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The current study aims to use a facile and novel method to remove Congo red (CR) and Methyl Orange (MO) dyes from contaminated water with Maize offal biomass (MOB) and its nanocomposite with magnetic nanoparticles (MOB/MNPs). The MOB and MOB/MNPs were characterized with Fourier-transform infrared (FTIR), scanning electron microscopy (SEM), BET, XRD and point of zero charge (pHPZC). The influence of initial CR and MO levels (20–320 mg/L), adsorbent dosage (1-3 g/L), pH (3-9), co-exiting ions, temperature (25–45 °C) and time (15–180 min) was estimated. The findings demonstrated that MOB/MNPs exhibited excellent adsorption of 114.75 and 29.0 mg/g for CR and MO dyes, respectively while MOB exhibited 81.35 and 23.02 mg/g adsorption for CR and MO dyes, respectively at optimum pH-5, and dose 2 g/L. Initially, there was rapid dye removal which slowed down until equilibrium was reached. The interfering/competing ions in contaminated water and elevated temperature favored the dyes sequestration. The MOB/MNPs exhibited tremendous reusability and stability. The dyes adsorption was spontaneous, and exothermic with enhanced randomness. The adsorption effects were well explained with Freundlich model, pseudo second order and Elovich models. It is concluded that MOB/MNPs showed excellent, eco-friendly, and cost-effective potential to decontaminate the water. Nanocomposite of Maize offal biomass demonstrated higher dyes removal. FTIR, SEM, BET, XRD and pHPZC provided vital evidence for dyes adsorption. MOB/MNPs displayed excellent stability and reusability for dyes adsorption. Groundwater samples exposed a higher dyes removal. Results were validated with equilibrium and kinetic adsorption models. [ABSTRACT FROM AUTHOR]

Myzus persicae (M. persicae) is now considered a threat to agricultural crops due to economic losses. Numerous synthetic insecticides applied every year against M. persicae, are reported to be unsafe for environment, humans, and beneficial insects. Furthermore, several species of Myzus have been found to develop resistance due to over application of these insecticides. Therefore, it is required to find some novel insecticide that would be safe for the environment as well as for humans. In the current study, two major pure constituents α-pinene and β-caryophyllene were evaluated for their insecticidal potential against M. persicae using a fumigant toxicity assay. Furthermore, impact of α-pinene and β-caryophyllene on expression of five different genes, e.g., HSP 60, FPPS I, OSD, TOL and ANT responsible for reproduction, dispersion, and growth of M. persicae has also been investigated. To perform fumigant toxicity assay, five different concentrations (3.5, 4, 4.5, 5 and 6 µL L-1) of α-pinene and β-caryophyllene were prepared. Lethal concentration (LC) was calculated, and gene expression studies were executed through qRT PCR at LC30 of α-pinene and β-caryophyllene. Both constituents demonstrated excellent fumigant toxicity effects against M. persicae at all five concentrations. However, α-pinene shows significantly better results (98%) as compared to β-caryophyllene (80%) after 72 h at 6 µL L-1 of dose. The highest upregulation in expression was demonstrated at LC30 dose of α-pinene in five in three out of five genes understudy (TOL, ANT, and FPPS I). Conversely, two genes HSP 60 and OSD demonstrated downregulation at LC30 dose of β-caryophyllene. Conclusively, our results highlighted the promising insecticidal potential of both compounds α-pinene and β-caryophylleneby interfering with the reproduction and development related processes in M. persicae, allowing us to recommend the phytoconstituents under investigation as an ecofriendly alternative to synthetic insecticides. [ABSTRACT FROM AUTHOR]

