A.A. Shaikh | Sardar Vallabhbhai Patel National Institute of Technology Surat (original) (raw)

Papers by A.A. Shaikh

Journal of Allergy and Clinical Immunology, 2007

Seasonal allergic rhinitis is common globally, and symptoms have been shown to impair learning ab... more Seasonal allergic rhinitis is common globally, and symptoms have been shown to impair learning ability in children in laboratory conditions. Critical examinations in children are often held in the summer during the peak grass pollen season. To investigate whether seasonal allergic rhinitis adversely impacts examination performance in United Kingdom teenagers. Case-control analysis of 1,834 students (age 15-17 years; 50% girls) sitting for national examinations. Cases were those who dropped 1 or more grades in any of 3 core subjects (mathematics, English, and science) between practice (winter) and final (summer) examinations; controls were those whose grades were either unchanged or improved. Associations between allergic rhinitis symptoms, clinician-diagnosed allergic rhinitis, and allergic rhinitis-related medication use, recorded on examination days immediately before the examination, were assessed using multilevel regression models. Between 38% and 43% of students reported symptoms of seasonal allergic rhinitis on any 1 of the examination days. There were 662 cases (36% of students) and 1,172 controls. After adjustment, cases were significantly more likely than controls to have had allergic rhinitis symptoms during the examination period (odds ratio [OR], 1.4; 95% CI, 1.1-1.8; P = .002), to have taken any allergic rhinitis medication (OR, 1.4; 95% CI, 1.1-1.7; P = .01), or to have taken sedating antihistamines (OR, 1.7; 95% CI, 1.1-2.8; P = .03). Current symptomatic allergic rhinitis and rhinitis medication use are associated with a significantly increased risk of unexpectedly dropping a grade in summer examinations. This is the first time the relationship between symptomatic allergic rhinitis and poor examination performance has been demonstrated, which has significant implications for clinical practice.

The present study is aimed to investigate micromilling performance of thermoplastics with differe... more The present study is aimed to investigate micromilling
performance of thermoplastics with different parameters, namely laser beam absorptivity, latent heat of vaporization, laser power and cutting speed. The 25-W CO2 (CW) laser engraving machine is used for the investigation.
In total 50 different combinations of laser power and
cutting speed with four categories of thermoplastics,
namely poly-methyl-methacrylate, poly-propylene, acrylonitrile butadiene styrene and nylon 6, are used in this study.
Experimental results suggest that laser beam absorptivity, cutting power and cutting speed are the major influencing parameters on depth of cut. Theoretical model for the prediction of depth of cut in terms of material properties, cutting power and cutting speed has been proposed. Two correction parameters have been introduced in this analysis using non-linear regression method to improve the theoretical
model. Comparison has been made between prediction
capabilities of theoretical model, model based on multigene genetic programming and artificial neural network. The comparison clearly indicates that all the three models provide accurate prediction of depth of cut. The details of experimentation, model development, testing and the performance comparison are presented in this paper.

Journal of Allergy and Clinical Immunology, 2007

Seasonal allergic rhinitis is common globally, and symptoms have been shown to impair learning ab... more Seasonal allergic rhinitis is common globally, and symptoms have been shown to impair learning ability in children in laboratory conditions. Critical examinations in children are often held in the summer during the peak grass pollen season. To investigate whether seasonal allergic rhinitis adversely impacts examination performance in United Kingdom teenagers. Case-control analysis of 1,834 students (age 15-17 years; 50% girls) sitting for national examinations. Cases were those who dropped 1 or more grades in any of 3 core subjects (mathematics, English, and science) between practice (winter) and final (summer) examinations; controls were those whose grades were either unchanged or improved. Associations between allergic rhinitis symptoms, clinician-diagnosed allergic rhinitis, and allergic rhinitis-related medication use, recorded on examination days immediately before the examination, were assessed using multilevel regression models. Between 38% and 43% of students reported symptoms of seasonal allergic rhinitis on any 1 of the examination days. There were 662 cases (36% of students) and 1,172 controls. After adjustment, cases were significantly more likely than controls to have had allergic rhinitis symptoms during the examination period (odds ratio [OR], 1.4; 95% CI, 1.1-1.8; P = .002), to have taken any allergic rhinitis medication (OR, 1.4; 95% CI, 1.1-1.7; P = .01), or to have taken sedating antihistamines (OR, 1.7; 95% CI, 1.1-2.8; P = .03). Current symptomatic allergic rhinitis and rhinitis medication use are associated with a significantly increased risk of unexpectedly dropping a grade in summer examinations. This is the first time the relationship between symptomatic allergic rhinitis and poor examination performance has been demonstrated, which has significant implications for clinical practice.

The present study is aimed to investigate micromilling performance of thermoplastics with differe... more The present study is aimed to investigate micromilling
performance of thermoplastics with different parameters, namely laser beam absorptivity, latent heat of vaporization, laser power and cutting speed. The 25-W CO2 (CW) laser engraving machine is used for the investigation.
In total 50 different combinations of laser power and
cutting speed with four categories of thermoplastics,
namely poly-methyl-methacrylate, poly-propylene, acrylonitrile butadiene styrene and nylon 6, are used in this study.
Experimental results suggest that laser beam absorptivity, cutting power and cutting speed are the major influencing parameters on depth of cut. Theoretical model for the prediction of depth of cut in terms of material properties, cutting power and cutting speed has been proposed. Two correction parameters have been introduced in this analysis using non-linear regression method to improve the theoretical
model. Comparison has been made between prediction
capabilities of theoretical model, model based on multigene genetic programming and artificial neural network. The comparison clearly indicates that all the three models provide accurate prediction of depth of cut. The details of experimentation, model development, testing and the performance comparison are presented in this paper.