There is need to investigate the use of liposomal amphotericin B in cryptococcal meningitis in In... more There is need to investigate the use of liposomal amphotericin B in cryptococcal meningitis in India. To compare the efficacy, safety, duration of treatment and cost of two doses of liposomal amphotericin B (Amp B) (Fungisome) in cryptococcal meningitis in HIV/AIDS patients. Prospective, randomized, multicenter study in tertiary care hospitals across India. Adult patients with culture-proven cryptococcal meningitis with HIV/AIDS were randomized to receive either 1 (Group A) or 3 mg/kg/day of Fungisome (Group B). Clinical efficacy and tolerability, laboratory evaluations and mycological response were assessed daily, twice weekly and weekly respectively. The patients were assessed at four and eight-week follow-up. We calculated average and standard deviation for the various parameters. The time to show clinical response was 13.66 days (1 mg) and 9.55 days (3 mg). In Group B (n=6 complete response), 50% patients responded within one week by microbial conversion, 83% in two weeks and 100% in three weeks. Patients with 1 mg dose (n=4 complete response), none showed microbial conversion within one week, 75% responded in two weeks, whereas one patient took four weeks. The average duration of treatment was 36.5+/-14.4 and 26.5+/-5.89 (S.D.) days in 1 and 3 mg/kg/day respectively. Drug was tolerated with little renal, hepatic or hematological toxicity. The cost was found to be 3.81 lacs and 1.74 lacs with 3mg/kg/day and 1mg/kg/day respectively. Higher dose showed better efficacy and quicker microbial conversion of Cerebrospinal fluid (CSF) (cerebrospinal fluid) than 1 mg/kg/day. It shortened the duration of treatment in days by 27% while drug cost almost doubled ( ISRCTN 52812742).
Detecting and locating damage in structural components and joints that have high feature densitie... more Detecting and locating damage in structural components and joints that have high feature densities and complex geometry is a difficult problem in the field of structural health monitoring (SHM). Active propagation of diagnostic waves is one approach that is used to detect damage. But small cracks and damage are difficult to detect because they have a small effect on the propagating waves as compared to the effects the complex geometry itself which causes dispersion and reflection of waves. Another limitation of active wave propagation is that pre-damage data is required for every sensor-actuator combination, and a large number of sensors might be needed to detect small cracks on large structures. Overall, the problem of detecting damage in complex geometries is not well investigated in the field of SHM. Nevertheless, the problem is important because damage often initiates at joints and locations where section properties change.
Structural Health Monitoring ideally would check the health of the structure in real time all the... more Structural Health Monitoring ideally would check the health of the structure in real time all the time. Simplifying the sensor system and the data acquisition equipment plays a very important role in achieving this goal. This paper discusses a practical technique that uses long continuous sensors and biomimetic signal processing to simplify health monitoring. The testing of a structural neural system with an updated analog processor module is discussed in this paper. A neuron is formed by connecting sensor elements to an analog processor. The structural neural system is formed by connecting multiple neurons to mimic the signal processing architecture of the neural system of the human body. This approach reduces the required number of data acquisition channels and still predicts the location of damage within a grid of miniature neurons. Different types of sensors can also be used. A piezoelectric ribbon sensor can sense damage due to impacts or crack growth because these damages generate Lamb waves that are detected by the neural system. The neuron can also receive diagnostic waves generated to check the structure on demand and when it is not in operation. In addition, new continuous multi-wall carbon nanotube sensors are being used as strain and crack detection neurons that operate during both static and dynamic loading. In general, the Structural Neural System may provide an advantage for the continuous monitoring of most large sensor systems in which anomalous events must be detected, and where it is impractical to have a separate channel of data acquisition for each sensor. Moreover, the data reduction technique and damage detection algorithm are easy to understand, simple to implement, reliable, and many sensor types can be used.
Journal of Intelligent Material Systems and Structures, 2006
Journal of Intelligent Material Systems and Structures Schulz, Vesselin Shanov, Peng He, FJ Boeri... more Journal of Intelligent Material Systems and Structures Schulz, Vesselin Shanov, Peng He, FJ Boerio, Donglu Shi and Subrahmin Srivinas Yun Yeo-Heung, Atul Miskin, Phil Kang, Sachin Jain, Suhasini Narasimhadevara, Douglas Hurd, Vishal Shinde, Mark J. Carbon ...