Cement is a key component of concrete; its qualities impact the properties of concrete created using a particular type of cement. In Pakistan, cement brands are used for an enormous amount. As a result, the cement qualities must fulfill the standards defined by the rules. This research compares the chemical properties of Paidaar, Lucky, DG, Fauji, and Bestway cement brands. This research compares the chemical properties of Paidaar, Lucky, DG, Fauji, and Bestway cement brands. The chemical analysis of cement was used to compute the compound composition of C3S, C2S, C3A, and C4AF. It was discovered that the Al2O3 and SO3 levels in Paidaar and Fauji cement exceeded the specified limits. The presence of more SO3 causes sulphates in cement to expand. Furthermore, a study of four key components (C3S, C2S, C3A, and C4AF) revealed that Paidaar, Lucky, and Fauji cement have less C3S and more C2S, as a result, when compared to other cement brands, it has the lowest strength. When different brands' chemical compositions were compared, the Paidaar, Lucky, DG, Fauji, and Bestway cements fulfilled the standards' recommended ranges. To ensure the quality specified by the standards, Paidaar, Lucky, and Fauji cement require significant quality control during the manufacturing process. [ABSTRACT FROM AUTHOR]

The objective of the present study was to investigate the effects of role conflict and role ambiguity on employee's creativity. Exactly how role stress and various performances of individuals are related has received considerable attention, in which stress has been found to affect individual creativity. However, exactly how role stress (role conflict and role ambiguity) and employee creativity are related has seldom been examined empirically. A sample size of 100 was selected and standard questionnaires were distributes among the employees of three public sector universities in Peshawar KPK Pakistan. The conclusions drawn from the study were that role conflict and role ambiguity have negative relationship with employees creativity. Implications of the findings of this study and possible directions for future research are also discussed. [ABSTRACT FROM AUTHOR]

Assessing trends of hydrometeorological variables is necessary for climate change modeling, accurate water resources management and improved regional planning. This study investigated the seasonal, annual, maximum (max.) and mean rainfall trend using data from 1986 to 2013 collected from three selected gauge stations including Tarbela, Daggar and Saidu sharif. Similarly, the historic data (1986 to 2013) of flow of Brandu river and max. and minimum (min.) temperature of Tarbela and Saidu Sharif gauge station were analysed. To identify trends for the hydrometeorological parameters, both non-parametric and parametric (MK) tests were applied at 10% significant level. The study concludes, a mixture of increasing and decreasing trends. Annual max. rainfall exhibited an increasing trend in the study area. Similarly, total annual and mean annual rainfall for Daggar and Saidu Sharif gauge stations showed decreasing trend while Tarbela gauge station exhibited an increasing trend. Statistically significant trends were found for annual total rainfall. [ABSTRACT FROM AUTHOR]

The current study was planned to synthesize copper oxide nanoparticles (CuO NPs) using aqueous Fumaria indica (F. indica) plant extract and was calcined at 100, 300, 600 and 900 °C using Muffle furnace. The X-ray diffraction analysis reveals that crystallinity and crystallite size increase (from 14.9 to 79.29 nm) with increasing calcination temperature. The microstructure was analyzed through scanning electron microscopy, while the constituent elements were identified through energy-dispersive X-ray. The diffuse reflectance spectroscopy analysis was carried out and the optical band gap was determined through Tauc plot, which was found to decrease (from 1.82 to 1.46 eV) with increasing calcination temperature. The surface functional moieties were identified by performing Fourier transform infrared spectroscopy. Agar well diffusion process was followed to screen CuO NPs against Gram-positive bacteria and Gram-negative bacteria, where higher activity was found against Gram-negative bacteria. The antioxidant activity of CuO NPs was evaluated during the neutralization ABTs free radical, thus it can be used to reduce the damaging effects of antioxidants. [ABSTRACT FROM AUTHOR]

