Economic Impact of CDM Implementation through Alternate Energy Resource Substitution

Since the Kyoto protocol agreement, Clean Development Mechanism (CDM) has garnered large emphasis in terms of certified emission reductions (CER) not only amidst the global carbon market but also in India. This paper attempts to assess the impact of CDM towards sustainable development particularly in rural domestic utility sector that mainly includes lighting and cooking applications, with electricity as the source of energy. A detailed survey has undertaken in the state of Kerala, in southern part of India to study the rural domestic energy consumption pattern. The data collected was analyzed that throws insight into the interrelationships of the various parameters that influence domestic utility sector pertaining to energy consumption by using electricity as the source of energy. The interrelationships between the different parameters were modeled that optimizes the contribution of electricity on domestic utility sector. The results were used to estimate the feasible extent of CO2 emission reduction through use of electricity as the energy resources, vis-à-vis its economic viability through cost effectiveness. The analysis also provides a platform for implementing CDM projects in the sector and related prospects with respects to the Indian scenari

Prevalence of Psychiatric Disorders among the Rural Geriatric Population: A Pilot Study in Karnataka, India

Background: Increasing life expectancy around the world, an outstanding achievement of our century, has brought with it new public health challenges. India is the second most populous country in the world, with over 72 million inhabitants above 60 years of age as of 2001. The life expectancy in India increased from 32 years in 1947 to over 66 years in 2010, with 8.0% of the population now reaching over 60 years of age. Few studies in India target the health, especially mental health, of this geriatric population. This study aims to estimate the current prevalence of psychiatric disorders in the geriatric population of the rural area of Singanodi,Karnataka, India.Methods: This cross sectional, epidemiological, community-based study was conducted in a rural health training area of Singanodi, Raichur District, Karnataka, India.The General Health Questionnaire-12, Mini Mental State Examination, and Geriatric Depression Scale were administered to 366 participants. Chi square tests with Yates correction were utilized for statistical analysis using SPSS 19.0 software.Results:We found that 33.9% of the geriatric population in the selected province were above the threshold for mental illness based on the GHQ-12 questionnaire. Females had a higher prevalence of mental disorder at 77.6% (152 out of 196) as compared to males who had a prevalence of 42.4% (72 out of 170). The most common psychiatric disorder was depression (21.9%), and generalized anxiety was present in 10.7% of the study population. Prevalence of cognitive impairment was 16.3%, with a significantly higher percentage of  affected individuals in 80+ age group.Conclusion: Mental disorders are common among elderly people, but they are not well documented in rural India. The assessment of psychiatric disorder prevalence will help strengthen psycho-geriatric services and thus improve the quality of life of the elderly.  A system that ensures comprehensive health care will have to be developed for this purpose as part of our future efforts

Natural Frequency based delamination estimation in GFRP beams using RSM and ANN

The importance of delamination detection can be understood from aircraft components like Vertical Stabilizer, which is subjected to heavy vibration during the flight movement and it may lead to delamination and finally even flight crash can happen because of that. Any solid structure's vibration behaviour discloses specific dynamic characteristics and property parameters of that structure. This research investigates the detection of delamination in composites using a method based on vibration signals.  The composite material's flexural stiffness and strength are reduced as a result of delaminations, and vibration properties such as natural frequency responses are altered. In inverse problems involving vibration response, the response signals such as natural frequencies are utilized to find the location and magnitude of delaminations. For different delaminated beams with varying position and size, inverse approaches such as Response Surface Methodology (RSM) and Artificial Neural Network (ANN) are utilized to address the inverse problem, which aids in the prediction of delamination size and location

Artificial neural network based delamination prediction in composite plates using vibration signals

Dynamic loading on composite components may induce damages such as cracks, delaminations, etc. and development of an early damage detection technique for delaminations is one of the most important aspects in ensuring the integrity and safety of composite components. The presence of damages such as delaminations on the composites reduces its stiffness and further changes the dynamic behaviour of the structures. As the loss in stiffness leads to changes in the natural frequencies, mode shapes, and other aspects of the structure, vibration analysis may be the ideal technique to employ in this case. In this research work, the supervised feed-forward multilayer back-propagation Artificial Neural Network (ANN) is used to determine the position and area of delaminations in GFRP plates using changes in natural frequencies as inputs. The natural frequencies were obtained by finite element analysis and results are validated by experimentation. The findings show that the suggested technique can satisfactorily estimate the location and extent of delaminations in composite plates

Photon emission from out of equilibrium dissipative parton plasma

Using the second order Israel-Stewart hydrodynamics we discuss the effect of viscosity on photon production in a parton plasma created in relativistic heavy ion collisions. We find that photon production rates can enhance by several factors due to the viscous effect in a chemically nonequilibrated plasma.Comment: 6 pages + 4 figure

Design of Low Power Data Preserving Flip Flop Using MTCMOS Technique

In order to reduce overall power consumption, a well-known technique is to scale supply voltages. However, to maintain performance, device threshold voltages must scale as well, which will cause sub threshold leakage currents to increase exponentially. The sub threshold voltage has to affect the two parameters one is the delay and other one is the sub threshold leakage current. Smaller the threshold voltage smaller will be delay while larger will be the sub threshold current. Controlling sub threshold leakage has been explored significantly in the literature, especially in the context of reducing leakage currents in burst mode type circuits, where the system spends the majority of the time in an idle standby, or sleep, state where no computation is taking place. MTCMOS or multi-threshold CMOS has been proposed as a very effective technique for reducing leakage currents during the standby by state by utilizing high sleep devices to gate the power supplies of a low logic block. Although MTCMOS circuit techniques are effective for controlling leakage currents in combinational logic, a drawback is that it can cause internal nodes to float, and cannot be directly used in standard memory cells without corrupting stored data. As a result, several researchers have explored possible MTCMOS latch designs that can reduce leakage currents yet maintain state during the standby modes. In this work a data preserving flip flop with reduced leakage power is designed using MTCMOS technique in 90nm technology with the help of CADENCE tool. The simulation results have shown that the leakage power is reduced by 25.70% compared to CMOS flip flop