Physics
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- ItemWind Speed Prediction Using Machine Learning Algorithms: A Case Study of Using ANFIS and KNNR(Al-Quds University, 2023-07-26) Khalil Shiban Mahmoud Abuayyash; خليل شيبان محمود ابو عياشWind speed prediction using machine learning algorithms is crucial for various applications, such as wind energy planning and urban development. This paper presents a case study on wind speed prediction in Jerusalem using the Adaptive Neuro-Fuzzy Inference System (ANFIS) and K-Nearest Neighbors Regression (KNNR) algorithms. The study evaluates their performance using multiple metrics, including root mean square (RMSE), bias, and coefficient of determination R2. ANFIS demonstrates good accuracy with lower RMSE (0.196) and minimal bias (0.0003). However, there is room for improvement in capturing overall variability (R2 = 0.15). In contrast, KNNR exhibits a higher R2 (0.4093), indicating a better fit, but with a higher RMSE (1.4209). This study provides insights into the applicability of ANFIS and KNNR in wind speed prediction for Jerusalem and suggests future research directions. The outcomes have practical implications for wind energy planning, urban development, and environmental assessments in similar regions.
- ItemMeasurement of Radioactivity in Some Liquid Foodstuffs Samples Collected from Palestinian Markets(Al-Quds University, 2023-07-26) Anwar Mohammad Ali Al-Jaradat; أنوار محمد علي الجراداتRadon has been identified as one of mankind's health dangers because long-term radon exposure raises the risk of getting lung cancer. The objectives of this thesis to measurement the concentration of radon and radium in 57 samples of liquid foodstuffs collected from different markets from West Bank and describes radioactivity as an alpha particle created by the decay of radium to radon, by using passive technique - Solid State Nuclear Detectors SSNTDs (CR39) which were etched chemically after 90 days of exposure by using 6.25 M of NaOH at 〖70〗^°, then optical microscope was used to calculate the average number of tracks per unit area then calculated the radon concentrations , the effective radium contents, the annual effective Dose for inhalation and ingestion of radon and effective dose equivalent.This study showed the results of both the concentration of radon and radium, and it was as follows; The results of radon concentration levels in fruit juice samples are getting between 51.0 Bq/m^3 to 278.8 Bq/m^3 and the concentration of radium getting between 0.714 Bq⁄kg to 3.90 Bq⁄kg . The results of radon concentration levels in milk samples are getting between 61.2 Bq/m^3 to 258.4 Bq/m^3 , the concentration of radium getting between 0.85 Bq⁄kg to 3.61 Bq⁄kg with average 2.6 Bq⁄kg . The results of levels of radon concentration in soft drinks and other liquid foodstuffs samples are getting between 64.6Bq/m^3 to 224.4 Bq/m^3 , and the concentration of radium getting between 0.90 Bq⁄kg to 3.14 Bq⁄kg . The obtained values show that the levels of radon and radium concentration of all samples are less than the safe limits as recommended by ICRP, there is no health hazards related to radiation.
- ItemWind Speed Prediction Using Machine Learning Algorithms: A Case Study of Using ANFIS and KNNR(2023) hKhalil Shiban Mahmoud Abuayyash; خليل شعبان محمود ابو عياشWind speed prediction using machine learning algorithms is crucial for various applications, such as wind energy planning and urban development. This paper presents a case study on wind speed prediction in Jerusalem using the Adaptive Neuro-Fuzzy Inference System (ANFIS) and K-Nearest Neighbors Regression (KNNR) algorithms. The study evaluates their performance using multiple metrics, including root mean square (RMSE), bias, and coefficient of determination R2. ANFIS demonstrates good accuracy with lower RMSE (0.196) and minimal bias (0.0003). However, there is room for improvement in capturing overall variability (R2 = 0.15). In contrast, KNNR exhibits a higher R2 (0.4093), indicating a better fit, but with a higher RMSE (1.4209). This study provides insights into the applicability of ANFIS and KNNR in wind speed prediction for Jerusalem and suggests future research directions. The outcomes have practical implications for wind energy planning, urban development, and environmental assessments in similar regions.