On-time recovery and treatment of disease is always desirable. The use of Machine learning in health-care has grown very fast to diagnosis the different kinds of diseases in the past few years. In such a diagnosis, past and real-time data are playing very crucial role in using data mining techniques. Still, we are lacking in diagnosing the emotional mental disturbance accurately in the early stages. Thus,the initial diagnosis of depression expressively stances a great problem for both,researchers and clinical professionals. We have addressed the said problem in our proposed work using Pipeline Machine Learning technique where people based on emotional stages have been effectively classified into different groups in e-healthcare. To implement Hybrid classification, a well known machine learning multi-feature hybrid classifier is used by having the emotional stimulation in form of negative or positive people. In order to improve classification, an Ensemble Learning Algorithm is used which helps in choosing the more suitable features from the available genres-emotion data on online media. Additionally, Hold out validation method has been to split the dataset for training and testing of the predictive model. Further, performance evaluation measures have been applied to check the proposed system evaluation. This study is done on Genres-Tags MovieLens dataset. The experimental results show that applied ensemble method provides optimal classification performance by choosing the best subset of features. The said results proved the excellency of the proposed system which comes from the choosing most related features selected by the Integrated Learning algorithm. Additionally, suggested approach is used to accurately and effectively diagnose the depression in its early stage. It will help in recovery and treatment of depressed people. We conclude that use of the suggested method is highly suitable in all aspects of e-healthcare for depress stimulation. [ABSTRACT FROM AUTHOR]

This study focuses on the application of laser-induced breakdown spectroscopy (LIBS) to determine lead and chromium in pristine aloe vera and aloe vera based beauty soaps using the second harmonic (532 nm) of a Q-switched Nd:YAG laser. The optimal experimental conditions were evaluated to improve the sensitivity of the detection system by a parametric dependence study. The atomic transition lines at 405.7 nm and 425.4 nm were used as the analytical lines to determine lead and chromium, respectively. The LIBS system was calibrated for these toxic elements and the samples under analysis included 8.00–15.00 ppm by mass of lead and 5.00–12.00 ppm by mass of chromium, which are far above the safe permissible levels of these elements (i.e., 0.50 ppm for Pb and 1.00 ppm for Cr). The quantitative results were checked before and after normalization with the background and better outcomes were obtained when the spectrum was normalized with the background. The LIBS results were compared to the outcomes of selected samples by a standard analytical method, inductively coupled plasma – optical emission spectroscopy (ICP-OES). Both outcomes were in outstanding conformity implying the reliability of the LIBS measurements. The current study is attractive for the general evaluation of human health and specifically for the analysis of aloe vera based cosmetics. [ABSTRACT FROM AUTHOR]

Water pollution is one of the major global challenges today. Water bodies are contaminated by the heavy release of waste effluents of textile industries, which includes intensively colored dye pollutants. Herein, a ternary nanocomposite of bismuth copper selenide with small particle size and ternary metal selenide (TMS)‐chitosan microspheres (TMS‐CM) of the spherical porous surface were successfully synthesized. SEM, XRD, EDX, FTIR, and UV/Vis spectrophotometry analysis revealed the structural and morphological characteristics of the newly synthesized nanocomposites. SEM imaging showed the average diameter of TMS nanoparticle to be 33 nm. The crystal size was calculated as 6.33 nm and crystalline structure as orthorhombic using XRD findings. EDX confirmed the presence of Bi, Cu, and Se in the ternary nanocomposite. The bandgap of 1.8 eV was calculated from Tauc's plot for the TMS nanocomposite. SEM confirmed the successful synthesis of spherical TMS‐CM microspheres of porous surface morphology with an average size of 885.6 μm. The presence of chitosan microspheres in the synthesis of TMS nanocomposite was identified by FTIR spectral analysis. Furthermore, highly efficient photocatalytic degradation (up to 95.4%) of ARS was achieved within 180 min at pH 4.0 using 0.5 g of TMS‐CM in sunlight. The first‐order kinetic model fitted well to the photocatalytic decontamination of ARS using TMS‐CM with a rate constant of 6.1x10−2 min−1. The TMS‐CM gave attractive results and high efficiency in photocatalytic degradation of ARS dye after reusing and regeneration of up to seven successive cycles. The newly synthesized nanophotocatalyst could be efficiently used for the decontamination of dye polluted water from textile industries. [ABSTRACT FROM AUTHOR]

