Zanco Journal of Pure and Applied Sciences

Alzheimer's Disease (AD) poses a substantial universal health challenge with limited effective treatment options. Ayurvedic medicinal herbs are being evaluated as prospective candidates for neuroprotection due to their diverse array of bioactive compounds and comprehensive therapeutic principles. This review compiles the latest information on Ayurvedic herbs. It examines their mechanisms of action, clinical effectiveness, safety profiles, and regulatory issues in the management of AD. Key findings highlight their potential to mitigate neuroinflammation, oxidative stress, and cognitive decline, offering insights into integrative approaches that synergize traditional wisdom with modern pharmacotherapy. Future research directions underscore the need for mechanistic studies, large-scale clinical trials, and personalized medicine strategies to optimize therapeutic outcomes in AD.

Modified asphalt mixtures are increasingly used in high trafficked flexible pavement to improve performance and durability. Many laboratory studies have been conducted to compare the effectiveness of these mixtures with traditional HMA (hot mix asphalt). In mixes for asphalt concrete paving, nano modifiers are typically recommended when increased performance and durability are required, common nano modifiers used in asphalt mixtures, including: CNTs (carbon nanotubes), NC (nano clay), and NS (nano silica). This study reviews these nanomaterials used in asphalt modification, describes the techniques used to modify the asphalt binder using these materials, presents the influences of these nano modifiers on the asphalt pavement concrete mixtures’ overall performance based on information from past literatures to assess their effects on properties as rutting resistance and moisture susceptibility as well as discusses challenges and advantages of nanomaterials in asphalt modification. The outcomes demonstrate that the utilizing nano modifiers in hot mix asphalt mixtures reduce the rutting depth by 4% to 88%. Additionally, nanomaterials enhance moisture sensitivity and increase tensile strength ratio by 9% to 25%.

Animal production is inextricably linked to human nutrition and health. Animal intestinal illnesses like Campylobacter, Salmonella, Listeria and Yersinia can directly lead to food contamination. As a result, innovative approaches to animal breeding are being used with the goal of producing meat that is safer and of higher quality while also taking environmental preservation and animal welfare into consideration. All together, these developments have sped up research for substitute feed additives that can achieve some of the advantageous effects of antibiotics. Alternative materials for antibiotics studied, commercially marketed and developed for use in practical utilization. The bacteria that make up the gastrointestinal microbiota vary from those that are believed to be advantageous to the host to those that could be detrimental. Feeds containing probiotics provide a ray of hope for that area of the feed industry. The information currently available regarding the effects of probiotics on animal health is required; they conclusively demonstrate how probiotics function to lower bacterial gastrointestinal pathogen populations. Worldwide interest for probiotics is rising due to customers seeking safe therapeutic and preventive health benefits as well as the introduction of promising new products to the market. Increased health consciousness among the general public and the availability of probiotics as dietary supplements are the primary drivers of the global probiotic market's expansion. The aim of this article is to discuss how probiotics and alternative chicken production techniques might enhance food safety and poultry health by reducing pathogenic organisms and increasing the yield and quality of eggs and meat.

In this study, coconut shell (CS), coconut shell carbonized (CSC), acid coconut shell carbonized (ACSC), base coconut shell carbonized (BCSC) finally coconut shell carbonized impregnation by nickel (II) oxide (CSC/NiO) nanocomposite, investigated to remove ciprofloxacin (CIP) from an aqueous solution. Optimization of adsorption conditions: initial CIP concentration, pH, adsorbent dose and contact time were studied and found to have a significant effect on CIP removal. The morphological and chemical characteristics of the adsorbents were established by Fourier Transform Infrared (FTIR), X-Ray diffraction (XRD), The Scanning Electron Microscopy (SEM) and Energy Dispersive X-Ray (EDX). The adsorption kinetic study shows the CIP adsorption onto adsorbents follow the pseudo-second order, the values of K2, qe and R2 in the range (0.254-9.529) gµg-1min-1, (0.016-0.300) mgg-1 and (0.706-0.980) respectively at three different temperature 298 K, 308 K and 318 K. The Freundlich isotherm model adsorption data were applied and the value of KF, nF and R2 in the range (3.056-3.694) mg g-1, (1.379-1.720) and (0.886-0.999) respectively. The experimental data found to be suitable linearity with Langmuir isotherm the value of KL, Cm and R2 in the range (0.011-0.180) L mg−1, (10000-166667) μg g−1 and (0.760-0.980) respectively. The negative values of ΔGo (−18.47 to −23.74) kJ mol−l and positive value of each of ΔHo and ΔSo in the range (0.131 to 0.228) kJ mol−l and (0.992 to 1) kJ mol−lK-1 were indicating the adsorption of CIP on to adsorbents was a spontaneous and endothermic process.

