Mansoura University

The fall armyworm [FAW; Spodoptera frugiperda (J.E Smith, 1797)] is an invasive and polyphagous insect that infests cereal crops, causing economic losses, and may be led to pose a threat to future the global maize crop in the future. Field trials were conducted to study the negative impacts of S. frugiperda on vegetative growth measurements, yield, and the components of the maize cultivar (Single-Hybrid 168 Yellow) in Luxor Governorate, Egypt. S. frugiperda larvae infestation to maize plants was observed in the 3rd week of June and so continued till the harvest in both 2021 and 2022 seasons. S. frugiperda had three peaks of the seasonal activity/season in the untreated (pesticide-free, control) and in the treated main plots by pesticides. Maize vegetative growth attributes (averages of plant height, stem diameter, and the number of green leaves per plant) displayed higher rates of the treated maize plants by insecticides against S. frugiperda. Maize grain, straw, and biological yield (kg/ha) were decreased in the untreated maize plants (insecticides free) than in the treated by insecticides. Concerning maize yield components, the treated plants were to outperform in the average length of a plant stem (cm), stem diameter (cm), and weight of cob (g), as well as, number of rows/cob, number of grains/ cob, number of grains/cob, maize cob grain weight (g) and weight of 1000-grains (g)], in comparison with the untreated plants. Also, the FAW infestation to untreated maize plants was decreased well in all calculated maize growth attributes, i.e., grain yield, and components. Regarding the relationship between variations in a given variable and the changes in S. frugiperda larvae numbers and plant damage percentage, the simple correlation and regression coefficient revealed a highly significant negative relationship in all the parameters tested. The obtained information may help farmers and decision-makers in the management of FAW populations based on an effective plan related to control measures that should be implemented.

Tissue engineering is an advanced and potential biomedical approach to treat patients suffering from lost or failed an organ or tissue to repair and regenerate damaged tissues that increase life expectancy. The biopolymers have been used to fabricate smart hydrogels to repair damaged tissue as they imitate the extracellular matrix (ECM) with intricate structural and functional characteristics. These hydrogels offer desired and controllable qualities, such as tunable mechanical stiffness and strength, inherent adaptability and biocompatibility, swell- ability, and biodegradability, all crucial for tissue engineering. Smart hydrogels provide a superior cellular environment for tissue engineering, enabling the generation of cutting-edge synthetic tissues due to their special qualities, such as stimuli sensitivity and reactivity. Numerous review articles have presented the exceptional potential of hydrogels for various biomedical applications, including drug delivery, regenerative medicine, and tissue engineering. Still, it is essential to write a comprehensive review article on smart hydrogels that suc- cessfully addresses the essential challenging issues in tissue engineering. Hence, the recent development on smart hydrogel for state-of-the-art tissue engineering conferred progress, highlighting significant challenges and future perspectives. This review discusses recent advances in smart hydrogels fabricated from biological macromole- cules and their use for advanced tissue engineering. It also provides critical insight, emphasizing future research directions and progress in tissue engineering.

Kaempferol, found in various plants and foods, has gained attention as a useful flavonoid in owing to its potential anticancer characteristics. Recent research studies suggest that kaempferol is effective in the inhibition and treatments of several forms of cancer, e.g. lung, ovarian, breast and lung cancer. One probable mechanism of action of kaempferol is its anti-inflammatory and antioxidant potential, which may help to prevent DNA damage and inhibit the proliferation of cancerous cells. Besides triggering apoptosis in cancerous cells, Kaempferol may also inhibit the growth and relocation of cancerous cells. Moreover, kaempferol has a very wide range of bioactivities, involving anti-inflammatory and antioxidant effects. This includes understanding the optimal dosing and timing of kaempferol treatment, as well as the potential interactions with other medications and the long-term safety of kaempferol use. Overall, the available evidence and studies suggest that kaempferol may provide a potential natural agent for the prevention and treatments of cancers. Despite the promising findings in preclinical and clinical research, further research is needed to confirm its efficacy and understand the mechanisms of action and to fully explore the potential of kaempferol in different cancers .