The effective detection of breast cancer is particularly essential for recovery and treatment in the initial phases. The existing methods are not successfully diagnosis breast cancer in the initial phases. Thus the initial recognition of breast cancer is expressively a great challenge for health professionals and scientists. To resolve the problem of initial stages recognition of breast cancer, we recommended a machine learning based diagnosis method which will excellently classify the malignant and benign persons. In the designing of our method machine learning model support vector machine has been applied to classify the malignant and benign persons. To increase the classification performances of the method, we used Minimal Redundancy Maximal Relevance and Chi-square algorithms to choose more appropriate features from the breast cancer dataset. The training/testing splitting technique is used for training and testing of the model. Additionally, the performance of the model has been evaluated by performance assessment metrics. The experimental results demonstrated that the classifier support vector machine obtained best classification performance on the selected subset of features as selected by Minimal Redundancy Maximal Relevance feature selection algorithm. The performances of support vector machine on selected features by Chi square feature selection algorithm are low as compared to Minimal Redundancy Maximal Relevance algorithm. From experimental results analysis, we determined that the integrated system based on Minimal Redundancy Maximal Relevance and support vector machine performances are high due to the selection of more suitable features and obtained 99.71% accuracy. According to McNemar's statistical test the proposed method is more significant then existing methods. Thus, we recommend that the proposed diagnosis method for effective detection of breast cancer. [ABSTRACT FROM AUTHOR]

This work is aimed at exploring the efficiency of a novel H2O2 modified activated carbon (PA-AC-HO) prepared from used tea leaves (UTLs) for the removal of toxic cationic dye, malachite green (MG) from aqueous systems. The surface properties of PA-AC-HO were analyzed by FTIR spectroscopy, scanning electron microscopy (SEM), BET surface area (SBET), Boehm's titration and point of zero charge (pHPZC), thermogravimetric (TG/DTA) and X-rays diffraction (XRD) analysis. Results showed that PA-AC-HO has sufficient number of acidic functional groups and pHPZC value lies in the acidic region. The SEM study confirmed that the adsorbent external surface is highly porous with BET surface area of 1,097.68 (m² g-1) and total pore volume of 0.83 cm3 g-1. Proximate-ultimate analysis showed high carbon and oxygen content of PA-AC-HO with amorphous nature. The adsorption characteristics of PA-AC-HO for the uptake of MG were studied by batch method. The dye uptake capacity and rate was found to increase with increasing contact time, dye initial concentrations and solution pH, but showed a decreasing trend with increasing salt ionic strength. Kinetic investigation revealed that adsorption of MG followed pseudo-second order model while the equilibrium isotherm data fitted the Langmuir and Temkin models well and maximum adsorption capacity was found to be 454.55 mg g-1. Thermodynamic investigation showed spontaneous and endothermic nature of the adsorption. Regeneration of dye loaded adsorbent was carried out by five consecutive cycles which showed good regeneration capacity. [ABSTRACT FROM AUTHOR]

Mesoporous Al-doped NiO ultralong nanowires with better uniformity, dispersity and well-defined morphologies were synthesized by a simple surfactant based hydrothermal treatment of aqueous solution of Al(NO3)3, NiCl2 and NaC2O4 in the presence of ethylene glycol and polyethylene glycol through continuous open air heating at 500 °C. The sensing performances of the gas sensor's based on bare and Al-doped NiO nanowires had been investigated towards ethanol, methanol, acetone, xylene, toluene and benzene. The results specified that the 3.2 at% Al-doped NiO nanowires display better gas sensitivity characteristics as compare to that of undoped, 1.6 at%, 2.1 at% and 4.3 at% Al-doped NiO nanowires. It has been investigated that the sensitivity features were upgraded with an increment on Al concentration into the crystallites based on NiO nanowires. The assimilation of Al3+ ions within NiO crystals modifies the carrier concentration by inducing changes in the chemisorbed and deficient oxygen of NiO nanowires. Hence, the incorporation of Al3+ into NiO nanowires would be a capable way for scheming and devising significant gas sensors. [ABSTRACT FROM AUTHOR]

