The performance in the 110-meter hurdles at the sprint hurdles event is determined by several physical and physiological qualities. Nonetheless, relatively little attention has been paid to the predictability of such factors in determining race performance. This study seeks to fill this gap by establishing the most critical physical and physiological characteristics affecting elite hurdlers’ performance and creating a statistical model that predicts race times from the identified measurable characteristics. The study utilized a descriptive research design in-volving six elite male hurdlers, all of whom completed a battery of standardized physical and functional tests to assess their explosive lower-body strength, agility, reaction time, and anaerobic capacity. Vertical jump height, zigzag agility test results, reaction time, and shuttle run endurance were examined using validated sports per-formance assessment protocols. A multiple linear regression analysis was then performed to create a model for 110-meter hurdle race times based on these attributes. The findings demonstrated that 97% of the variation (R² = 0.970) in performance over the hurdles could be explained by four variables: vertical leap (explosive power), zigzag agility (change-of-direction speed), reaction time and anaerobic endurance; this made it one of the most predictive models created for this event. the findings of this study can be an endorsement for integrated sprint hurdle training spanning the broad spectrum of qualities — explosive strength, agility, and neuromuscular re-sponse times — that affect sprint hurdles performance. Anyway, the results highlight the prioritization of an-aerobic stamina to ensure the maintenance of high intensity over time in the race. Future research should in-clude larger and more diverse athlete populations to enhance model strength. Furthermore, the implementation of machine learning methods such as artificial neural networks could enhance the accuracy of the model by identifying non-linear relationships among biomechanical, physiological and psychological variables. The ad-vancements in motion-capture systems, muscle activation analysis, and psychological profiling would drastical-ly increase how we assess athletes and continuously push the frontiers of sports performance science.
n-Hexane conversion enhancement was studied by adding TCE (Trichloro-ethylene) on feed stream using 0.3%Pt/HY zeolite catalyst. All experiments were achieved at atmospheric pressure and on a continuous laboratory unit with a fixed bed reactor at a temperature range 240-270◦C, LHSV 1-3h-1, H2/nC6 mole ratio 1-4.
By adding 435 ppm of TCE, 49.5 mole% conversion was achieved at LHSV 1h-1, temperature of 270ºC and H2/nC6 mole ratio of 4, while the conversion was 18.3 mol% on the same catalyst without adding TCE at the same conditions. The activation energy decreased from 98.18 for pure Pt/HY zeolite to 82.83 kJ/mole by adding TCE. Beside enhancement the activity, selectivity and product distribution enhanced by providing DMB (Dimethyl b
The effect of the tensor term in the Skyrme interaction has been estimated in calculating the static and dynamic nuclear properties in sd and fp-shell model spaces nuclei. The nuclear shell gaps have been studied with different Skyrme parameterizations; Skxta and Skxtb with tensor interaction, SkX, SkM, and SLy4 without tensor interaction, and Skxcsb with consideration of the effect of charge symmetry breaking. We have examined the stability of N = 28 for 42Si and 48Ca. The results showed that the disappearance of the magicity occurs in the shell closure of 42Si. Furthermore, excitation energy, quadrupole deformation, neutron separation energy, pairing energy, and density profile have also been calculated. Quadrupole deformation indicates a
... Show MoreIn the hybrid coolingsolar systems , a solar collectoris used to convertsolar energy intoheat sourcein order to super heat therefrigerant leave thecompressor,andthisprocess helpsin the transformation ofrefrigerant state from gaseous statetothe liquid statein upper two-thirdsof thecondenserinstead of the lower two-thirdssuchas in thetraditional air-conditioning systems and this willreduce theenergyneeded torun the process ofcooling.In this research two hybrid air-conditioning system with an evacuated tube solar collector were used, therefrigerant was R22 and the capacity was 2 tons each.The tilt angle of the evacuated tube solar collector was changed and the solar collector fluid was replaced into oil instead of water.A comparison wasi
... Show MoreNew microphotometer was constructed in our Laboratory Which deals with the determination of Molybdenum (VI) through its Catalysis effect on Hydrogen peroxide and potasum iodide Reaction in acid medium H2SO4 0.01 mM. Linearity of 97.3% for the range 5- 100 ppm. The repeatability of result was better than 0.8 % 0.5 ppm was obtanined as L.U. (The method applied for the determination of Molybdenum (VI) in medicinal Sample (centrum). The determination was compared well with the developed method the conventional method.
Lowering specific energy consumption (SEC) in reverse osmosis (RO) plants is one of the most important criteria in water treatment industry. The present work focused on best suggested RO pilot plant configurations for minimizing specific energy consumption, finding the best configurations experimentally to recover the water with minimizing salts in permeate side in RO module, study the factors affecting the performance of single and two stage systems, TFC membrane is used in spiral wound module. Brackish water is used as feed solution with different concentrations (2000, 3000, 4000 and 5000 ppm). The operating parameters studied were permeate flux, rejection and SEC. The experimental results showed the permeate concentration increased and w
... Show MoreDeep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod
... Show MoreObjective: The aim of this study was to develop a bioadhesive gel of gatifloxacin for the treatment of periodontal diseases.Methods: Periodontal gels of gatifloxacin were prepared using different hydrophilic polymers such as carbopol 940 (CP 940), carboxymethyl cellulose (CMC) and hydroxypropylmethyl cellulose (HPMC) in varied concentrations, either alone or as a combination. The prepared gels were evaluated for their physical appearance, pH, drug content, viscosity, bioadhesiveness and in vitro drug release profile. The influence of the type and the concentration of polymer on the drug release as well as on viscosity and mucoadhesiveness of prepared gels were investigated.Results: The prepared gels showed acceptable physical proper
... Show MoreDespite widespread agreement on the beneficial nature of hydrated lime (HL) addition to asphalt concrete mixes, understanding of the effect of HL particle size is still limited. Previous investigations have focused mainly on two different size comparisons, and so certain guidance for a practical application cannot yet be produced. This study investigates three distinct sizes of HL, in the range of regular, nano, and sub-nano scales, for their effects on the properties of modified asphalt concretes. Five different percentages of HL as a partial replacement of ordinary limestone filler in asphalt concrete mixes were studied for wearing course application purposes. Experimental tests were conducted to evaluate the mechanical properties
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