There has been serious environmental and health damage caused by the excessive discharge of organic wastewater. In this article, a magnetic nanocomposite adsorbent, cyclodextrin@Ferrous-ferric oxide (CDs@Fe3O4), was used for the efficient adsorption of sulfathiazole (STZ) from wastewater due to its special amphiphilicity. The amount of separated STZ was determined using a diazotization-coupling reaction with 1,5-dihydro naphthalene. It was determined whether initial drug concentration, pH, dosage of adsorbent, contacting time, and temperature influenced the adsorption process. The proposed method showed a linear range from 0.5 to 4.0 μg/mL STZ. With an STZ concentration of 20 μg/mL and 80 mg of adsorbent, CDs@Fe3O4 has the best adsorption and removal effect on STZ at a pH of 7.0 and room temperature that reaches 99.1%. An external magnetic field can quickly separate CDs@Fe3O4 adsorbed with STZ drug, and then HCl treatment can easily regenerate the composite. Despite recycling five times, the magnetic composite is able to remove more than 99% of STZ. The proposed method was applied successfully using synthetic water samples. The obtained results showed recovery values from 96.27 to 100.02% with RSDs ranging from 0.32 to 2.48%. Thus, an environmentally friendly and economical method will be developed to treat drug wastewater.

Desmodesmus exhibits significant morphological diversity, leading to multiple synonyms being assigned to this species based solely on optical microscopic morphology. Prior studies have demonstrated that Candida spp. displays increased resistance in critical care units relative to non-ICU isolates. In the current study, the green alga Desmodesmus subspicatus (Scenedesmaceae) from AL-Hilla River in Iraq was isolated, purified, and identified morphologically via optical microscope and at the level of molecular using 5.8S ribosomal RNA genes, as well as the isolate species recorded in NCBI gene bank with PQ192620.1. Using the MEGA and BLAST programs, we constructed a phylogenetic tree and analyzed the similarities and differences with international isolates. The results showed that the antifungal activity of the alcoholic extract of the algae Desmodesmus subspicatus against C. dubliniensis had a standard deviation of 4.66 and a mean inhibition zone of 23.90. The average inhibition zone against Candida albicans was 25.23, with a standard deviation 5.54. C. glabrata had an inhibition zone with an average of 24.20 and a standard deviation of 4.04.

To solve unconstrained optimization problems, this study proposes a conjugate gradient (CG) algorithm that satisfies both the convergence and descent conditions. The technique improves on conventional CG techniques through guaranteeing quick convergence and increased solution accuracy across a range of test functions. The study also applies this CG method to model COVID-19 transmission dynamics within a parameterized optimization scope. Analyzing reported cases from January 28, 2024, to September 29, 2024, demonstrates the model's effectiveness in capturing nonlinear trends, with a resurgence of COVID-19 cases in the latter half of the study period. This emphasizes the need for adaptive public health strategies in response to fluctuating infection rates, highlighting the significance of advanced mathematical modeling in infectious disease management.

The conjugate formula's significance is frequently emphasised by conjugate gradient approaches. In this paper, a novel conjugate coefficient for the conjugate gradient technique is introduced using a quadratic model and conjugacy condition. This coefficient is used to address image restoration issues. The algorithms described in this study exhibit the essential descent property and global convergence. The new approach is far better, as shown by numerical experiments. It has been demonstrated that the innovative conjugate gradient strategy outperforms the conventional FR conjugate gradient method. The great improvement of the new method has been confirmed by numerical testing. It has been demonstrated that the novel conjugate gradient approach outperforms the widely used FR approach.