- ItemComparison between Monte Carlo Simulations, The estimates of the Mean Particle Theory and Observations of H^+ and O^+ Outflows at High Latitudes.(Al-Quds University, 2023-05-22) May Rajab Halaika; مي رجب حلايقةIn this thesis we make a comparison between the results of Monte Carlo simulations, mean particle theory, and observations in different regions of earth magnetosphere (aurora, polar wind, central polar cap and, cusp) for 〖 H〗^+ and 〖 O〗^+ ions outflow at high latitudes and altitudes. We present altitude profiles for mean perpendicular energy W_Ʇ , mean parallel energy W_‖ and, total mean energy W_total. Monte Carlo simulations are obtained by using Barghouthi model [Barghouthi, 2008], mean particle theory estimates are obtained by using Retterer et al. [1987a], and observations are obtained from different available studies. As a results of comparisons in different regions we have found that; 1) Monte Carlo simulations and Mean particle theory gives similar results in auroral regions and produce no agreement in polar wind region, 2) comparison with observations in polar wind region and auroral region gives excellent agreement in aurora and good agreement in polar wind, 3) it is appropriate to use altitude and velocity diffusion coefficients in auroral and polar wind regions, because of that we have obtained reasonable results, 4) in the central polar cap and cusp we have obtained excellent agreement for both methods and observations, 5) due to these comparisons we can claim that the wave length of the electromagnetic wave existed in those regions is 8km
- ItemSynthesis, Characterization, and Antibacterial Activity of Ciprofloxacin Prodrugs(Al-Quds University, 2023-05-20) Shorouq Shalan Ahmad Faroun; شروق شعلان أحمد فرعونThe increasing problem of antibiotic resistance highlights the critical need for the development of new antibiotics. Bacterial resistance has wide-ranging consequences, including the potential for longer and more severe infections, heightened rates of illness and death, and escalated healthcare expenses. In certain instances, infections caused by antibiotic-resistant bacteria can become untreatable, severely limiting effective treatment options. This poses a significant public health threat, as the management of common bacterial infections becomes more challenging and the risk of spreading resistant strains to others intensifies. In the market and industry of antibiotics, the development of new antibiotics faces significant challenges. The process of bringing a new antibiotic to market has become increasingly slow and complex, with an average timeframe of a decade or more. The rise of antibiotic resistance has necessitated a continuous search for novel solutions to combat infectious diseases effectively, and conventional methods for discovering antibiotics have largely run their course. Despite these obstacles, there are still chances to find new antibiotics by using medicinal chemistry and computational chemistry to create novel prodrugs as the prodrug strategy has been frequently used as a chemical approach for the enhancement of certain disadvantages of parent drugs. In this thesis, two amide prodrugs have been synthesized of the anti-infective agent Ciprofloxacin, and their potential advantages in fighting bacteria over the respective parent compound have been demonstrated. The two novel prodrugs of Ciprofloxacin (ProD1 and ProD2) were synthesized to improve the antibiotic spectrum of the parent drug. The research details the synthesis of the prodrugs using the linkers cis-5-Norbornene-Endo-2,3-Diarboxylic Anhydride, and di-methyl-Maleic