Journal of Intelligent Material Systems and Structures, 2006
The objective of this study (Part II) paper is to develop a dry actuator for wider application th... more The objective of this study (Part II) paper is to develop a dry actuator for wider application than the wet actuator. To form a dry actuator, a carbon nanofiber (CNF) actuator is based on a solid polymer electrolyte (SPE). The SPE film is prepared from polymethyl methacrylate (PMMA), an ion-exchange material, a plasticizer, and a solvent by the solution casting method. Ion conductivity studies were carried out to characterize the electrochemical properties of the SPE. Electrochemical impedance spectroscopy was performed to understand the electrochemical cell of the dry actuator. The actuator was tested in a dry environment at various voltages and frequencies and the tip displacement was measured using a laser displacement sensor. Compared to previous single wall carbon nanotube buckypaper actuators, the dry-based CNF actuator requires a little higher voltage to actuate, but it is two orders of magnitude lower in cost. Compared to the liquid-based actuator, the solid electrolyte-based actuator is slower and the displacements are smaller. These results have verified the principle of the CNF dry actuator. Further development of this new smart material could lead to practical smart structures applications in which the CNF hybrid material could be used as a muscle layer on structures, or as the structural material itself.
Detecting and locating cracks in structural components and joints that have high feature densitie... more Detecting and locating cracks in structural components and joints that have high feature densities is a challenging problem in the field of Structural Health Monitoring. There have been advances in piezoelectric sensors, actuators, wave propagation, MEMS, and optical fiber sensors. However, few sensor-signal processing techniques have been applied to the monitoring of joints and complex structural geometries. This is in part because maintaining and analyzing a large amount of data obtained from a large number of sensors that may be needed to monitor joints for cracks is difficult. Reliable low cost assessment of the health of structures is crucial to maintain operational availability and productivity, reduce maintenance cost, and prevent catastrophic failure of large structures such as wind turbines, aircraft, and civil infrastructure. Recently, there have also been advances in development of simple passive techniques for health monitoring including a technique based on mimicking the biological neural system using electronic logic circuits. This technique aids in reducing the required number of data acquisition channels by a factor of ten or more and is able to predict the location of a crack within a rectangular grid or within an arbitrarily arranged network of continuous sensors or neurons. The current paper shows results obtained by implementing this method on an aluminum plate and joint. The plates were tested using simulated acoustic emissions and also loading via an MTS machine. The testing indicates that the neural system can monitor complex joints and detect acoustic emissions due to propagating cracks. High sensitivity of the neural system is needed, and further sensor development and testing on different types of joints is required. Also indicated is that sensor geometry, sensor location, signal filtering, and logic parameters of the neural system will be specific to the particular type of joint (material, thickness, geometry) being monitored. Also, a novel piezoresistive carbon nanotube nerve crack sensor is presented that can become a neuron and respond to local crack growth.
A small size prototype of a Structural Neural System (SNS) was tested in real time for damage det... more A small size prototype of a Structural Neural System (SNS) was tested in real time for damage detection in a laboratory setting and the results are presented in this paper. The SNS is a passive online structural health monitoring (SHM) system that can detect small propagating damages in real time before the overall failure of the structure is realized. The passive SHM method is based on the concept of detecting acoustic emissions (AE) due to damage propagating. Propagating cracks were identified near the vicinity of a sensor in a composite specimen during fatigue testing. In the composite specimen, in additions to a propagating crack, fretting occurred because of slipping contact between the load points and the composite specimen. The SNS was able to predict the location of damage due to crack propagation and also detect signals from fretting simultaneously in real time.
A systematic study of extraction of zinc salicylate is reported. Optimum conditions for the extra... more A systematic study of extraction of zinc salicylate is reported. Optimum conditions for the extraction and determination of zinc are evaluated from a critical study of the effect of pH, sodium salicylate concentration and triphenylphosphine oxide concentration. The effect of foreign ions on the extraction is also discussed. The probable composition of the species has been deduced from the extraction data. The method has been used to separate zinc from cadmium and mercury in binary mixtures and for the determination of zinc in various pharmaceutical products.