Ethyl 2‐amino‐4,5‐diphenylfuran‐3‐carboxylate ( 2 ), a reactive synthon, was successfully used to synthesize a novel series of furan and furo[2,3– d ]pyrimidinone analogues by interactions with the proper chemical reagents. With the aid of precise spectroscopic data (FT‐IR, Mass, ¹ H‐NMR, and ¹³ C‐NMR spectra), the structures of products were clearly established. The cytotoxic results by MTT assay showed that furo[2,3– d ]pyrimidinone analogues 4 (IC 50 =6.1±0.8 & 10.2±2.5 μM), 6 (IC 50 =9.2±2.1 & 17.8±0.5 μM), 11 (IC 50 =7.1±0.5 & 9.2±1.8 μM), 12 (IC 50 =5.4±2.3 & 9.8±1.7 μM), 15 (IC 50 =5.2±2.0 & 8.8±2.0 μM), 18 (IC 50 =4.2±2.4 & 10.7±1.8 μM), and 21 (IC 50 =12.8±1.9 & 18.8±0.9 μM) had strong in vitro cytotoxic activities to inhibit the growth of colorectal carcinoma (HCT‐116), and prostate cancer (PC3) cell lines, respectively. However, their effects on normal lung fibroblast (WI‐38) were weak in comparison to 5‐fluorouracil as a positive control. On the other hand, the biological evaluations supported the presence of strong antioxidant activity for the furo[2,3– d ]pyrimidinone analogues 4 , 6 , 15 , 17 , and 21 (% inhibition=89.10, 84.16, 82.09, 88.11, and 80.23 %, respectively) when compared to ascorbic acid (88.42 %). It has been proven that the most powerful cytotoxic and antioxidant compounds have a superior protective influence on DNA against bleomycin‐induced damage.

Climate change poses a critical global challenge, necessitating the monitoring of shorelines to understand its impact. Satellite images and Google Earth Engine (GEE) are commonly used to monitor shoreline changes with reasonable accuracy. This study aims to improve the precision and reliability of shoreline monitoring by developing an automated deterministic technique using Landsat images and GEE. The developed technique identifies pure water and land pixels by applying spectral index thresholds. Additionally, it employs Monte Carlo simulation to generate multispectral reflectance values for pixels with varying water percentages. Then, a linear fitting model is employed to estimate the wetness coefficient in each pixel in the image. Finally, geospatial software, in the GIS environment, is used for estimating the shoreline changes using the estimated wetness coefficient map. In order to assess and verify the proposed shoreline estimation technique, five regions were selected, including Egypt's northern coast, as well as shorelines in Morocco, India, Japan, and Portugal, spanning the years from 2003 to 2022. The results show an effective estimation of shoreline changes with a root-mean-square error of 0.56-pixel size, indicating subpixel accuracy. A notable advantage of this method is its flexibility, as it derives information directly from the image, making it suitable for a wide range of regions with different water and soil characteristics. Therefore, it can be used to offer valuable insights for monitoring shoreline changes and supporting coastal management and planning efforts. The findings of the case studies revealed that breakwaters effectively reduced erosion in coastal areas of Egypt and Portugal, whereas the coastal regions of India and Morocco remained stable. Conversely, Japan experienced a high erosion rate (-2.83 + 4.08 m/year) in its coastal areas due to wave height. This emphasizes the importance of monitoring shoreline changes and developing effective strategies to mitigate the negative impacts of climate change on coastal areas.

In this study, the simultaneous determination of bilastine and montelukast, two recently approved co‐formulated antihistaminic medications, was accomplished using a quick, sensitive, environmentally friendly, and reasonably priced synchronous fluorescence spectroscopic approach for the first time. Enhancement of the method's sensitivity down to nanogram levels was achieved by the addition of sodium dodecyl sulfate (1.0% w/v) as a micellar system. According to the results, bilastine and montelukast's fluorescence was measured at 255.3 and 355.3 nm, respectively, using Δλ of 40.0 nm and distilled water as a green diluting solvent. With respect to the concentration ranges of bilastine (5.0–300.0 ng/ml) and montelukast (50.0–1000.0 ng/ml), the method showed excellent linearity ( r ≥ 0.9998). The results showed that the suggested method is highly sensitive, with detection limits of 1.42 and 13.74 ng/ml for bilastine and montelukast, respectively. Within‐run precisions (intra‐ and interday) per cent relative standard deviations (RSD) for both analytes were <0.59%. With high percentage recoveries and low percentage RSD values, the designed approach was successfully applied for the simultaneous estimation of the cited medications in their dosage form and human plasma samples. To evaluate the green profile of the suggested method, an analytical GREENNESS metric approach (AGREE) and green analytical procedure index (GAPI) metric tools were used. These two methods for evaluating greenness confirmed that the developed method met the highest number of green requirements, recommending its use as a green substitute for the routine analysis of the studied drugs. The proposed approach was validated according to ICHQ2 (R1) guidelines.