Anhydride respectively, utilizing nucleophilic acyl substitution. The final products of the produced prodrugs were obtained as powders and in high yields. Furthermore, they were characterized using melting point, and chromatographic methods in which UPLC, FT-IR, and 1H-NMR analysis were carried out. The in vitro susceptibility for both prodrugs was determined against Escherichia coli, staphylococcus aureus, and pseudomonas, and compared to that of the parent drug Ciprofloxacin, using disc diffusion method, and broth diffusion method. The results demonstrated that both novel prodrugs exhibited superior efficacy compared to their parent drug in combating pseudomonas and E. coli infections. Furthermore, when administered at higher doses, they also displayed effectiveness against staphylococcus aureus. It is worth noting that those two novel prodrugs are stable compounds as they exert the antibiotic effect themselves without the need to undergo conversion to their corresponding parent drugs. The novel prodrugs exhibit their antibacterial activity against different types of bacterial strains due to the presence of the 4-pyridone ring with a 3- carboxylic acid group substitution on their structures. يعد اكتشاف مضادات حيوية جديدة أمرًا بالغ الأهمية و حاجة ملحة، في ضوء المشكلة المتزايدة لمقاومة المضادات الحيوية المتوفرة. حيث أن لمقاومة البكتيريا للمضادات الحيوية المتواجدة تبعات واسعة النطاق، بما في ذلك احتمالية حدوث عدوى طويلة الأمد وأكثر شدة، وارتفاع معدلات المرض والوفيات، وتزايد تكاليف الرعاية الصحية. وفي بعض الحالات، يمكن أن تصبح العدوى الناجمة عن البكتيريا المقاومة للمضادات الحيوية لا يمكن علاجها، مما لا يترك خيارات متاحة لعلاج فعال. وهذا يشكل تهديداً كبيراً للصحة العامة، حيث تصبح إدارة العدوى البكتيرية الشائعة أكثر تحديًا ويزيد خطر انتشار سلالات مقاومة للمضادات الحيوية إلى الآخرين. في سوق وصناعة المضادات الحيوية، يواجه تطوير المضادات الحيوية الجديدة تحديات كبيرة. أصبحت عملية إطلاق مضاد حيوي جديد في السوق أكثر بطئًا وتعقيدًا، مع متوسط فترة زمنية تستغرق عقدًا من الزمان أو أكثر. ارتفاع مقاومة المضادات الحيوية قد استدعى إلى البحث المستمر عن حلول جديدة لمكافحة الأمراض المعدية بفعالية، وأصبحت الطرق التقليدية لاكتشاف المضادات الحيوية قد استنفذت معظم إمكاناتها. على الرغم من هذه العقبات، لا تزال هناك فرص لاكتشاف مضادات حيوية جديدة باستخدام الكيمياء الدوائية والكيمياء الحاسوبية لإنشاء طلائع مضادات حيوية جديدة، حيث تم استخدام استراتيجية تصنع الطلائع الدوائية لتحسين بعض عيوب العقاقير الأصلية. في هذه الأطروحة، تم تخليق اثنان من طلائع الأميد لدواء سيبروفلوكساسين المستخدم كمضاد بكتيري باستخدام cis-5-Norbornene-Endo-2,3-Diarboxylic Anhydride, and di-methyl-Maleic Anhydride عن طريق nucleophilic acyl substitution ، وتم إظهار مزاياهما المحتملة في مكافحة البكتيريا مقارنة بالمركب الأم. أثناء قراءتك للعمل، ستجد توصيفًا دقيقا يشرح طريقة تخليق هذه المركبات الدوائية، بالاضافة إلى توصيفٍ لهذه المركبات عن طريق تحليلها باستخدام بعض الفحوصات المعياريةفي الابحاث مثل درجة الانصهار و تقنيات الفصل اللوني (الفصل الكروماتوغرافي) مثل UPLC و FT-IR و 1H-NMR وتم الحصول على المنتجات النهائية للطلائع بشكل مسحوقي بعائد عالٍ. تم تحديد الحساسية في المختبر لكلا المشتقتين بالنسبة لثلاث أنواع من البكتيريا: Escherichia coli, Staphylococcus aureus, and Pseudomonas ومقارنتها بتلك للمركب الأم سيبروفلوكساسين، باستخدام طريقتي: Disc diffusion method and broth diffusion method . أظهرت النتائج أن كلا المشتقتين الجديدين تفوقا بفاعلية على المركب الأم في مكافحة العدوى Escherichia coli و Pseudomonas. علاوة على ذلك، عندما تم إعطاؤها بجرعات أعلى، أظهرت فعالية أيضًا ضد Staphylococcus aureus. يجدر بالذكر أن هذه الطلائع الجديدة هي مركبات مستقرة، حيث يظهر تأثير المضاد الحيوي بذاته دون الحاجة إلى التحول إلى المركبات الأم.