There is need to investigate the use of liposomal amphotericin B in cryptococcal meningitis in In... more There is need to investigate the use of liposomal amphotericin B in cryptococcal meningitis in India. To compare the efficacy, safety, duration of treatment and cost of two doses of liposomal amphotericin B (Amp B) (Fungisome) in cryptococcal meningitis in HIV/AIDS patients. Prospective, randomized, multicenter study in tertiary care hospitals across India. Adult patients with culture-proven cryptococcal meningitis with HIV/AIDS were randomized to receive either 1 (Group A) or 3 mg/kg/day of Fungisome (Group B). Clinical efficacy and tolerability, laboratory evaluations and mycological response were assessed daily, twice weekly and weekly respectively. The patients were assessed at four and eight-week follow-up. We calculated average and standard deviation for the various parameters. The time to show clinical response was 13.66 days (1 mg) and 9.55 days (3 mg). In Group B (n=6 complete response), 50% patients responded within one week by microbial conversion, 83% in two weeks and 100% in three weeks. Patients with 1 mg dose (n=4 complete response), none showed microbial conversion within one week, 75% responded in two weeks, whereas one patient took four weeks. The average duration of treatment was 36.5+/-14.4 and 26.5+/-5.89 (S.D.) days in 1 and 3 mg/kg/day respectively. Drug was tolerated with little renal, hepatic or hematological toxicity. The cost was found to be 3.81 lacs and 1.74 lacs with 3mg/kg/day and 1mg/kg/day respectively. Higher dose showed better efficacy and quicker microbial conversion of Cerebrospinal fluid (CSF) (cerebrospinal fluid) than 1 mg/kg/day. It shortened the duration of treatment in days by 27% while drug cost almost doubled ( ISRCTN 52812742).
Detecting and locating damage in structural components and joints that have high feature densitie... more Detecting and locating damage in structural components and joints that have high feature densities and complex geometry is a difficult problem in the field of structural health monitoring (SHM). Active propagation of diagnostic waves is one approach that is used to detect damage. But small cracks and damage are difficult to detect because they have a small effect on the propagating waves as compared to the effects the complex geometry itself which causes dispersion and reflection of waves. Another limitation of active wave propagation is that pre-damage data is required for every sensor-actuator combination, and a large number of sensors might be needed to detect small cracks on large structures. Overall, the problem of detecting damage in complex geometries is not well investigated in the field of SHM. Nevertheless, the problem is important because damage often initiates at joints and locations where section properties change.
Structural Health Monitoring ideally would check the health of the structure in real time all the... more Structural Health Monitoring ideally would check the health of the structure in real time all the time. Simplifying the sensor system and the data acquisition equipment plays a very important role in achieving this goal. This paper discusses a practical technique that uses long continuous sensors and biomimetic signal processing to simplify health monitoring. The testing of a structural neural system with an updated analog processor module is discussed in this paper. A neuron is formed by connecting sensor elements to an analog processor. The structural neural system is formed by connecting multiple neurons to mimic the signal processing architecture of the neural system of the human body. This approach reduces the required number of data acquisition channels and still predicts the location of damage within a grid of miniature neurons. Different types of sensors can also be used. A piezoelectric ribbon sensor can sense damage due to impacts or crack growth because these damages generate Lamb waves that are detected by the neural system. The neuron can also receive diagnostic waves generated to check the structure on demand and when it is not in operation. In addition, new continuous multi-wall carbon nanotube sensors are being used as strain and crack detection neurons that operate during both static and dynamic loading. In general, the Structural Neural System may provide an advantage for the continuous monitoring of most large sensor systems in which anomalous events must be detected, and where it is impractical to have a separate channel of data acquisition for each sensor. Moreover, the data reduction technique and damage detection algorithm are easy to understand, simple to implement, reliable, and many sensor types can be used.
Journal of Intelligent Material Systems and Structures, 2006
Journal of Intelligent Material Systems and Structures Schulz, Vesselin Shanov, Peng He, FJ Boeri... more Journal of Intelligent Material Systems and Structures Schulz, Vesselin Shanov, Peng He, FJ Boerio, Donglu Shi and Subrahmin Srivinas Yun Yeo-Heung, Atul Miskin, Phil Kang, Sachin Jain, Suhasini Narasimhadevara, Douglas Hurd, Vishal Shinde, Mark J. Carbon ...
