Accurate and fast locating of diseased plants is critical for the sustainability of forest management. Recent developments in computer vision made by deep learning provide a new way for diseased plant detection from images captured by unmanned aerial vehicles (UAV). In this paper, we developed an anchor-free detector, an enhanced CenterNet named as Enhanced CenterNet (ECenterNet) model, which significantly improved the overall accuracy over the original CenterNet model without any increase in the running speed or number of parameters. Compared with the original model, in the newly proposed model improvements had been made in the training stage to increase the accuracy of the detector, while procedures in the test stage remained unchanged. Under the hold-out dataset, the proposed model is trained on 5,281 tiles and tested on 3,842 images, the results showed that the overall detection accuracy of ECenterNet reached 54.7% by COCO Challenge metrics (mean average precision (mAP) @[0.5, 0.95]), while mAP accuracy of the original CenterNet was 49.8%. This research indicates that the proposed deep learning detection model provides a better solution for detecting diseased plants from UAV images with high accuracy and real-time speed.

Temperature is regarded as one of the most important variables for aquatic life, as well as a key physical criterion of water quality, due to its role in a variety of chemical, physical, and biological processes.We chose the HEC-RAS tool to model the thermal regime of the Sebou-Kenitra river estuary because it is impossible to determine the spatiotemporal evolution of temperature in watercourses using traditional methods such as single measurements or interpolation due to the influence of several factors, including hydraulic, tidal rhythm, upstream contributions, and intrusion. The main goal of this research is to develop and test the “HEC-RAS” model with the aim of better understanding thermal dynamics and predicting the spatiotemporal variation of the Sebou river estuary temperature, using the energy transport equation and a variety of input data such as initial temperature, air temperature, wind speed, and dispersion coefficient. The HEC-RAS model, which takes into account many meteorological and geophysical elements and provides an overview of the thermal situation at our study site “the Sebou river estuary,” has also been acknowledged for its deterministic role. We illustrated the impact of meteorological and tidal data on spatiotemporal temperature change at numerous places in the Sebou river estuary by using this model.

Biodiesel generated from a variety of non-edible feedstocks has gained widespread acceptance as a limited diesel fuel alternative in compression ignition engines. For the reliable implementation of biodiesel in commercial sectors, its effect on engine combustion, emission, and performance needs to be examined experimentally. In this study, 10% (N10) and 20 % (N20) Neem oil methyl ester (NME) blends were tested in a direct injection 4-stroke single-cylinder diesel engine incorporated with 5% and 10% exhaust gas recirculation (EGR). At maximum load conditions, Brake thermal efficiency (BTE) was found highest for N20 by 7.2%, and also Brake specific energy consumption (BSEC) was reduced by 11.4% for N20 as compared to diesel. Meanwhile, the incorporation of EGR deteriorates the performance parameters for the N20 blend. The results of emission analysis showed that oxides of nitrogen (NOx) increased with the addition of biodiesel whereas the addition of EGR diminished the NOx value for both biodiesel blends at all loading conditions. Unburnt hydrocarbon (UHC), Carbon monoxide (CO), and smoke emissions decreased by 40.6%, 31.2%, and 29.6% for the N20 blend respectively at full load when compared to diesel. Interestingly, when EGR was provided, CO, UHC, and smoke density values are increased for both N10 and N20 blends at all loading conditions, however lower than diesel operation.

Batch experiments were used to study the interaction mechanism of Ni(II) with biochar as a function of solution pH, contact time, initial concentrations, reaction temperature, and the addition of humic compounds. The results indicate that Ni(II) can be interacted with biochar by a compound mechanism under different environmental conditions. It is suggested that outer-sphere surface complexes at low pH are transformed into inner-sphere surface complexes and surface precipitates are formed at pH 8.89 or 10.18. The combined macroscopic and microscopic insights provide additional details regarding the mobility, fate, and risk of Ni(II) in a practical aquatic environment, as well as the natural purification of metals in ecological environments.

Nanomaterials (NMs) are those tiny materials that range from 1-100 nm. These materials show different characteristics in their physical and chemical forms in comparison to their bulk form. The use of nanomaterials is increasing day by day because of their enormous capabilities in the health sector as well as in other industries. There are currently few, if any, actual protocols for the disposal and characterization of these nanomaterials, which results in environmental toxicity. Heavy use of chemicals in the testing of nanomaterials has resulted in polluting our entire ecosystem. Inconsistent results of nanomaterial show that it is challenging to reduce the toxicity generated by it. In this review, we discuss the administration and use of nanomaterials in the agribusiness sector, in food, and, most importantly, in the environment, for purposes of protecting our plants and crops, dealing with incurable diseases, developing new tastes and textures in the food sector, sensations, identifying pathogenic organisms, and distribution systems where these minute particles can wreak havoc. Despite the potential benefits of nanomaterials, their unintentional harm to the environment and, in some cases, our health is making further development difficult. This article discusses the toxicity of nanomaterials and how they damage our environment, as well as the obstacles that come with overcoming them.

