The essay discusses how different environmental factors affect plant growth by explaining how each factor affects the physiological processes within the plant. The essay begins by explaining the effect of temperature on plant growth, as high or low temperatures can significantly affect the rate of photosynthesis and lead to a reduction in water and nutrient absorption. It also discusses the light intensity impacting plants because the more appropriate the light intensity is, the more enhanced the plant's photosynthesis ability, and in the excess or insufficient light condition, the growth can be inhibited. Additionally, the article outlines the effect of water shortage on the plant because this leads to the closure of stomata to avoid water

In this research PbS thin film have been prepared by chemical bath deposition technique (CBD).The PbS film with thickness of (1-1.5)μm was thermally treated at temperature of 100°C for 4 hours. Some Structural characteristics was studied by using X-ray diffraction (XRD)and optical microscope photograph some of chemical gas sensing measurements were carried out ,it shown that the sensitivity of (CO2) gas depend on the grain Size and deposition substrate. The grain size of PbS film deposited on on glass closed to 21.4 nm while 37.97nm for Si substrate. The result of current-voltage characterization shwon the sensitivity of prepared film deposited on Si better than film on glass.

Nearly a century and a half has passed since Sarah Orne Jewett published her much anthologized short story “A White Heron” (1886), but commentators on the tale missed one of the most important points in the text. It is the story’s similarity to the traditional Euro-centric fairy tale of “Little Red Riding Hood”. As an author, writing at the end of the ninetieth century, a time that witnessed the demise of the Romantic movement in America and the beginning of the age of Realism, Jewett did not romanticize her characters, despite the idyllic landscape in which “A White Heron” is set. Her story can be analyzed as a text that aims at disseminating ecological awareness among her young readers. This study focuses on Jewett

Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

This research paper studies the use of an environmentally and not expensive method to degrade Orange G dye (OG) from the aqueous solution, where the extract of ficus leaves has been used to fabricate the green bimetallic iron/copper nanoparticles (G-Fe/Cu-NPs). The fabricated G‑Fe/Cu-NPs were characterized utilizing scanning electron microscopy, BET, atomic force microscopy, energy dispersive spectroscopy, Fourier-transform infrared spectroscopy and zeta potential. The rounded and shaped as like spherical nanoparticles were found for G-Fe/Cu‑NPs with the size ranged 32-59 nm and the surface area was 4.452 m²/g. Then the resultant nanoparticles were utilized as a Fenton-like oxidation catalyst. The degradation efficiency of

Developing an efficient algorithm for automated Magnetic Resonance Imaging (MRI) segmentation to characterize tumor abnormalities in an accurate and reproducible manner is ever demanding. This paper presents an overview of the recent development and challenges of the energy minimizing active contour segmentation model called snake for the MRI. This model is successfully used in contour detection for object recognition, computer vision and graphics as well as biomedical image processing including X-ray, MRI and Ultrasound images. Snakes being deformable well-defined curves in the image domain can move under the influence of internal forces and external forces are subsequently derived from the image data. We underscore a critical appraisal

Today’s modern medical imaging research faces the challenge of detecting brain tumor through Magnetic Resonance Images (MRI). Normally, to produce images of soft tissue of human body, MRI images are used by experts. It is used for analysis of human organs to replace surgery. For brain tumor detection, image segmentation is required. For this purpose, the brain is partitioned into two distinct regions. This is considered to be one of the most important but difficult part of the process of detecting brain tumor. Hence, it is highly necessary that segmentation of the MRI images must be done accurately before asking the computer to do the exact diagnosis. Earlier, a variety of algorithms were developed for segmentation of MRI images by usin