Journal of Intelligent Material Systems and Structures, 2006
The objective of this study (Part II) paper is to develop a dry actuator for wider application th... more The objective of this study (Part II) paper is to develop a dry actuator for wider application than the wet actuator. To form a dry actuator, a carbon nanofiber (CNF) actuator is based on a solid polymer electrolyte (SPE). The SPE film is prepared from polymethyl methacrylate (PMMA), an ion-exchange material, a plasticizer, and a solvent by the solution casting method. Ion conductivity studies were carried out to characterize the electrochemical properties of the SPE. Electrochemical impedance spectroscopy was performed to understand the electrochemical cell of the dry actuator. The actuator was tested in a dry environment at various voltages and frequencies and the tip displacement was measured using a laser displacement sensor. Compared to previous single wall carbon nanotube buckypaper actuators, the dry-based CNF actuator requires a little higher voltage to actuate, but it is two orders of magnitude lower in cost. Compared to the liquid-based actuator, the solid electrolyte-based actuator is slower and the displacements are smaller. These results have verified the principle of the CNF dry actuator. Further development of this new smart material could lead to practical smart structures applications in which the CNF hybrid material could be used as a muscle layer on structures, or as the structural material itself.
Detecting and locating cracks in structural components and joints that have high feature densitie... more Detecting and locating cracks in structural components and joints that have high feature densities is a challenging problem in the field of Structural Health Monitoring. There have been advances in piezoelectric sensors, actuators, wave propagation, MEMS, and optical fiber sensors. However, few sensor-signal processing techniques have been applied to the monitoring of joints and complex structural geometries. This is in part because maintaining and analyzing a large amount of data obtained from a large number of sensors that may be needed to monitor joints for cracks is difficult. Reliable low cost assessment of the health of structures is crucial to maintain operational availability and productivity, reduce maintenance cost, and prevent catastrophic failure of large structures such as wind turbines, aircraft, and civil infrastructure. Recently, there have also been advances in development of simple passive techniques for health monitoring including a technique based on mimicking the biological neural system using electronic logic circuits. This technique aids in reducing the required number of data acquisition channels by a factor of ten or more and is able to predict the location of a crack within a rectangular grid or within an arbitrarily arranged network of continuous sensors or neurons. The current paper shows results obtained by implementing this method on an aluminum plate and joint. The plates were tested using simulated acoustic emissions and also loading via an MTS machine. The testing indicates that the neural system can monitor complex joints and detect acoustic emissions due to propagating cracks. High sensitivity of the neural system is needed, and further sensor development and testing on different types of joints is required. Also indicated is that sensor geometry, sensor location, signal filtering, and logic parameters of the neural system will be specific to the particular type of joint (material, thickness, geometry) being monitored. Also, a novel piezoresistive carbon nanotube nerve crack sensor is presented that can become a neuron and respond to local crack growth.
A small size prototype of a Structural Neural System (SNS) was tested in real time for damage det... more A small size prototype of a Structural Neural System (SNS) was tested in real time for damage detection in a laboratory setting and the results are presented in this paper. The SNS is a passive online structural health monitoring (SHM) system that can detect small propagating damages in real time before the overall failure of the structure is realized. The passive SHM method is based on the concept of detecting acoustic emissions (AE) due to damage propagating. Propagating cracks were identified near the vicinity of a sensor in a composite specimen during fatigue testing. In the composite specimen, in additions to a propagating crack, fretting occurred because of slipping contact between the load points and the composite specimen. The SNS was able to predict the location of damage due to crack propagation and also detect signals from fretting simultaneously in real time.
A systematic study of extraction of zinc salicylate is reported. Optimum conditions for the extra... more A systematic study of extraction of zinc salicylate is reported. Optimum conditions for the extraction and determination of zinc are evaluated from a critical study of the effect of pH, sodium salicylate concentration and triphenylphosphine oxide concentration. The effect of foreign ions on the extraction is also discussed. The probable composition of the species has been deduced from the extraction data. The method has been used to separate zinc from cadmium and mercury in binary mixtures and for the determination of zinc in various pharmaceutical products.
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Papers by Vishal Shinde