The present study deals with spatial and temporal variation of heavy metals and its contaminant in Qua Iboe River within five sampling locations, from January 2020 to June 2021. Seven heavy metals (Cd, Zn, Pb, Fe, Mn, Cr and Ni) were investigated using standards methods. Contamination factor (Cf), degree of contamination (DC), ecological risk factor (Er) and potential ecological risk index (PERI) were used to determined the contamination status and ecological risk. The spatial mean values of Zn, Pb, Fe and Ni in all the locations, Cd in locations 2, 3, 5; Cd mean value in wet season and the mean value of Zn, Pb, Fe , Ni in both seasons were exceeded the limits. The Cf value for Cd (location 1), Cr (locations 1, 2, 4, 5) and in both seasons were less than 1, DC values across the locations and in both seasons were ≥ 24 (very high degree of contamination), ER values for Zn in locations 1, 4 and 5 were between 40 ≤ – < 80 (moderate), 2 was between 160 ≤ – < 320 (high), location 3 and in both seasons were between 80 ≤ – < 160 (considerable high ecological risk). The PERI values in locations 2, 3, 5 and for the seasons were ranged between 150 < PERI < 300 indicating moderate ecological risk. These were influenced by human activities, geogenic and seasons. Frequent monitoring is recommended to salvage the aquatic ecosystem and the inhabitant biota.

Ascochyta rabiei (Pass.) Labr., the fungal pathogen that causes ascochyta blight, is a serious global danger to chickpea crops, especially in the Mediterranean and other colder, wetter climates. This foliar disease can cause losses of up to 50% and is particularly damaging in humid and rainy environments. Severe outbreaks frequently result in total crop destruction. Chemical control, despite providing quick and efficient intervention, presents challenges such as environmental contamination and the evolution of fungicide resistance due to the heterothallic nature of the fungus. This study aimed to explore the use of antagonistic fungi as a safer alternative for managing Ascochyta blight damage. In a field trial, the commercial product Biocont-T, containing Trichoderma harzianum, was applied as a pre-planting treatment and mixed with peat moss at various rates. The experiment followed a randomized complete block design (RCBD) and was replicated three times. Results indicated that the most effective treatment inhibiting the disease (55.55%) involved a peat-based soil inoculation mixture containing 20.8 kg/ha of Biocont-T and 2083 kg/ha of peat moss (T3). This was followed by T1 (20.8 kg/ha of Biocont-T), which inhibited the disease by 52.77%, T2 (41.66 kg/ha of Biocont-T) with a 41.66% inhibition rate, and T6 (1041.66 kg/ha of pre-inoculated peat moss with the bioagent for one week), also with a 41.66% inhibition rate. In conclusion, while using T. harzianum as a biocontrol agent did not completely eradicate the disease, it proved an effective method with no adverse environmental effects.

The objective of this study was to assess the impact of freezing and refreezing temperatures, as well as the duration of frozen storage, on fatty acid and amino acid profiles, and the oxidative stability of lipids and proteins in broiler breast meat. Forty broiler breast muscle samples were divided into two primary groups. The first group was subdivided into three equal sections, each subjected to freezing durations of 0, 30, 60, and 90 days. The second group underwent freezing cycles for 30, 60, and 90 days, followed by overnight thawing at 4 °C. Refreezing intervals of 0, 30, 60, and 90 days were then implemented before the meat quality assessment. The results showed a significant reduction (P < 0.05) in essential amino acids, such as lysine, threonine, and valine, in broiler breast meat samples. These reductions were observed after 30, 60, and 90 days of freezing in the first group and following two or three cycles of freezing and refreezing in the second group. Non-essential amino acids such as tyrosine and arginine showed no significant reduction during all refreezing intervals. Fatty acids exhibited a significant decline (P < 0.05), including saturated and monounsaturated fatty acids, but linoleic acid remained stable across all storage durations.Lipid and protein oxidation levels increased steadily over time, particularly during prolonged storage and repeated freeze-thaw cycles. These findings indicate that extended freezing and refreezing negatively affect the amino acid and fatty acid profiles, contributing to a decline in broiler meat quality.

