Natural Sciences

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https://hdl.handle.net/20.500.11888/18293

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    A HYBRID DEEP LEARNING MODEL FOR FORECASTING PM2.5 AIR POLLUTANT CONCENTRATIONS
    (An-Najah National University, 2024-12-18) Massad, Asma
    Air quality forecasting is a crucial research field that aids scientists and policymakers in making informed decisions to combat air pollution. Among various pollutants, PM2.5 -particulate matter with a diameter smaller than 2.5 micrometers- poses significant health risks, as it can reach the lower respiratory tract and enter the bloodstream. Accurately forecasting PM2.5 levels is thus essential. Although machine learning-based spatiotemporal forecasting models have advanced, the pursuit for more accurate forecasts continues. The use of hybrid deep learning models for PM2.5 forecasting represents a promising and active area of research, as these models aim to capture complex spatiotemporal dependencies more effectively. We developed a Dynamic Graph Attention Network (DyGAT) to model spatial dependencies effectively. DyGAT leverages engineered edge features, including distance, wind speed, and wind direction, while using attention mechanisms to capture the dynamic nature of these dependencies. DyGAT was then combined with Informer, a Transformer for efficient time-series forecasting, to capture spatial and temporal patterns comprehensively, improving prediction accuracy. Our model was evaluated on a benchmark dataset from Beijing, with 420,768 records over four years. DyGAT-Informer outperformed a version without the DyGAT component and other baseline models. It achieved 50.43 for MAE, 79.9 for RMSE and 28.88% for SMAPE, compared to 51.44 for MAE, 80.83 for RMSE and 30.25% for SMAPE in the next best model. Additionally, we conducted a case study using a dataset from Nablus, Palestine, consisting of 2692 records per station over a two months period. We incorporated geospatial features about nearby pollution sources into the dataset. Due to the insufficient number of records in the Nablus dataset for training the Informer, it was replaced with a sequence-to-sequence Long Short-Term Memory (LSTM) model. DyGAT-LSTM, trained with additional geospatial features about nearby pollution sources, achieved a 2.08% reduction in MAE, 1.17% in RMSE, and 1.96% in SMAPE. This confirms the benefit of incorporating such data. Finally, despite the short distances between stations, DyGAT successfully captured spatial dependencies, where DyGAT-LSTM achieved a reduction of 3.13% in MAE, 1.48% in RMSE, and 3.67% in SMAPE when compared to the LSTM-only model.
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    3-AMINOIMIDAZO[1,2-a] PYRIDINE DERIVATIVES: SYNTHESIS AND ANTIMICROBIAL ACTIVITIES
    (An-Najah National University, 2024-12-18) Dragmeh, Osama
    Background: Worldwide, antimicrobial resistance continues to be a major public health issue. Novel antibacterials with improved activity characteristics are therefore in high demand. Antibacterial is one of the many pharmacological actions of imidazo[1,2-a]pyridines. These bioactive substances are the main ingredients of several widely marketed therapeutic medications, such as Alpidem and Zolpidem. Objectives: Creation of novel 3-amino-6-floroimidazo[1,2-a]pyridine derivatives and evaluation of their effectiveness against five bacterial strains. Methodology: The one-pot Groebke-Blackburn-Bienayme-Three Component Reaction (GBB-3CR) was used in the compound synthesis. Several spectroscopic methods, including infrared (IR), proton nuclear magnetic resonance (1H NMR), and carbon-13 nuclear magnetic resonance (13C NMR), were used to confirm the structure. The assessment of purity also makes use of the High-Performance Liquid Chromatography (HPLC) technology. To evaluate the compounds' effectiveness against S. aureus, S. epidermidis, K. pneumonia, P. aeruginosa, and E. coli, biological experiments were conducted on the produced compounds. Results: The seven synthetic compounds (85-91) were produced with a purity of 88-100%. These compounds (85-91) have been verified for their structural formula using 1H NMR, 13C NMR, and IR spectroscopy. These techniques indicate the GBB-3CR normal product. Biologically, compound 91 exhibited the best inhibitory behavior among the others; the lowest MIC value (15.625 µg/ml) was recorded for compound 91 against E. coli. Moreover, compound 91 works better than Gentamicin against K. pneumoniae. The same observation was reported for compounds 85 and 89 against S. epidermis. It is worth pointing out that compound 89 in this study kills E. coli and S. epidermis at lower concentrations (62.5 µg/mL) than Gentamicin antibiotics 125 µg/mL and 250 µg/mL, respectively. The same observation was noticed for compound 85 against S. epidermis with an MBC value of 62.5 µg/mL. Compounds 91, 89, and 85 have good antibacterial effects due to the substitution on C-2 of 3-amino-6-floroimidazo[1,2-a]pyridine scaffolds, which are 1-methylimidazole, p-trifluoromethylphenyl, and 3,5-dimethoxy-4-hydroxyphenyl, respectively. Conclusions: A straightforward, cost-effective, one-step process was used to create new, promising bioactive chemicals. Additional research on these derivatives might provide more potent compounds that show promise as innovative antibacterial treatment options.