Due to various reasons, crack formation may occur in the concrete structure. Crack formation increases the permeability of concrete to detrimental substances including different types of chemicals, glasses, and water, which upon contact with concrete leads to significant impairment in various properties of concrete including strength, durability, etc. In the present investigation, special microbiological growth having the ability to precipitate calcite through the process of biomineralization is induced in the concrete to evaluate the performance of the concrete. The bacteria were directly added to the concrete mix instead of encapsulating them into clay pellets. Bacteria were classified into two groups i.e. A & B. i. e. 50 & 100 g of bacteria powder were added into 1 L of water respectively. Out of the two groups A and B, 4 samples each were taken of 10 mL, 20 mL, 30 mL and 40 mL, and mixed in the concrete. The results showed that compressive strength and flexural strength increased up to 23.57% and 35% respectively more than the control specimen and the optimum capacity achieved at 30 mL bacterial concentration.

This study focused on the ion release and microstructure of slag during its degradation following erosion by different pH solutions. It focused on controlling factors such as slag particle size range, pH value of the solution, and soaking time. The surface microstructure and particle size distribution of slag with the particle size of 0.075–5.0 mm, the mineral composition of suspended pollutants larger than 0.45 μm, and the phenomenon of nano-scale ion release were examined. When slag was soaked in solutions with different pH values for 30 days, the pH value of leachate tended to be neutral, the release amount of Ca, Mg, Fe, and Cd ions increased and the release rate gradually decreased. The dissolution process of slag in the alkaline solution was slower than that in acid, but suspension and gels formed more easily in an alkaline environment. Nitric acid accelerated the chemical reaction of akermanite, gehlenite, and hawleyite, and released Ca, Mg, and Cd ions. There were clear damage cracks and various irregular pores on the slag surface. Under the attack of alkali solution, the weight of akermanite in slag increased, the Mg ion content in solution decreased, and the suspended solids of calcite and portlandite increased. At pH 12, unlike at pH 3, there were no large surface cracks in the slag and the interface damage was small. Compared with pH 7, there were more irregular substances, such as flakes and spheres. The particle size of slag was mainly 0.1–0.5 mm, the content before and after leaching was 52.80%–55.87% and 55.00%–58.27%, and the slag was in a poor grading state. The findings of this study act as an important reference for understanding the influence of slag leaching on water and soil pollution.

This research aims to evaluate the concentration of radon gas and the risks involved as a result of exposure to it. The nuclear track detector CR-39 was used to measure radon gas in the buildings of Al-Qadisiyah University’s College of Education. For a month, 11 buildings in the college of Education at Al-Qadisiyah University were chosen to measure the radon concentration, with CR-39 reagent placed inside the sponge by two detectors for each building. The highest value of radon concentration was recorded in the CH1 model (270.5±32.9 Bq.m-3), at the building of the Department of Chemistry, and the lowest value was recorded in the Li1 model (96.9±27.7 Bq.m-3), which is the college library building with a concentration rate equal to (168). It is below the acceptable and recommended limit by the International Committee for Radiation Protection (200-300 Bq.m-3).

The degradation of 1-butyl 3-methyl imidazolium chloride (BMIMCl) ionic liquid (IL) by Fenton oxidation has been studied. The optimization of operating parameters for maximum degradation of BMIMCl has been carried out using the Central Composite Design (CCD) of Response Surface Methodology (RSM). The three independent input parameters selected were the dosage of Hydrogen Peroxide (H2O2), the dosage of iron (Fe2+), and the pH of the output or response selected was Total Organic Carbon (TOC) removal efficiency. Experiments were carried out according to the experimental design provided by CCD. For TOC Degradation, the model’s R2 and R2adj correlation coefficients between experimental and model-predicted values were 0.9769 and 0.9561, respectively. This indicates a satisfactory correlation of experimental results with model-predicted values. The optimum values of operating parameters for maximum degradation were found to be H2O2=307 mM (X1), Fe2+=1.1 mM (X2), and (pH)=3.3 (X3), for a reaction time of 120 min. For these operating parameters, the experimental result for TOC removal efficiency was found to be 72.89% as compared to the model-predicted value of 73.67%. These results indicate that the values were closely correlated with each other and thus the model was validated satisfactorily. Overall, the results indicate that the BMIMCl ionic liquid can be effectively degraded by the Fenton oxidation process.

Residents in arid regions of northwest China, where dust storms are more common, are continually exposed to air pollution particularly fine particles of PM2.5 and PM10, causing health hazards to residents. Urban greening species have a strong dust retention capacity which is also available in arid conditions and should be chosen to reduce the impact of air pollution on people and the urban environment. In this paper, three common tree species in four different functional areas: Transportation area (TA), Residential area (RA), Industrial area (IA), and Clean area (CA) of Aksu City were selected to measure their foliar dust to select the matching trees for appropriate sites. The dust particle size distribution for PM2.5 and PM10 was analyzed to explore the particle size difference between foliar dust and natural landing dust. The largest particle size was recorded in IA (168.56 μm), while the smallest was found in CA (43.25 μm). Furthermore, Salix babylonica (S. babylonica) absorbed the highest PM2.5 and PM10, 0.15% and 1.39% respectively; while Ulmus densa (U. densa) absorbed the least PM2.5 and PM10, 0.08% and 0.37%. Platanus acerifolia (P. acerifolia) foliar dust particle density was the highest, and has stable dust retention capacity, while, S. babylonica foliar dust particulate density is the lowest under the same conditions (height/location, pollution exposition, weather). Our findings concluded that the average values of dust diameters in the four areas differed significantly. It is concluded that P. acerifolia is the best performer in removing dust in different functional urban areas and S. babylonica was more suitable for CA because of having the capacity to remove fine particle matter.