A Simulation Study of Pilots\u27 Ability to Perceive Angular Motion under the Influence of Alcohol

The study consisted of experimental research to determine the effect of alcohol on the pilots’ ability to perceive angular motion. It was hypothesized that in the absence of visual cues, pilots’ thresholds of perceiving a change in angular motion is adversely affected by alcohol in the blood, thereby increasing the potential to enter a state of spatial disorientation. The experiments were designed to simulate a real time in-flight scenario, in a rotating flight simulator, where angular accelerations could be controlled and pilots’ thresholds of perceiving a change in angular motion could be measured. The study revealed that the subjects registered a significant deterioration of their ability to perceive a change in angular motion at low Blood Alcohol Contents (BA

Evading Lyth bound in models of quintessential inflation

Quintessential inflation refers to an attempt to unify inflation and late-time cosmic acceleration using a single scalar field. In this letter we consider two different classes of quintessential inflation, one of which is based upon a Lagrangian with non-canonical kinetic term $k^2(\phi)\partial^\mu \phi \partial_\mu \phi$ and a steep exponential potential while the second class uses the concept of steep brane world inflation. We show that in both cases the Lyth bound can be evaded, despite the large tensor-to-scalar ratio of perturbations. The post-inflationary dynamics is consistent with nucleosynthesis constraint in these cases.Comment: 6 Latex pages, no figures, reference updated and typos corrected, To appear in PL

Determining and modeling the dispersion of non point source pollutants in Lake Victoria: A case study of Gaba Landing site in Uganda

Lake Victoria is an important source of livelihood that is threatened by rising pollution. In this study, pollutants in runoff are characterized and their dispersion after they enter the lake is measured and modeled at different points in the study areas. The objective is to develop a one dimensional mathematical model which can be used to predict the nutrient (ammonia, nitrite, nitrate, and phosphate) dispersion distances within the lake. A comparison between rain period nutrient concentrations and dry period nutrient concentrations within the Lake showed an elevation in nutrient levels during the rainy season, with exception of nitrate. However, nitrate had high levels during the dry season. Ammonia was found to disperse to horizontal distances of 38 m; nitrite 45 m, with nitrate and phosphate each attaining distances of 34 m. Measured nutrient concentration within the Lake compared well with model estimations.Key words: Modeling, water quality, nutrients, lake Victoria

Processing of Polymers Stress Relaxation Curves Using Machine Learning Methods

حاليًا، أحد المجالات الموضوعية لتطبيق طرق التعلم الآلي هو التنبؤ بالخصائص المادية. الهدف من هذا العمل هو تطوير نماذج التعلم الآلي لتحديد الخصائص الريولوجية للبوليمرات من منحنيات استرخاء الإجهاد التجريبية. تقدم الورقة لمحة عامة عن الاتجاهات الرئيسية للنهج الميتاهويرية (البحث المحلي، والخوارزميات التطورية) لحل مشاكل التحسين التوافقي. يتم وصف الخوارزميات الميتاهورية لحل بعض مشاكل تحسين التوافقية المهمة، مع التركيز بشكل خاص على بناء أشجار القرار. تم إجراء تحليل مقارن للخوارزميات لحل مشكلة الانحدار في CatBoost Regressor. . الهدف من الدراسة هو مجموعات البيانات المتولدة التي تم الحصول عليها على أساس منحنيات استرخاء الإجهاد النظرية. وترد جداول البيانات الأولية لنماذج التدريب لجميع العينات، ويجري تحليل إحصائي لخصائص مجموعات البيانات الأولية. كان العدد الإجمالي للتجارب العددية لجميع العينات 346020 اختلافًا. عند تطوير النماذج، تم استخدام طرق CatBoost للذكاء الاصطناعي، وتم استخدام طرق التسوية (تحلل الوزن، وتسوية الوزن المفصول، وزيادة) لتحسين دقة النموذج، وتم استخدام طريقة Z-Score لتطبيع البيانات. نتيجة للدراسة، تم تطوير نماذج ذكية لتحديد المعلمات الريولوجية للبوليمرات المدرجة في معادلة ماكسويل-غوريفيتش غير الخطية المعممة (لزوجة الاسترخاء الأولية، وحدة السرعة) باستخدام مجموعات البيانات المولدة لرابط الإيبوكسي EDT-10 كمثال. بناءً على نتائج اختبار النماذج، تم تقييم جودة النماذج، ورسم رسوم بيانية للتنبؤات للمتدربين وعينات الاختبار، ورسوم بيانية لأخطاء التنبؤ. تستند النماذج الذكية إلى خوارزمية CatBoost ويتم تنفيذها في بيئة دفتر المشتري في بايثون. اجتازت النماذج المشيدة تقييم الجودة وفقًا للمقاييس التالية: MAE و MSE و RMSE و MAPE. كانت القيمة القصوى لتنبؤات خطأ النموذج 0.86 لمقياس MAPE، والقيمة الدنيا لتنبؤات خطأ النموذج كانت 0.001 لمقياس    MSE. تقديرات أداء النموذج التي تم الحصول عليها أثناء الاختبار.Currently, one of the topical areas of application of machine learning methods is the prediction of material characteristics. The aim of this work is to develop machine learning models for determining the rheological properties of polymers from experimental stress relaxation curves. The paper presents an overview of the main directions of metaheuristic approaches (local search, evolutionary algorithms) to solving combinatorial optimization problems. Metaheuristic algorithms for solving some important combinatorial optimization problems are described, with special emphasis on the construction of decision trees. A comparative analysis of algorithms for solving the regression problem in CatBoost Regressor has been carried out. The object of the study is the generated data sets obtained on the basis of theoretical stress relaxation curves. Tables of initial data for training models for all samples are presented, a statistical analysis of the characteristics of the initial data sets is carried out. The total number of numerical experiments for all samples was 346020 variations. When developing the models, CatBoost artificial intelligence methods were used, regularization methods (Weight Decay, Decoupled Weight Decay Regularization, Augmentation) were used to improve the accuracy of the model, and the Z-Score method was used to normalize the data. As a result of the study, intelligent models were developed to determine the rheological parameters of polymers included in the generalized non-linear Maxwell-Gurevich equation (initial relaxation viscosity, velocity modulus) using generated data sets for the EDT-10 epoxy binder as an example. Based on the results of testing the models, the quality of the models was assessed, graphs of forecasts for trainees and test samples, graphs of forecast errors were plotted. Intelligent models are based on the CatBoost algorithm and implemented in the Jupyter Notebook environment in Python. The constructed models have passed the quality assessment according to the following metrics: MAE, MSE, RMSE, MAPE. The maximum value of model error predictions was 0.86 for the MAPE metric, and the minimum value of model error predictions was 0.001 for the MSE metric. Model performance estimates obtained during testing are valid

Kinetics Study of the Formation of Pyrmidine Thione from the Reaction of 2,6-dibenzylidinecyclohexanone and its Derivatives with Thiourea

Kinetics of the addition of thiourea to 2,6-dibenzylidenecyclohexanone and its derivatives have been studied. The reaction is found as a pseudo-first order process which includes a nucleophilic attack by thiourea at the carbonyl group of the ketone system to produce the heterocyclic pyrimidine thione "thiopyrimidine" (Claisen route mechanism). The effect of the substituents at the para position of the 2,6-dibenzylidenecyclohexanone and its derivatives on the rate of reaction, at different temperatures, is studied. Arrhenius parameters, entropies, enthalpies and free energies of activations are estimated. A suitable mechanism, which is correspondent with the results and with Claisen routes mechanism, is suggested for this reaction