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    ENHANCING THE EFFICACY OF A GROUND SOURCE HORIZONTAL HEAT PUMP BY CARBON NANOTUBES SUSPENDED IN WATER
    (An-Najah National University, 2025-01-09) Khoswan, Ibrahim
    This study explores enhancements in ground source horizontal heat pumps ((GSHHP)) by improving the heat transfer medium through nano-fluids. Researchers have used various types of carbon nanotubes (CNTs) in water. Both functionalized single-walled, Multiwalled carbon nano tubes ((MWCNT)s) with Tween 80 as a surfactant provided optimal suspension, while multi-walled CNTs achieved a 126% increase in thermal conductivity after sonication. Effects of various parameters, like concentration, shape factor, temperature, viscosity, aspect ratio, and added surfactant were studied. The result for (MWCNT) at the thermal conductivity increased with the concentration of (MWCNT) using Tween 80 using 10-60-minute sonication for each sample, no extra suspension would happen beyond that time, and the suspension concentration became saturated. The Thermal conductivity of (SWCNT)-water suspension was less for the same concentration (10% wt.) to reach k(SWCNT)nf= 0.77 W/m.K with a 28% improvement compared to water thermal conductivity kw = 0.6 W/m.K. Those results were better compared to the literature. The results revealed that smaller concentrations of (SWCNT) will be needed, which lowers both capital and running costs. making the system eco-friendlier. The concentration of CNTs influenced the specific heat capacity of the water-based nano-fluid. Higher CNT concentrations led to enhanced thermal conductivity but had mixed effects on specific heat capacity, diverging from typical predictions in the literature((SWCNT)s), ((MWCNT)s) impacted the specific heat differently. (MWCNT)s showed a more noticeable effect on increasing thermal conductivity, though the specific heat enhancement was less pronounced for (SWCNT)s at similar concentrations. Sonication time and the use of a surfactant (Tween 80) affected CNT dispersion in water. A simulation study further verified the experimental findings in both thermal conductivity and specific heat. New models of our experimental data were developed in this dissertation to predict specific heat thermal conductivity enhancement as a function of CNT concentration and nano-fluid properties. These models offered a more accurate estimation of specific heat changes compared to earlier theoretical models which were inaccurate. Also, the simulation of ((GSHHP)) described a qualitative model to rationalize the effects of (CNTs) on nano-fluid conductivity.
