Comparative Responses of Three Pomegranates (Punica Granatum L.) Varieties to Salinity

During 2011 and 2012 seasons, three pomegranate cultivars Manfalouty, Wonderfull and Nab–Elgamal. were subjected to saline ground water at concentration (1.8 and 6.0 dSm-1). The trees about seven years old grown at 2.5 x 3.5 m apart in sandy clay loam soil under Sohag environmental conditions. Results revealed that irrigation with saline water (6dSm-1), increased salt accumulation in leaves. On the other hand, the higher significant reduction was observed in growth; flowering and yield with highly fruit cracking in relative to 1.8 dSm-1. Total Sugar and acidity percentages did not alter significantly with varying Saline irrigation. The studied varieties were affected differently by salt-stress, Manfalouty, Wonderfull, and Nab-Elgamal in descending order in response to salinity

Bayesian Convolution for Stochastic Epidemic Model

Dengue Hemorrhagic Fever (DHF) is a tropical disease that always attacks densely populated urban communities. Some factors, such as environment, climate and mobility, have contributed to the spread of the disease. The Aedes aegypti mosquito is an agent of dengue virus in humans, and by inhibiting its life cycle it can reduce the spread of the dengue disease. Therefore, it is necessary to involve the dynamics of mosquito's life cycle in a model in order to obtain a reli- able risk map for intervention. The aim of this study is to develop a stochastic convolution susceptible, infective, recovered-susceptible, infective (SIR-SI) mod- el describing the dynamics of the relationship between humans and Aedes aegypti mosquitoes. This model involves temporal trend and uncertainty factors for both local and global heterogeneity. Bayesian approach was applied for the parameter estimation of the model. It has an intrinsic recurrent logic for Bayesian analysis by including prior distributions. We developed a numerical computation and carry out simulations in WinBUGS, an open-source software package to perform Mar- kov chain Monte Carlo (MCMC) method for Bayesian models, for the complex systems of convolution SIR-SI model. We considered the monthly DHF data of the 2016–2018 periods from 10 districts in Kendari-Indonesia for the application as well as the validation of the developed model. The estimated parameters were updated through to Bayesian MCMC. The parameter estimation process reached convergence (or fulfilled the Markov chain properties) after 50000 burn-in and 10000 iterations. The deviance was obtained at 453.7, which is smaller compared to those in previous models. The districts of Wua-Wua and Kadia were consistent as high-risk areas of DHF. These two districts were considered to have a signifi- cant contribution to the fluctuation of DHF cases

SutteARIMA: A Novel Method for Forecasting the Infant Mortality Rate in Indonesia

This study focuses on the novel forecasting method (SutteARIMA) and its application in predicting Infant Mortality Rate data in Indonesia. It undertakes a comparison of the most popular and widely used four forecasting methods: ARIMA, Neural Networks Time Series (NNAR), Holt-Winters, and SutteARIMA. The data used were obtained from the website of the World Bank. The data consisted of the annual infant mortality rate (per 1000 live births) from 1991 to 2019. To determine a suitable and best method for predicting Infant Mortality rate, the forecasting results of these four methods were compared based on the mean absolute percentage error (MAPE) and mean squared error (MSE). The results of the study showed that the accuracy level of SutteARIMA method (MAPE: 0.83% and MSE: 0.046) in predicting Infant Mortality rate in Indonesia was smaller than the other three forecasting methods, specifically the ARIMA (0.2.2) with a MAPE of 1.21% and a MSE of 0.146; the NNAR with a MAPE of 7.95% and a MSE of 3.90; and the Holt-Winters with a MAPE of 1.03% and a MSE: of 0.083

Promising photocatalytic and antimicrobial activity of novel capsaicin coated cobalt ferrite nanocatalyst

Abstract In this study, CoFe2O4 nanoparticles were prepared by the co-precipitation method then surface modified with Capsaicin (Capsicum annuum ssp.). The virgin CoFe2O4 NPs and Capsaicin-coated CoFe2O4 NPs (CPCF NPs) were characterized by XRD, FTIR, SEM, and TEM. The antimicrobial potential and photocatalytic degradation efficiencies of the prepared samples via Fuchsine basic (FB) were investigated. The results revealed that CoFe2O4 NPs have spherical shapes and their diameter varied from 18.0 to 30.0 nm with an average particle size of 25.0 nm. Antimicrobial activity was tested on Gram-positive (S. aureusATCC 52923) and Gram-negative (E. coli ATCC 52922) by disk diffusion and broth dilution methods to determine the zone of inhibition (ZOI) and minimum inhibitory concentration (MIC), respectively. UV-assisted photocatalytic degradation of FB was examined. Various parameters affecting the photocatalytic efficiency such as pH, initial concentration of FB, and dose of nanocatalyst were studied. The in-vitro ZOI and MIC results verified that CPCF NPs were more active upon Gram-Positive S. aureus ATCC 52923 (23.0 mm ZOI and 0.625 μg/ml MIC) than Gram-Negative E. coli ATCC 52922 (17.0 mm ZOI and 1.250 μg/ml MIC). Results obtained from the photocatalytic activity indicated that the maximum FB removal achieving 94.6% in equilibrium was observed using 20.0 mg of CPCF NPS at pH 9.0. The synthesized CPCF NPs were effective in the removal of FB and also as potent antimicrobial agent against both Gram-positive and Gram-negative bacteria with potential medical and environmental applications

