Utilization of Fly Ash as Low-Cost Adsorbent for the Treatment of Industrial Dyes Effluents- A Comparative Study

ABSTRACT Coal and sugar manufacturing power generation plants are engender million tons of fly ash as waste per annum. It creates serious disposal and environmental problems. There is no alternative usage for its utilization in industries. In this regard, efforts were taken to utilize fly ash waste in the treatment of highly toxic and polluted dyes effluents. In this advanced research, characterization of fly ash properties, preparation of adsorbent, utilization for the optimum reduction of dyes effluent pollutants, determination of adsorptive capacity and study of isotherm adsorption models were accomplished. Treatment efficiency was optimized using these ashes as adsorbent at optimum dose. Sugarcane bagasse fly ash (SBFA) could reduce the higher concentration of COD (51%), color (70%), turbidity (71%) and TSS (96%) from dyes effluent. All used fly ashes could reduce higher concentration of effluent pollutants at 4 g dosing. SBFA has high porosity, which resulted in high adsorption of effluent pollutants as compared to other fly ashes. The adsorptive capacity of all used fly ash was declined on increasing adsorbent dosing. Langmuir and freundlich isotherm models were evaluated for the determination of chemical adsorption behavior of fly ashes

A deep learning-based model for plant lesion segmentation, subtype identification, and survival probability estimation

Plants are the primary source of food for world’s population. Diseases in plants can cause yield loss, which can be mitigated by continual monitoring. Monitoring plant diseases manually is difficult and prone to errors. Using computer vision and artificial intelligence (AI) for the early identification of plant illnesses can prevent the negative consequences of diseases at the very beginning and overcome the limitations of continuous manual monitoring. The research focuses on the development of an automatic system capable of performing the segmentation of leaf lesions and the detection of disease without requiring human intervention. To get lesion region segmentation, we propose a context-aware 3D Convolutional Neural Network (CNN) model based on CANet architecture that considers the ambiguity of plant lesion placement in the plant leaf image subregions. A Deep CNN is employed to recognize the subtype of leaf lesion using the segmented lesion area. Finally, the plant’s survival is predicted using a hybrid method combining CNN and Linear Regression. To evaluate the efficacy and effectiveness of our proposed plant disease detection scheme and survival prediction, we utilized the Plant Village Benchmark Dataset, which is composed of several photos of plant leaves affected by a certain disease. Using the DICE and IoU matrices, the segmentation model performance for plant leaf lesion segmentation is evaluated. The proposed lesion segmentation model achieved an average accuracy of 92% with an IoU of 90%. In comparison, the lesion subtype recognition model achieves accuracies of 91.11%, 93.01 and 99.04 for pepper, potato and tomato plants. The higher accuracy of the proposed model indicates that it can be utilized for real-time disease detection in unmanned aerial vehicles and offline to offer crop health updates and reduce the risk of low yield

Synthesis of new 2-{2,3-dihydro-1,4-benzodioxin-6- yl[(4-methylphenyl) sulfonyl]amino}-N-(un/substituted-phenyl) acetamides as α-glucosidase and acetylcholinesterase inhibitors and their in silico study

The aim of the present research work was to investigate the enzyme inhibitory potential of some new sulfonamides having benzodioxane and acetamide moieties. The synthesis was started by the reaction of N-2,3-dihydrobenzo[1,4]-dioxin-6-amine (1) with 4-methylbenzenesulfonyl chloride (2) in the presence of 10% aqueous Na2CO3 to yield N-(2,3-dihydrobenzo[1,4]-dioxin-6-yl)-4-methylbenzenesulfonamide (3), which was then reacted with 2-bromo-N-(un/substituted-phenyl)acetamides (6a-l) in DMF and lithium hydride as a base to afford various 2-{2,3-dihydro-1,4-benzodioxin-6-yl[(4-methylphenyl)sulfonyl] amino}-N-(un/substituted-phenyl)acetamides (7a-l). All the synthesized compounds were characterized by their IR and 1 H-NMR spectral data along with CHN analysis data. The enzyme inhibitory activities of these compounds were tested against -glucosidase and acetylcholinesterase (AChE). Most of the compounds exhibited substantial inhibitory activity against yeast -glucosidase and weak against AChE. The in silico molecular docking results were also consistent with in vitro enzyme inhibition data

An effective deep learning approach for the classification of Bacteriosis in peach leave