Objective Understanding the lateralization factors, including the anatomic and hemodynamic mechanisms, is essential for diagnosing cardio-embolic stroke. This study aims to investigate the elements, for the first time together, that could affect the laterality of stroke. Methods We performed a monocentric retrospective case-control study based on prospective registries of acute ischemic stroke patients in the comprehensive stroke center of the RWTH University hospital of Aachen for three years (June 2018–June 2021). We enrolled 222 patients with cardioembolic stroke (136 left stroke and 86 right stroke) admitted for first-ever acute ischemic stroke with unilateral large vessel occlusion of the anterior circulation. The peak systolic velocity (PSV) asymmetry of middle cerebral artery (MCA) was assessed by doppler as well as internal carotid artery (ICA) angle, aortic arch (AA) branching pattern and anatomy were assessed by CT-Angiography. Results We found that the increasing left ICA angle (p = 0.047), presence of bovine type AA anatomy (p = 0.041) as well as slow PSV of the right MCA with a value of >15% than left (p = 0.005) were the predictors for left stroke lateralization, while the latter was an independent predictor for the left stroke (OR=3.341 [1.415–7.887]). Inter-Rater Reliability ranged from moderate to perfect agreement. Conclusion The predictors for left stroke lateralization include the higher values of left ICA angle, presence of the bovine type AA and the slow right MCA PSV.

Grid-forming solid-state transformer (GFm-SST) is an emerging technology in modernized power grids that delivers the merits of SSTs and GFm control, thus, providing a compact, controllable, and grid-supporting means of renewable resources integration. This paper presents a comprehensive and coordinated GFm controller for two-stage SST-interfaced solar photovoltaic (PV) systems. The controllers of both SST stages are coordinated, and a virtual governor is implemented within the coordinated reference generation stage so that the PV power directly interacts with grid-side frequency events while preserving minimal dc voltage variations. A bandgap ac voltage controller is proposed to ensure accurate reactive power sharing, even under parallel operation with line parameters mismatch, and reduced Q – P coupling. In addition, the proposed GFm-SST-PV system is equipped with a low-voltage ride-through controller to bypass faulty conditions safely. Furthermore, a linearized small-signal model of the whole system is developed, validated, and used to 1) investigate the system stability under broad variations of solar irradiance, power reserve, and control parameters and 2) provide guidelines for a coordinated design of all control parameters, considering all system dynamics and control loops interactions. Extensive time-domain simulations and hardware-in-the-loop real-time tests are conducted to verify all features and capabilities of the proposed configuration.

It is critical to remove dyes from wastewater as they cause harm to human and aquatic life due to their carcinogenic, toxic, and mutagenic effects. Here, low-cost activated carbons (CPs) were produced from the date (Phoenix dactylifera L.) pits. The prepared CPs were chemically activated utilizing zinc chloride to obtain activated carbons from date pits (ZCPs). The physicochemical properties, chemical composition, and morphology of ZCPs material and the active surface functional groups involved in adsorption were identified using N2 adsorption–desorption isotherm, scanning electron microscopy, point of zero charges (pHPZC), and Fourier transforms spectroscopy. The ZCPs biocomposite was applied for the Brilliant green (BG) removal from aqueous solutions, where the efficiency was assessed as functions of pH value, foreign ions, the initial dye concentration, dose of adsorbent, adsorption time, and temperature. The outcomes showed that the prepared ZCPs biocomposite exhibited high uptake of BG with a qe of 247.752 mg/g. The isotherm and kinetic studies show that the adsorption process of BG dye onto ZCPs biocomposite followed Langmuir, and pseudo-second-order models, respectively. From the estimated thermodynamic functions, it was found that the nature of the BG dye adsorption process onto the prepared ZCPs adsorbent was endothermic and spontaneous. With a relative standard deviation of less than 3%, the prepared ZCPs were successfully applied for the removal of BG from real water samples with a recovery of more than 90%. The plausible mechanism of BG adsorption onto the prepared ZCPs can be assigned to various interactions, such as pore–filling, electrostatic attraction, H-bonding, and π–π stacking.

