladder and lung cancers, reproductive outcomes, and declined cognitive performance have been consistent with what we reported in our previous systematic review article. We have found highly convincing evidence of in utero As exposure as a significant risk factor for several health outcomes, particularly for bladder cancer, even at moderate level. New data have emerged regarding the associations of As with breast and laryngeal cancers as well as type 2 diabetes. We observed early life As exposure to be associated with kidney injury, carotid intima-media thickness, and various pulmonary outcomes in children. Other childhood effects such as low birth weight, low gestational age, anemia, increased apoptosis, and decreased cognitive functions were also reported. Studies identified genetic variants of As methyltransferase that could determine susceptibility to As related health outcomes. Arsenic-induced DNA damage and alteration of gene and protein expression have also been reported. While the scope of research is still vast, the substantial work done on As exposure and its health effects in LA will help direct further large-scale studies for more comprehensive knowledge and plan appropriate mitigation strategies.
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•Arsenic (As) induced breast & laryngeal cancers - first reported in Latin America.•Associations found between As exposure and cardiopulmonary outcomes and diabetes.•Genetic susceptibility and polymorphisms were found crucial in As related effects.•New evidence on bladder and lung cancers in As-exposed populations has emerged.
Pakistan is fifth among high burden countries for tuberculosis. A steady increase is seen in extrapulmonary tuberculosis (EPTB), which now accounts for 20% of all notified TB cases. There is very ...limited information on the epidemiology of EPTB. This study was performed with the aim to describe the demographic characteristics, clinical manifestations and treatment outcomes of EPTB patients in Pakistan.
We performed descriptive analysis on routinely collected data for cohorts of TB patients registered nationwide in 2016 at health facilities selected using stratified convenient sampling.
Altogether 54092 TB including 15790 (29.2%) EPTB cases were registered in 2016 at 50 study sites. The median age was 24 years for EPTB and 30 years for PTB patients. The crude prevalence of EPTB in females was 30.5% (95%CI; 29.9-31.0) compared to 27.9% (95%CI; 27.3-28.4) in males. The likelihood of having EPTB (OR), was 1.1 times greater for females, 2.0 times for children, and 3.3 times for residents of provinces in the North-West. The most common forms of EPTB were pleural (29.6%), lymphatic (22.7%) and abdominal TB (21.0%). Pleural TB was the most common clinical manifestation in adults (34.2%) and abdominal TB in children (38.4%). An increase in the prevalence of pleural and osteoarticular and decline in lymphatic and abdominal TB was observed with advancing age. Diversity in demography and clinical manifestations were noted between provinces. The treatment success rate for all type EPTB was significantly high compared to bacteriology confirmed PTB with the exception of EPTB affecting CNS with a high mortality rate.
The study provides an insight into demography, clinical manifestations and treatment outcomes of EPTB. Further studies are needed to explain significant diversities observed between provinces, specific risk factors and challenges concerning EPTB management.
This study presents the oxygenic photogranule (OPG) process, a light-driven process for wastewater treatment, developed based on photogranulation of filamentous cyanobacteria, nonphototrophic ...bacteria, and microalgae. Unlike other biogranular processes requiring airlift or upflow-based mixing, the OPG process was operated in stirred-tank reactors without aeration. Reactors were seeded with hydrostatically grown photogranules and operated in a sequencing-batch mode for five months to treat wastewater. The new reactor biomass propagated with progression of photogranulation under periodic light/dark cycles. Due to effective biomass separation from water, the system was operated with short settling time (10 min) with effective decoupling of hydraulic and solids retention times (0.75 d vs 21–42 d). During quasi-steady state, the diameter of the OPGs ranged between 0.1 and 4.5 mm. The reactors produced effluents with average total chemical oxygen demand less than 30 mg/L. Nitrogen removal (28–71%) was achieved by bioassimilation and nitrification/denitrification pathways. Oxygen needed for the oxidation of organic matter and nitrification was produced by OPGs at a rate of 12.6 ± 2.4 mg O2/g biomass-h. The OPG system presents a new biogranule process, which can potentially use simple mixing and natural light to treat wastewater.
Melanoma is a type of skin cancer with a high mortality rate. The different types of skin lesions result in an inaccurate diagnosis due to their high similarity. Accurate classification of the skin ...lesions in their early stages enables dermatologists to treat the patients and save their lives. This paper proposes a model for a highly accurate classification of skin lesions. The proposed model utilized the transfer learning and pre-trained model with GoogleNet. The model parameters are used as initial values, and then these parameters will be modified through training. The latest well-known public challenge dataset, ISIC 2019, is used to test the ability of the proposed model to classify different kinds of skin lesions. The proposed model successfully classified the eight different classes of skin lesions, namely, melanoma, melanocytic nevus, basal cell carcinoma, actinic keratosis, benign keratosis, dermatofibroma, vascular lesion, and Squamous cell carcinoma. The achieved classification accuracy, sensitivity, specificity, and precision percentages are 94.92%, 79.8%, 97%, and 80.36%, respectively. The proposed model can detect images that do not belong to any one of the eight classes where these images are classified as unknown images.
In this study, combined DFT, SCAPS-1D, and wxAMPS frameworks are used to investigate the optimized designs of Cs2BiAgI6 double perovskite-based solar cells. First-principles calculations are employed ...to investigate the structural stability, optical responses, and electronic contribution of the constituent elements in Cs2BiAgI6 absorber material, where SCAPS-1D and wxAMPS simulators are used to scrutinize different configurations of Cs2BiAgI6 solar cells. Here, PCBM, ZnO, TiO2, C60, IGZO, SnO2, WS2, and CeO2 are used as ETL, and Cu2O, CuSCN, CuSbS2, NiO, P3HT, PEDOT:PSS, spiro-MeOTAD, CuI, CuO, V2O5, CBTS, CFTS are used as HTL, and Au is used as a back contact. About ninety-six combinations of Cs2BiAgI6-based solar cell structures are investigated, in which eight sets of solar cell structures are identified as the most efficient structures. Besides, holistic investigation on the effect of different factors such as the thickness of different layers, series and shunt resistances, temperature, capacitance, Mott–Schottky and generation–recombination rates, and J–V (current–voltage density) and QE (quantum efficiency) characteristics is performed. The results show CBTS as the best HTL for Cs2BiAgI6 with all eight ETLs used in this work, resulting in a power conversion efficiency (PCE) of 19.99%, 21.55%, 21.59%, 17.47%, 20.42%, 21.52%, 14.44%, 21.43% with PCBM, TiO2, ZnO, C60, IGZO, SnO2, CeO2, WS2, respectively. The proposed strategy may pave the way for further design optimization of lead-free double perovskite solar cells.
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