A low cost PC based card for heat-capacity measurements at low temperatures

We describe a simple, low cost pc based card for the measurement of heat capacity using adiabatic calorimetry at low temperatures. This card provides the control pulse to the sample heater as well as trigger pulse to the nano-voltmeter which monitors the sensor voltage (Ge sensor, Lake Shore Inc., USA). We have also added a 12 bit DAC on this card and this is used for remote setting of the heater current of an old SHE (now Biomagnetic, Inc., USA, model CCS) analog constant current source. Although this card is used here for heat-capacity measurements, the same can also be used for thermo-power and thermal-conductivity measurements

SMART-CAM FOR WAREHOUSE

We are implementing a project for memory optimization for video surveillance with the help of human motion happening in the surrounding in the warehouse and also will be able to playback the recorded video which will only have the human motion recorded video and images will be click continuously after a fixed interval of time to get a view when there is human motion or no human motion images will be always clicked and stored. This system is based on IoT (Internet of Things). It has a Raspberry Pi (RPI), Camera module to detect human (thief) or detection of fire. Motion detection is a process of confirming a change in the position of an object relative to its surroundings or the change in the surroundings relative to an object. Generally, motion detection is useful in real-time or active surveillance systems. IN this paper the main focus is given to the processing of the captured video data to detect human motion in it. So that it is easy for the user to view images and videos whenever he wants. So this system is very useful to maintain a warehouse and memory optimization will be done

Measurements of primary biological aerosol particles and ice nuclei at the Amazon Tall Tower Observatory.

International audienc

Pathways of precipitation formation in different thermodynamic and aerosol environments over the Indian Peninsula

This study examines precipitation pathways in different thermodynamic and aerosol environments over the Indian peninsula. A three-dimensional idealized Large-Eddy Simulation (LES) model with spectral bin microphysics is used to simulate convective clouds growing under different monsoon environments. Numerical simulations were evaluated using in-situ measurements from the Cloud-Aerosol Interactions and Precipitation Enhancement Experiment (CAIPEEX). Sensitivity studies were carried out using varied combinations of water vapor mixing ratio (by ±10 and ± 20%) and cloud condensation nuclei number concentrations (100 and 3000 cm−3). The response of various microphysical process rates to the changes in moisture and aerosol is analyzed. The clouds developed in a moist environment have a greater cloud depth, more supercooled liquid, broader cloud drop spectra, earlier onset of mixed-phase regimes, and enhanced precipitation. The amount of moisture is an important factor in determining the aerosol effects on cloud phase and precipitation, with a more significant aerosol impact in the moist environment (+ 20%). An increase in aerosol number concentration results in an enhanced mixed-phase fraction, updraft velocity, and precipitation, mainly through enhancing deposition and aggregation rates. The overall change in moisture by ±20% in cloud properties and precipitation is much more significant than the ten-times change in aerosol concentrations. The secondary ice formation via the Hallet-Mossop (H-M) process plays a significant role in determining the total ice crystal concentration, and its importance increases with the increases of both moisture and aerosol number concentration. The impact of this process on precipitation is minimal. These results provide an important understanding of how co-varied moisture and aerosols over the Indian region would affect the monsoon clouds and precipitation

Abiotic stress responses in plants - present and future

Drought, cold, high-salinity and heat are major abiotic stresses that severely reduce the yield of food crops worldwide. Traditional plant breeding approaches to improve abiotic stress tolerance of crops had limited success due to multigenic nature of stress tolerance. In the last decade molecular techniques have been used to understand the mechanisms by which plants perceive environmental signals and further their transmission to cellular machinery to activate adaptive responses. This knowledge is critical for the development of rational breeding and transgenic strategies to impart stress tolerance in crops. Studies on physiological and molecular mechanisms of abiotic stress tolerance have led to characterisation of a number of genes associated with stress adaptation. Techniques like microarrays have proven to be invaluable in generating a list of stress related genes. Some of these genes arc specific for a particular stress while others are shared between various stresses. Interestingly, a number of genes are shared in abiotic and biotic stress responses

Observational and simulated cloud microphysical features of rain formation in the mixed phase clouds observed during CAIPEEX

Cloud microphysical observations of rain formation in mixed phase monsoon clouds (from 10 to − 9 °C) using instrumented aircraft during Cloud Aerosol Interaction and Precipitation Enhancement Experiment (CAIPEEX) are presented. The drop size and particle size distributions are broader in the mixed phase region, indicating efficient growth of liquid as well as ice phase. Aircraft observations noticed higher ice particle concentrations in Hallet–Mossop zone (− 3 to − 8 °C) with existence of smaller and larger cloud droplets, rimed needles columns, and graupel particles. Observations strongly suggested the active presence of Hallet–Mossop (1974) process in this cloud. The higher correlations found between slope and intercept parameters of exponential size distributions can be attributed to the efficient secondary ice production as well as to the aggregation growth of ice particles. Large Eddy Simulation (LES) of these clouds are compared with observed cloud microphysical properties, also illustrated the important role of Hallet–Mossop (HM) process and its link with warm rain and graupel formation. The raindrop freezing plays a crucial role in graupel formation in early stage of ice development. The observed mean values of microphysical parameters including liquid water content, ice water content, ice number concentrations, and reflectivity showed good agreement with model simulations. Primary ice nuclei have only a minor role in the total ice mass in these clouds