Enhanced photocatalytic and antibacterial activities of novel Ag-HA bioceramic nanocatalyst for waste-water treatment

Abstract Hydroxyapatite (HA), the most common bioceramic material, offers attractive properties as a catalyst support. Highly crystalline mono-dispersed silver doped hydroxyapatite (Ag-HA) nanorods of 60 nm length was developed via hydrothermal processing. Silver dopant offered enhanced chemisorption for crystal violet (CV) contaminant. Silver was found to intensify negative charge on the catalyst surface; in this regard enhanced chemisorption of positively charged contaminants was accomplished. Silver dopant experienced decrease in the binding energy of valence electron for oxygen, calcium, and phosphorous using X-ray photoelectron spectroscopy XPS/ESCA; this finding could promote electron–hole generation and light absorption. Removal efficiency of Ag-HA nanocomposite for CV reached 88% after the synergistic effect with 1.0 mM H2O2; silver dopant could initiate H2O2 cleavage and intensify the release of active ȮH radicals. Whereas HA suffers from lack of microbial resistance; Ag-HA nanocomposite demonstrated high activity against Gram-positive (S. aureus) bacteria with zone of inhibition (ZOI) mm value of 18.0 mm, and high biofilm inhibition of 91.1%. Ag-HA nanocompsite experienced distinctive characerisitcs for utilization as green bioceramic photocatalyst for wastewater treatment

Carbon-dot-loaded CoxNi1−xFe2O4; x = 0.9/SiO2/TiO2 nanocomposite with enhanced photocatalytic and antimicrobial potential: An engineered nanocomposite for wastewater treatment

Abstract Water scarcity is now a serious global issue resulting from population growth, water decrease, and pollution. Traditional wastewater treatment plants are insufficient and cannot meet the basic standards of water quality at reasonable cost or processing time. In this paper we report the preparation, characterization and multiple applications of an efficient photocatalytic nanocomposite (CoxNi1−xFe2O4; x = 0.9/SiO2/TiO2/C-dots) synthesized by a layer-by-layer method. Then, the photocatalytic capabilities of the synthesized nanocomposite were extensively-studied against aqueous solutions of chloramine-T trihydrate. In addition, reaction kinetics, degradation mechanism and various parameters affecting the photocatalytic efficiency (nanocomposite dose, chloramine-T initial concentration, and reaction pH) were analyzed in detail. Further, the antimicrobial activities of the prepared nanocomposite were tested and the effect of UV-activation on the antimicrobial abilities of the prepared nanocomposite was analyzed. Finally, a comparison between the antimicrobial abilities of the current nanocomposite and our previously-reported nanocomposite (CoxNi1−xFe2O4; x = 0.9/SiO2/TiO2) had been carried out. Our results revealed that the prepared nanocomposite possessed a high degree of crystallinity, confirmed by XRD, while UV–Vis. recorded an absorption peak at 299 nm. In addition, the prepared nanocomposite possessed BET-surface area of (28.29 ± 0.19 m2/g) with narrow pore size distribution. Moreover, it had semi-spherical morphology, high-purity and an average particle size of (19.0 nm). The photocatalytic degradation efficiency was inversely-proportional to chloramine-T initial concentration and directly proportional to the photocatalyst dose. In addition, basic medium (pH 9) was the best suited for chloramine-T degradation. Moreover, UV-irradiation improved the antimicrobial abilities of the prepared nanocomposite against E. coli, B. cereus, and C. tropicalis after 60 min. The observed antimicrobial abilities (high ZOI, low MIC and more efficient antibiofilm capabilities) were unique compared to our previously-reported nanocomposite. Our work offers significant insights into more efficient water treatment and fosters the ongoing efforts looking at how pollutants degrade the water supply and the disinfection of water-borne pathogenic microorganisms

Gene expression analysis and the risk of relapse in favorable histology Wilms’ tumor

Wilms’ tumor (WT) relapse occurs in 15% of patients. We aim to investigate the association between the expression of several genetic markers and WT relapse risk. The study included 51 children treated for WT at a tertiary center between 2001 and 2019: 23 patients had disease relapse (group A) and 28 remained relapse-free after at least 2 years of follow-up (group B). Patients with syndromic, bilateral synchronous or anaplastic WT were excluded. Autologous renal tissue from 20 patients served as control. Total RNA was isolated from tumor tissue and control. Gene expression levels of WT1, HIF1α, b-FGF, c-MYC and SLC22A18 were assessed using quantitative RT-PCR and normalized to GAPDH. Immunohistochemical staining for WT1 and gene expression levels were compared between the study groups. Median patient age was 3 (IQR = 2–5) years and 36 (70.6%) had stage I disease. Baseline characteristics were similar between study groups. Relapse occurred at a median of 6.8 (2.8–24.7) months, predominantly in the lungs (11/23, 47.8%). Tumors that relapsed expressed significantly higher levels of WT1, HIF1α, b-FGF and c-MYC and lower levels of SLC22A18 (p Higher expression levels of WT1, HIF1 α, b-FGF and c-MYC and lower level of SLC22A18 are associated with increased risk of WT relapse. These genetic markers can serve as future prognostic predictors and help stratify patients for treatment.</p