Olive ( Olea europaea L.) is a subtropical tree cultivated in arid, dry and temperate regions. Olive orchards in Al‐Jouf of Saudi Arabia are the largest worldwide and currently face harmful pest infestation. The present study aimed at evaluating the efficiency of the predatory mite Agistemus exsertus Gonzalez (Acari: Stigmaeidae) and the exogenously applied melatonin (MT), glycine betaine (GB) and 5‐aminolevulinic acid (ALA) as eco‐friendly approaches for enhancing the biological control of four mite species ( Tegolophus hassani , Oxycenus niloticus , Aceria olivi and Tetranychus urticae ) infesting olive trees in Al‐Jouf under laboratory and field conditions. Field experiment was conducted on 6‐year‐old Manzanillo olive trees grown in a private orchard farm in Al‐Jouf during two seasons, 2020 and 2021. Results revealed that A. exsertus developed successfully from egg to adult. The females of T. hassani , O. niloticus , A. olivi, and T. urticae required 7.36, 8.89, 9.98 and 8.38 days, respectively, to develop from egg to adult at 28°C and 65 ± 5% relative humidity. O. niloticus was the most preferred prey of A. exsertus . The net reproductive rate (R 0 ) was 42.1, 38.7, 34.6 and 36.8 females/female/generation, the intrinsic rate of increase (r m ) was 0.27, 0.26, 0.23 and 0.20 females/female/day, and the mean generation time (T) was 16.2, 17.1, 18.6 and 17.2 days when a predator consumed T. hassani , O. niloticus , A. olivi and T. urticae , respectively. The adult female consumed daily about 114 O. niloticus , 105 A. olivi , 95 T. hassani and 15.2 T. urticae individuals, respectively. A. exsertus proved to be an effective biocontrol agent against mites infesting olive trees. In addition, the exogenous application of 1 mM MT, 15 mM GB and 25 mg/L ALA, alone or in combination, caused significant mortality for the four mites. Application of these natural compounds, alone or in combination, also significantly enhanced the growth, relative water content, relative chlorophyll, content of flavonoid and nutrients, antioxidant enzymes activities, stress‐related genes expression and fruit yield and quality of the infested olive trees compared to non‐treated infested trees. This study is the first that demonstrates the efficiency of these eco‐friendly approaches for controlling mites infesting olive trees, and could be used as a replacement for the harmful chemical acaricides.

In this paper, we investigate the impact of both static and dynamic effects of motion on Underwater visible light communication (UVLC) channels. While previous studies have focused on static channel modeling, we argue that dynamic channel modeling is crucial for accurate UVLC analysis. To model static and dynamic UVLC channels, we use the Monte Carlo ray tracing (MCRT) method in Zemax Optics Studio; a reliable and practical setup simulator that produces results similar to experimental data. We evaluate the effect of channel coding on system performance by comparing nine different combinations and using Goodness-of-Fit (GoF) tests to determine the best-fit distribution. Our results reveal that the static case outperforms the dynamic case in terms of raw performance without any coding. However, we also show that the bit error rate (BER) is severely impacted in various realistic scenarios for a dynamic environment. To improve the BER and achieve adequate received signal quality, we recommend using convolutional codes. This paper emphasizes the importance of dynamic channel modeling in UVLC and provides practical solutions to enhance the UVLC performance in dynamic environments. The findings of our study provide valuable insights into the performance of UVLC systems and emphasize the need for researchers and designers to account for the dynamic realistic behavior in the underwater channel to achieve optimal performance in UVLC systems for underwater communication applications.

Rainfall plays an essential part in numerous aspects of the natural world, including the environment, ecosystems, human societies, and the global climate system. The lack of rainfall data, typically accompanied by data gaps in arid regions like Saudi Arabia, presents substantial obstacles for hydrological and environmental studies. The objective of this study is to identify a suitable imputation technique for finding missing rainfall data on daily and monthly time scales. In this study, eight weather stations were selected, located in the vicinity of Al-Madinah Al-Munawarah City for the period of 5 years (2008–2012). Two stations (226, 371) were considered target/empty stations to compare the computed values from each method to real values, i.e., cross-validation. In this study, various techniques, including arithmetic average (AA), inverse distance weighing (IDW), normal ratio (NR), satellite products, TRMM, IMERG-GPM, CHIRPS, MERRA-2, and artificial intelligence-based and feed-forward backpropagation neural network (FFBP-NN), were evaluated. Statistical measures were used to check the reliability of each imputation technique on daily and monthly rainfall datasets. The results revealed that FFBP-NN exhibited the highest correlation values, surpassing 0.95 for both the stations on monthly and above 0.80 on daily time scale. IMERG-GPM performed well across satellite datasets, with a daily correlation over 0.50 and a monthly correlation above 0.80. Similarly, NR outperformed AA and IDW techniques in terms of correlation, providing values above 0.5 for daily and 0.89 for monthly intervals over both stations. Generally, all methods performed well on both time scales, except MERRA-2 dataset having a lower correlation coefficient. Based on the analysis, it is recommended to utilize the FFBP-NN approach for longer time series data availability while IMERG-GPM for high spatial variation in region. This research contributes to the ongoing efforts to mitigate data gaps in arid regions and supports more accurate water resource management and environmental planning.