Bacteriosis is one of the most prevalent and deadly infections that affect peach crops globally. Timely detection of Bacteriosis disease is essential for lowering pesticide use and preventing crop loss. It takes time and effort to distinguish and detect Bacteriosis or a short hole in a peach leaf. In this paper, we proposed a novel LightWeight (WLNet) Convolutional Neural Network (CNN) model based on Visual Geometry Group (VGG-19) for detecting and classifying images into Bacteriosis and healthy images. Profound knowledge of the proposed model is utilized to detect Bacteriosis in peach leaf images. First, a dataset is developed which consists of 10000 images: 4500 are Bacteriosis and 5500 are healthy images. Second, images are preprocessed using different steps to prepare them for the identification of Bacteriosis and healthy leaves. These preprocessing steps include image resizing, noise removal, image enhancement, background removal, and augmentation techniques, which enhance the performance of leaves classification and help to achieve a decent result. Finally, the proposed LWNet model is trained for leaf classification. The proposed model is compared with four different CNN models: LeNet, Alexnet, VGG-16, and the simple VGG-19 model. The proposed model obtains an accuracy of 99%, which is higher than LeNet, Alexnet, VGG-16, and the simple VGG-19 model. The achieved results indicate that the proposed model is more effective for the detection of Bacteriosis in peach leaf images, in comparison with the existing models

An Experimental Channel Capacity Analysis of Cooperative Networks Using Universal Software Radio Peripheral (USRP)

Cooperative communication (CC) is one of the best solutions to overcome channel fading and to improve channel capacity. However, most of the researchers evaluate its performance based on mathematical modeling or by simulations. These approaches are often unable to successfully capture many real-world radio signal propagation problems. Hardware based wireless communication test-bed provides reliable and accurate measurements, which are not attainable through other means. This research work investigates experimental performance analysis of CC over direct communication (DC) in the lab environment. The experimental setup is built using Universal Software Radio Peripheral (USRP) and Laboratory Virtual Instrument Engineering Workbench (LabVIEW). A text message is transmitted by using Phase Shift Keying (PSK) modulation schemes. The setup uses amplify and forward (AF) relaying mode and two time slot transmission protocols. The maximum ratio combining (MRC) technique is used for combining SNR at the receiver. Channel capacity analysis is performed in order to evaluate the performance of CC over DC with and without obstacle. Moreover, optimal position of the relay is also analyzed by varying the position of the relay. Extensive experiments are carried out in the lab environment to evaluate the performance of the system for different hardware setups. The results reveal that cooperative communication attains significant improvement in terms of channel capacity of the system

Synthesis and in silico study of 2-furyl(4-{4-[(substituted)sulfonyl]benzyl}-1-piperazinyl)methanone derivatives as suitable therapeutic agents

In the study presented here, a new series of 2-furyl(4-{4-[(substituted)sulfonyl]benzyl}-1-piperazinyl)methanone derivatives was targeted. The synthesis was initiated by the treatment of different secondary amines (1a-h) with 4-bromomethylbenzenesulfonyl chloride (2) to obtain various 1-{[4-(bromomethyl)phenyl]sulfonyl}amines (3a-h). 2-Furyl(1-piperazinyl)methanone (2-furoyl-1-piperazine; 4) was then dissolved in acetonitrile, with the addition of K2CO3, and the mixture was refluxed for activation. This activated molecule was further treated with equi-molar amounts of 3a-h to form targeted 2-furyl(4-{4-[(substituted)sulfonyl]benzyl}-1-piperazinyl)methanone derivatives (5a-h) in the same reaction set up. The structure confirmation of all the synthesized compounds was carried out by EI-MS, IR and 1H-NMR spectral analysis. The compounds showed good enzyme inhibitory activity. Compound 5h showed excellent inhibitory effect against acetyl- and butyrylcholinesterase with respective IC50 values of 2.91±0.001 and 4.35±0.004 μM, compared to eserine, a reference standard with IC50 values of 0.04±0.0001 and 0.85±0.001 μM, respectively, against these enzymes. All synthesized molecules were active against almost all Gram-positive and Gram-negative bacterial strains tested. The cytotoxicity of the molecules was also checked to determine their utility as possible therapeutic agents

Synthesis and in silico study of 2-furyl(4-{4-[(substituted)sulfonyl]benzyl}-1-piperazinyl)methanone derivatives as suitable therapeutic agents

