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    WALKABILITY IN URBAN AREAS AND INFLUENCING FACTORS; RAFIDIA STREET - NABLUS, AS A CASE STUDY
    (An-Najah National University, 2024-10-29) Zaki, Alawneh
    Walkability is a crucial component of sustainable urban development, directly influencing the quality of life by promoting pedestrian mobility, reducing traffic congestion, and enhancing environmental health. This study explores walkability by examining the essential elements and indicators that influence pedestrian movement and accessibility in urban areas. It introduces a comprehensive walkability index designed to assess and quantify these factors, offering a standardized framework for evaluating walkability across various settings. In developing countries, the walking environment is ignored due to a variety of factors, including financial constraints, lack of policies and studies on influencing factors on, and negligence of society and decision-makers regarding this mode of urban mobility. Walking in different land uses, like city center, commercial area, or residential area, is not always safe due to different factors, including lack of pedestrian facilities. The methodology was developed by integrating 10 elements, 29 indicators, and 80 sub-indicators to evaluate walkability. The elements and indicators were weighted by experts. Furthermore, data was gathered using various methods, including questionnaires, field observations, and aerial photographs. Both qualitative and quantitative data were converted into measurable quantitative scores, ranging from 0 to 1. Analysis showed that the walking environment in Rafidia street has several weaknesses. These issues stem from factors such as poor organization, linear layout, lack of attention to pedestrian facilities, and inadequate distribution of services. Additional contributing factors include the inconsistency of road right-of-way throughout the area, the absence of barriers separating pedestrians from vehicles, and the lack of a key element streetscape design. This study not only presents a detailed analysis of walkability in Rafidia Street, but also offers practical solutions to improve pedestrian experiences in urban areas. By developing a clear framework for assessing and enhancing walkability, the study contributes to the broader efforts of creating sustainable, livable cities that prioritize pedestrian mobility.
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    TECHNO-ECONOMIC ANALYSIS OF A HYBRID CSP-PV SYSTEM INTEGRATED WITH THERMAL STORAGE IN PALESTINE
    (An-Najah National University, 2024-10-09) Kmail, Ahmad
    This thesis conducts a techno-economic analysis of a hybrid Parabolic Trough Concentrated Solar Power (CSP) and Photovoltaic (PV) system for electricity generation in Palestine. It aims to assess the feasibility, and performance of combining CSP and PV technologies to address Palestine’s energy challenges. The study begins with an assessment of solar power potential in Palestine, adopting the governorate of Jericho as a case study. The hybrid system is, aimed to maximize the benefits provided by both CSP and PV, availability of power around the clock, and increased efficiency. Technical and economic assessments for each technology are performed using the System Advisor Model software to analyze capacity factor, energy production, cost life cycle analysis, and economic parameter analysis including Levelized cost of energy (LCOE), internal rate of return (IRR), and Payback period (PP) for the hybrid system. The analysis is conducted under two scenarios: supplying a baseload and load following, to measure the system performance and economic flexibility under varying conditions. Assessments of environmental impacts are certainly part of the procedure regarding estimating the avoided carbon dioxide (CO2) emissions by adopting the hybrid system. The results show that utilizing a hybrid CSP-PV system has advantages over standalone systems in terms of increased energy output, reliability, and cost. In particular, the inclusion of thermal energy storage in CSP enhances the system's flexibility and reliability which makes it a feasible option for developing clean energy in Palestine. The economic analysis reveals that the hybrid system achieves an LCOE of 11.72 cent/kWh, an IRR of 13.35%, and a PP of 7 years under the load following scenario, with similar positive outcomes under the base load scenario. Additionally, the hybrid system is projected to avoid approximately 5,011.01 tons of CO2 emissions annually.
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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.