This study is conducted to determine the effect of pathogenicity of the fungus Lecanicillium lecanii in some aspects of life of the insect saw toothed beetle Oryzaephilus surinamensis L. (Coleoptera: Silvanidae) under laboratory conditions with three concentrations of spores and mildew commentator (1 × 103, 1 × 105, 1 × 107) spore / ml , on eggs and larvae second phase of the insect .The study also includs the effect of the fungus concentrations of germination on rice (jasmine) by using direct spray treatment. The results show great fungus efficiency in the control of some aspects of life of the insect, where varied efficiency depends on the concentration of spores, The highest percentage loss of eggs is 63.33% at a concentration

Early detection of eye diseases can forestall visual deficiency and vision loss. There are several types of human eye diseases, for example, diabetic retinopathy, glaucoma, arteriosclerosis, and hypertension. Diabetic retinopathy (DR) which is brought about by diabetes causes the retinal vessels harmed and blood leakage in the retina. Retinal blood vessels have a huge job in the detection and treatment of different retinal diseases. Thus, retinal vasculature extraction is significant to help experts for the finding and treatment of systematic diseases. Accordingly, early detection and consequent treatment are fundamental for influenced patients to protect their vision. The aim of this paper is to detect blood vessels from

This study was conducted to assess the hydrocarbon degradation abilities of Sphingomonas paucimobilis, Pentoae species, Staphylococcus aureus, and Enterobacter cloacae, which isolated from diesel contaminated soil samples. Single strains and mixed bacterial consortia have been investigated their ability to degrade 1.0 % (v/v) of diesel oil in Bushnell- Haas medium as sole.carbon.and.energy.source. At temperature 30^∘C, the individual.bacterial.isolates exhibited low growth and low degradation.than did the.mixed. bacterial.culture. After 28 days.of incubation the.combination.of four isolates degraded.an upper limit.of diesel  88.4%. This was. continued.by 85.1% by S. paucimobilis, 84 % by Pentoae sp., 79% by S.aureus, and

Manganese sulfate and Punica granatum plant extract were used to create MnO₂ nanoparticles, which were then characterized using techniques like Fourier transform infrared spectroscopy, ultraviolet-visible spectroscopy, atomic force microscopy, X-ray diffraction, transmission electron microscopy, scanning electron microscopy, and energy-dispersive X-ray spectroscopy. The crystal's size was calculated to be 30.94nm by employing the Debye Scherrer equation in X-ray diffraction. MnO₂ NPs were shown to be effective in adsorbing M(II) = Co, Ni, and Cu ions, proving that all three metal ions may be removed from water in one go. Ni(II) has a higher adsorption rate throughout the board. Co, Ni, and Cu ion removal efficiencie

Manganese sulfate and Punica granatum plant extract were used to create MnO2 nanoparticles, which were then characterized using techniques like Fourier transform infrared spectroscopy, ultraviolet-visible spectroscopy, atomic force microscopy, X-ray diffraction, transmission electron microscopy, scanning electron microscopy, and energy-dispersive X-ray spectroscopy. The crystal's size was calculated to be 30.94nm by employing the Debye Scherrer equation in X-ray diffraction. MnO2 NPs were shown to be effective in adsorbing M(II) = Co, Ni, and Cu ions, proving that all three metal ions may be removed from water in one go. Ni(II) has a higher adsorption rate throughout the board. Co, Ni, and Cu ion removal efficiencies were 32.79%, 75

The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi

The depletion of petroleum reserves and increasing environmental concerns have driven the development of eco-friendly asphalt binders. This research investigates the performance of natural asphalt (NA) modified with waste engine oil (WEO) as a sustainable alternative to conventional petroleum asphalt (PA). The study examines NA modified with 10%, 20%, and 30% WEO by the weight of asphalt to identify an optimal blend ratio that enhances the binder’s flexibility and workability while maintaining high-temperature stability. Comprehensive testing was conducted, including penetration, softening point, viscosity, ductility, multiple stress creep recovery (MSCR), linear amplitude sweep (LAS), energy-dispersive X-ray spectroscopy (EDX), F

Rapid worldwide urbanization and drastic population growth have increased the demand for new road construction, which will cause a substantial amount of natural resources such as aggregates to be consumed. The use of recycled concrete aggregate could be one of the possible ways to offset the aggregate shortage problem and reduce environmental pollution. This paper reports an experimental study of unbound granular material using recycled concrete aggregate for pavement subbase construction. Five percentages of recycled concrete aggregate obtained from two different sources with an originally designed compressive strength of 20–30 MPa as well as 31–40 MPa at three particle size levels, i.e., coarse, fine, and extra fine, were test