Abstract In the study presented here, a new series of 2-furyl(4-{4-[(substituted)sulfonyl]benzyl}-1-piperazinyl)methanone derivatives was targeted. The synthesis was initiated by the treatment of different secondary amines (1a-h) with 4-bromomethylbenzenesulfonyl chloride (2) to obtain various 1-{[4-(bromomethyl)phenyl]sulfonyl}amines (3a-h). 2-Furyl(1-piperazinyl)methanone (2-furoyl-1-piperazine; 4) was then dissolved in acetonitrile, with the addition of K2CO3, and the mixture was refluxed for activation. This activated molecule was further treated with equi-molar amounts of 3a-h to form targeted 2-furyl(4-{4-[(substituted)sulfonyl]benzyl}-1-piperazinyl)methanone derivatives (5a-h) in the same reaction set up. The structure confirmation of all the synthesized compounds was carried out by EI-MS, IR and 1H-NMR spectral analysis. The compounds showed good enzyme inhibitory activity. Compound 5h showed excellent inhibitory effect against acetyl- and butyrylcholinesterase with respective IC50 values of 2.91±0.001 and 4.35±0.004 μM, compared to eserine, a reference standard with IC50 values of 0.04±0.0001 and 0.85±0.001 μM, respectively, against these enzymes. All synthesized molecules were active against almost all Gram-positive and Gram-negative bacterial strains tested. The cytotoxicity of the molecules was also checked to determine their utility as possible therapeutic agents

Assessment of Coagulant Synergy for the Depollution of Binder Emulsion Plant Effluent

Binder emulsion plant effluent is a source of intense pollution when discharged into the environment without proper degree of treatment due to its strong color as well as higher total suspended solids (TSS) and chemical oxygen demand (COD) contents. An empirical study was conducted to optimize the effect of the coagulants used for the removal of Color, Turbidity, TSS, and COD from binder emulsion effluent. The coagulants, used with and without the induction of Powdered Activated Carbon (PAC) to enhance the decrease in pollution concentration, included Ferrous Sulfate, Ferric Chloride, Alum and Lime. Ferric Chloride used in combination with PAC produced a synergistic effect in terms of effluent depollution and transpired into efficient removal of effluent COD (83%), Color (98%), Turbidity (97%) and TSS (96%). Induction of PAC with all the coagulants combined proved highly effective as well in decreasing the effluent COD, color, Turbidity and TSS by 91%, 99%, 99% and 97% respectively. In a combined process of coagulation and adsorption, combination of ferric chloride and PAC gave effective results in terms of pollutants removal by around 90% as compared to combination of PAC with other coagulants, yielding removal percentages of lower than 50%

Coagulation-Adsorption Hybrid Process for the Treatment of Dyes and Pigments Wastewater

The study aimed to improve the effectiveness of dyes and pigments wastewater treatment. Hybrid system of adsorption and coagulation was applied for the reduction of COD, color, turbidity and TSS. Activated carbon adsorbent was prepared from a waste of sugar industry boiler. It was processed through physicochemical treatment with sulfuric acid following grinding, sieving, washing and drying unit operations. Combined wastewater of dyes and pigments manufacturing plant was treated with a hybrid process of coagulation and adsorption. FeCl 3, FeSO 4and Alum coagulants were tested individually and found them less effective. It was revealed that FeCl 3 coagulation, adsorption and hybrid process reduced COD (41, 51 and 54%), Color (67, 70 and 89%), turbidity (69, 71 and 90%) and TSS (82, 93 and 97%) respectively. Combination of FeCl3 -SBFA (Sugarcane Bagasse Fly Ash) proved 90% efficient in removal than coagulation as an individual process. 4g adsorbent dose was optimized for this hybrid proces

Trans-Esterification of Poultry Skin Fat to Produce Biodiesel

Chicken skin and its fat are sources of solid waste that are usually not utilized and add solid pollution. This research work deals with the production of useful biodiesel from utilizing the waste chicken (fat and its skins). Waste chicken fat and its skins (sourced from local shops of Hyderabad, Sindh, Pakistan) were extracted and trans-estrification was made. The product of trans-estrification was fatty acid methyl esters (FAME) commonly known as biodiesel. Sodium Hydroxide (NaOH) was used as catalyst and glycerol was obtained as a by-product. The FAME produced was tested for six parameters namely calorific value, cloud point, pour point, flash point, density and viscosity when compared to ASTM E2515-11 standard values. The results of this experiment showed that the calorific value, cloud point, pour point, flash point, density and viscosity values of FAME produced from chicken skin and its fat were close to that of petroleum derived diese