A field study was done in two locations, Grdarasha and Qlyasan. The experiment included three factors, the first factor was Nano-NPK spraying with 4 concentrations (0, 150, 300, and 450) µg cm-3, the second factor was two periods of spraying according to Zadoks scale Z-21 and Z-43 and the third factor was two bread wheat cultivars (C1 = Adana-99 and C2= Aras). Numerous quantitative and qualitative parameters were studied. The mentioned factors showed a positive role, the fertilization treatments of 450 µg cm-3 recorded the highest values of plant height (96.17 and 73.24) cm, flag leaf area (33.19 and 33.04) cm2, number of grain spike-1 (48.76 and 41.78), weight of grain spike-1 (1.95 and 1.54) g, seed index (38.54 and 39.35) g, grain yield (4.93 and 4.84) t ha-1 and protein yield (707.28 and 609.46) kg ha-1 for both locations respectively. Spraying the Nano - fertilizer at the second stage had significant impact on some traits, the highest values in flag leaf area, no spikelet spike -1, seed index, grain yield and protein yield was (30.83 and 32.17) cm2, (17.57 and 17.60), (37.10 and 39.16) g, (4.49 and 4.34) t ha-1and (621.86 and 533.70) kg ha-1. In contrast, the second cultivar Aras surprised Adana in most of the traits. The interaction treatments (450 mg L-1x Booting stage x Ara's cultivars) recorded the highest seed and protein production (5.29 and 5.71) t ha-1 seed yield and (763.29 and 717.27) kg ha-1 protein yield for both locations respectively. It is appeared from the three studied factors and their combination significant influences on most of the studied traits.

In the recent years, building boundary segmentation obtained significant advancement through using deep learning. The present algorithms, such as Convolutional Neural Network (CNN) are unable to detect buildings in challenging urban areas like occlusions. This study investigates the integration of U-Net and Fully Convolutional Networks (FCN) with Mask R-CNN to improve building boundary segmentation using high-resolution satellite imagery. A sequential hybrid approach has been developed for combining semantic and instant segmentation. The integration between the U-Net with Mask R-CNN has been achieved by feeding the segmentation result from the U-Net as an input into the Mask R-CNN. A similar procedure was applied in the integration of the FCN with Mask R-CNN. The integration of U-Net with Mask R-CNN resulted in an improvement in the recall by 9.9% and an increase by 4.3 % in the F1-score, demonstrating its capability in segmenting boundary precision and fine-grained details. Similarly, FCN combined with Mask R-CNN has shown an enhancement of recall by 9.9% and precision by 7.6%, assuring its capability in the capture of global context. Further analysis through comparison between integration U-Net with Mask R-CNN with results from previous studies, demonstrates that the proposed integration scheme outperforms the existing results. The performance evaluation across RGB and panchromatic datasets highlights the flexibility of these integrations by proving their efficiency in different applications. Despite the minor challenges that appeared in boundary alignment, the results brought out the potential of such hybrid models for applications in urban planning, cadastral mapping, and disaster management.

Linear electrical power generation is one of the methods to generate electrical power from linear moving forces with zero unwanted CO and NO emissions. Such power source can be harvested from linear moving systems such as oscillating engines (the so called free – piston engine), sea and ocean tides and waves. The linear generator is the major part responsible of generating the electrical power from the combined driving linear system and the generator as its load. Such electrical machines are found vastly in three – phase fashion. At first the linear generator in its five – phase mode is modelled, optimised and analysed. Then, the generator mass, cost and running features are investigated and compared with an existing three – phase machine. Few weak points have emerged in the selected five – phase machine models although better operational features have been harvested compared with the base three – phase linear generator model.