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    UTILIZING MODIFIED KAOLINITE FOR PHENAZOPYRIDINE REMOVAL THROUGH ADSORPTION AND SUBSEQUENT THERMOLYSIS DECOMPOSITION
    (An-Najah National University, 2024-11-21) Salman, Sahar
    In this study, modified kaolinite was utilized as an adsorbent for the elimination of phenazopyridine hydrochloride (PhPy) and methyl orange (MO) dyes from aqueous solutions. Various parameters, such as the effects of different concentrations of adsorbate, the amount of adsorbent, the solution pH, and the temperature, have been studied and analyzed using UV-Vis. When the concentration decreased, the adsorption increased and was affected by the amount of modified kaolinite until the equilibrium level was reached. The ideal pH value for PhPy adsorption was 5, but for MO, it was 2, and equilibrium adsorption was established within the first fifteen minutes. Additionally, the adsorbed PhPy and MO clearly decreased when the temperature increased, suggesting exothermic adsorption. Kinetic models were used to analyze the experimental data to illustrate the kinetic adsorption process. The PhPy and MO adsorption processes followed pseudo second-order kinetics. The data were resolved via the most common adsorption isotherms, i.e., the Langmuir and Freundlich isotherms, and the adsorption process fit well with the Langmuir isotherm model for both dyes. The activation energy of PhPy and MO adsorption on the modified kaolinite was estimated. The results confirmed that the process was followed physical adsorption. Characterization of the modified kaolinite was essential in perception its adsorption properties. X-ray diffraction (XRD) analysis was used to determine the crystalline structure and emphasize the successful modification of kaolinite. XRD patterns provided insights into changes in the interlayer spacing, indicating interactions between the kaolinite and ZnCl2. Scanning electron microscopy (SEM) was utilized to analyze the surface morphology and observe the textural changes caused by the modification process. SEM images revealed an increase in surface roughness and porosity. Thermogravimetric analysis (TGA) was utilized to evaluate the thermal stability and decomposition behavior of the modified kaolinite. TGA curves demonstrated the material's resistance to thermal degradation up to specific temperatures, confirming its suitability for regeneration for four cycles through thermal decomposition at 600 °C for PhPy and MO without impacting adsorption efficiency. Fourier transform infrared (FT-IR) spectroscopy was utilized to further confirm the adsorption process and assess the interaction between the dyes and the modified kaolinite. The FT-IR spectra revealed shifts or changes in specific functional group vibrations, indicating the adsorption of PhPy and MO onto the kaolinite surface. FT-IR also provided evidence of the thermal decomposition process by identifying changes in the functional groups of the adsorbed dyes after thermal treatment at 600 °C. The disappearance of peaks associated with organic functional groups from PhPy and MO in the post-regeneration FT-IR spectra validated the successful decomposition of the adsorbed dyes and the regeneration of the modified kaolinite surface for reuse.
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    THE EFFECT OF GREEN SUPPLY CHAIN MANAGEMENT PRACTICES AND SUSTAINABLE PERFORMANCE ON THE CONSTRUCTION INDUSTRY IN PALESTINE: A CONCEPTUAL FRAMEWORK
    (An-Najah National University, 2024-11-23) Sharqawi, Shurouq
    Green supply chain management (GSCM) has been a highly studied topic as it integrates the environmental aspects into traditional supply chain management concepts. As the construction industry is one of the biggest industries worldwide with tremendous and complex activities and influencing parties, greening the supply chain of this industry will enhance the sustainable performance of the companies and parties working within this industry. This study presents an overview of GSCM practices in the Palestinian construction market and explores the relationship between GSCM practices and sustainable performance (SP), considering the effect of institutional pressures as a moderator on this relationship. A conceptual framework was developed according to the findings of previous studies to identify the primary constructs and their indicators. Data were collected through a structured questionnaire and distributed to a random sample; 97 responses were gathered from different stakeholders working in the construction industry in the West Bank. Smart-PLS 4.0 software analyzed the data through partial least squares structural equation modeling (PLS-SEM). The results of this study reveal that GSCM practices, SP, and institutional pressures have high implementation levels among the targeted sample. A significant position relationship was confirmed between GSCM practices and SP. Additionally, it was found that institutional pressures have a negative significant moderating effect on the relationship between GSCM practices and SP. To the best knowledge of the researcher; this study is considered the first study connecting the GSCM practices with the SP, considering the moderating effect of institutional pressures in the construction industry. Additionally; theoretical and practical implications were also included in this study along with a managerial framework. Finally, the study limitations and future research recommendations were covered in the last section.