Water decontamination from chromium (Cr) is of prime importance because of its carcinogenic nature. The sample of activated carbon was characterized by surface area analyzer, SEM/EDX, TGA, FTIR and PZC. This study was focused on adsorption of hexavalent chromium from the aqueous phase onto activated carbon. Both the temperature and pH had a positive effect on the chromate uptake by activated carbon. The chromate uptake at different pH values followed the trend: pH 2 > pH 3 > pH 5 > pH 7 > pH 8. The sorption maxima at pH 2 was explained on the basis of electrostatic attraction between the negatively charged chromate anions and positively charged surface of the activated carbon. Different models were tested to access the sorption maxima and to probe into the chromate adsorption mechanism. The thermodynamic parameters suggested that heat is needed to shift the hexavalent chromium from solution to the solid surface. It was concluded that the anion exchange sorption was involved in removing the chromate anion from the aqueous system into the surface of activated carbon. [ABSTRACT FROM AUTHOR]

Study and research of Bt (Bacillus thuringiensis) transgenic plants have opened new ways to combat insect pests. Over the decades, however, insect pests, especially the Lepidopteran, have developed tolerance against Bt delta-endotoxins. Such issues can be addressed through the development of novel toxins with greater toxicity and affinity against a broad range of insect receptors. In this computational study, functional domains of Bacillus thuringiensis crystal delta-endotoxin (Cry1Ac) insecticidal protein and vegetative insecticidal protein (Vip3Aa) have been fused to develop a broad-range Vip3Aa-Cry1Ac fusion protein. Cry1Ac and Vip3Aa are non-homologous insecticidal proteins possessing receptors against different targets within the midgut of insects. The insecticidal proteins were fused to broaden the insecticidal activity. Molecular docking analysis of the fusion protein against aminopeptidase-N (APN) and cadherin receptors of five Lepidopteran insects (Agrotis ipsilon, Helicoverpa armigera, Pectinophora gossypiella, Spodoptera exigua, and Spodoptera litura) revealed that the Ser290, Ser293, Leu337, Thr340, and Arg437 residues of the fusion protein are involved in the interaction with insect receptors. The Helicoverpa armigera cadherin receptor, however, showed no interaction, which might be due to either loss or burial of interactive residues inside the fusion protein. These findings revealed that the Vip3Aa-Cry1Ac fusion protein has a strong affinity against Lepidopteran insect receptors and hence has a potential to be an efficient broad-range insecticidal protein. [ABSTRACT FROM AUTHOR]

Biosorpt ion of Mn (II) from aqueous solut ion by P. Ostreatus was invest igated at different concentrations, pH and temperature. The close agreement between the experimental and theoretical biosorption capacity confirmed that Pseudo 2nd order equat ion is best fitted to the present experimental data. The biosorption capacity of P. Ost reatus was observed to be dependent upon the pH and temperature of adsorpt ion system. The values of biosorpt ion maxima (Xm) and binding energy constant (Kb) were observed to decrease with rise in temperature in the range of 298 - 323K. The negative values of ΔG and ΔH showed the process of Mn (II) biosorpt ion onto P. Ost reatus is spontaneous and exothermic respectively. Similarly, the values of isosteric heat of biosorption (ΔD) were decreased with increase in surface coverage (e) which indicated that the surface of the P. Ostreatus is energet ically heterogeneous in nature. [ABSTRACT FROM AUTHOR]

The ever increasing demand of security has resulted in wide use of Biometric systems. Despite overcoming the traditional verification problems, the unimodal systems suffer from various challenges like intra class variation, noise in the sensor data etc, affecting the system performance. These problems are effectively handled by multimodal systems. In this paper, we present multimodal approach for palm- and fingerprints by feature level and score level fusions (sum and product rules). The proposed multi-modal systems are tested on a developed database consisting of 440 palm- and fingerprints each of 55 individuals. In feature level fusion, directional energy-based feature vectors of palm- and fingerprint identifiers are combined to form joint feature vector that is subsequently used to identify the individual using a distance classifier. In score level fusion, the matching scores of individual classifiers are fused by sum and product rules. Receiver operating characteristics curves are formed for unimodal and multimodal systems. Equal Error Rate (EER) of 0.538% for feature level fusion shows best performance compared to score level fusion of 0.6141 and 0.5482% of sum and product rules, respectively. Multimodal systems, however, significantly outperform unimodal palm- and fingerprints identifiers with EER of 2.822 and 2.553%, respectively. [ABSTRACT FROM AUTHOR]