We present an investigation of the electronic, optical, and mechanical characteristics of the nano-structured Gallium Phosphide (GaP) semiconductor. It has been reported that high pressures have an impact on the interesting features. In our investigation, the pseudo-potential method was employed. It has been demonstrated that the phonon frequencies and sound speeds of GaP depend on pressure. The recent study can aid in our understanding of how pressure impacts the properties of nano-structured GaP material and electronics. Our results generally demonstrate good agreement with the experiment. The optoelectronic applications in the high-pressure region could make use of the predicted properties.

Background Retinal degenerative diseases such as diabetic retinopathy and diabetic macular edema are characterized by impaired retinal endothelial cells (RECs) functionality. While the role of glycolysis in glucose homeostasis is well-established, its contributions to REC barrier assembly and cell spreading remain poorly understood. This study aimed to investigate the importance of upper glycolytic components in regulating the behavior of human RECs (HRECs). Methods Electric cell-substrate impedance sensing (ECIS) technology was employed to analyze the real-time impact of various upper glycolytic components on maintaining barrier functionality and cell spreading of HRECs by measuring cell resistance and capacitance, respectively. Specific inhibitors were used: WZB117 to inhibit Glut1/3, lonidamine to inhibit hexokinases, PFK158 to inhibit the PFKFB3-PFK axis, and TDZD-8 to inhibit aldolases. Additionally, the viability of HRECs was evaluated using the lactate dehydrogenase (LDH) cytotoxicity assay. Results The most significant reduction in electrical resistance and increase in capacitance of HRECs resulted from the dose-dependent inhibition of PFKFB3/PFK using PFK158, followed by aldolase inhibition using TDZD-8. LDH level analysis at 24- and 48-hours post-treatment with PFK158 (1 μM) or TDZD-8 (1 and 10 μM) showed no significant difference compared to the control, indicating that the disruption of HRECs functionality was not attributed to cell death. Conversely, inhibiting Glut1/3 with WZB117 had minimal impact on HREC behavior, except at higher concentrations (10 μM) and prolonged exposure. Lastly, inhibiting hexokinase with lonidamine did not noticeably alter HREC cell behavior. Conclusion This study illustrates the unique impacts of components within upper glycolysis on HREC functionality, emphasizing the crucial role of the PFKFB3/PFK axis in regulating HREC behavior. Understanding the specific contributions of each glycolytic component in preserving normal REC functionality will facilitate the development of targeted interventions for treating endothelial cell dysfunction in retinal disorders while minimizing effects on healthy cells.

One of the major problems that cause continual trouble in deep learning networks is that training a large network requires massive labelled datasets. The preparation of a massive labelled dataset is a cumbersome task and requires lot of human interventions. This paper proposes a novel generator network ‘Sim2Real’ transfer is a recent and fast-developing field in machine learning used to bridge the gap between simulated and real data. Training with simulated datasets often converges due to its size but fails to generalize real-world applications. Simulated datasets can be used to train and test deep learning models, enables the development and evaluation of new algorithms and architectures. By simulating road dataset, researchers can generate large amounts of realistic road-traffic dataset that can be used to study and understand several problems such as vehicular object tracking and classification, traffic situation analysis etc. The main advantage of such a transfer algorithm is to use the abundance of a simulated dataset to generate huge realistic-looking datasets to solve data-intense tasks. This work presents a novel, robust sim2real algorithm that converts the labels of a semantic segmentation map to a realistic-looking street view using the Cityscapes dataset and aims to achieve robust urban mobility for smart cities. Further, the generalizability of the Cycle Generative Adversarial Network (CycleGAN) architecture was tested by using an origami robot dataset for sim2real transfer. We show that the results were found to be qualitatively satisfactory for different traffic analysis applications. In addition, road perception was done using a lightweight SVM pipeline and evaluated on the KITTI dataset. We have incorporated Cycle Consistency Loss and Identity Loss as the metrics to evaluate the performance of the proposed Cycle GAN model. We inferred that the proposed Cycle GAN model provides an Identity loss of less than 0.2 in both the Cityscapes dataset and KITTI datasets. Also, we understand that the super-pixel resolution has a good impact on the quantitative results of the proposed Cycle GAN models.