Preparation and Evaluation of Curcumin Invasomes

Curcumin has poor aqueous solubility and has bioavailability problems. Hence in the present study the solubility of curcumin was increased by complexing with cyclodextrin (CD) and Hydroxy propyl β cyclodextrin(HPβCD). This complex was incorporated in to invasomes and then into HPMC gel to prepare as a transdermal formulation. Curcumin cyclodextrin complexes were prepared by physical mixture and co-precipitation method. Different formulations of invasomes containing 0.5, 1.0, 1.5 % of limonene, fenchone, nerolidol  were prepared using mechanical dispersion technique. Invasomes were characterized for vesicular size, surface morphology, zeta potential, entrapment efficiency and percutaneous permeation. Formulations CHL1 and CHL2 were optimized for further studies. It was found in the study that complexation with HPβCD in 1:2 proportion prepared by co-precipitation method was found to bind 90% of curcumin. Invasomal preparation with 0.5% limonene, 4% ethanol was found to enhance permeation by 8.11 times the control. In vivo diffusion studies were conducted using franz diffusion cell, ex vivo skin permeation studies of CHL1 using rat abdominal skin showed cumulative drug permeated (Q24­) of 70.32 µg/cm2, steady state transdermal flux of 3.344 µg/cm2/hr-1, permeability coefficient of 5.35 cm/hr and lag time of 1 hr when compared with control formulation. From the results it was concluded that the solubility of curcumin was increased by complexing with HPβCD and invasomal preparation with 0.5% limonene has improved the permeation through the skin

Validation of Satellite (TMPA and IMERG) Rainfall Products with the IMD Gridded Data Sets over Monsoon Core Region of India

This work presents the validation of satellite (TMPA and IMERG) rainfall products against the India Meteorological Department (IMD) gridded data sets (0.25° × 0.25°) of dense network of rain gauges distributed over the monsoon core region of India. The validation uses the data sets covering the 20 years (1998–2017) and detects the time series bias; inter annual variations and Intra Seasonal Oscillations (ISO). The bias in the two data sets is found to be very less over the core region compared to whole India. The correlation between daily rainfall IMD and satellite is found to be +0.88 which is of 99% confidence level. The dominant periodicities in the rainfall patterns of IMD and satellite are Madden Julie Oscillation (30–60 days) and local oscillations (less than 20 days) are conspicuous and the normalized power varies from year to year. During the El Niño and La Niña years, the normalized power of rainfall pattern is low and high in satellite data sets which infer the suppressed and strongest activity of MJO over Indian Ocean that modulates the rainfall pattern over India

On the Robustness of Explanations of Deep Neural Network Models: A Survey

Explainability has been widely stated as a cornerstone of the responsible and trustworthy use of machine learning models. With the ubiquitous use of Deep Neural Network (DNN) models expanding to risk-sensitive and safety-critical domains, many methods have been proposed to explain the decisions of these models. Recent years have also seen concerted efforts that have shown how such explanations can be distorted (attacked) by minor input perturbations. While there have been many surveys that review explainability methods themselves, there has been no effort hitherto to assimilate the different methods and metrics proposed to study the robustness of explanations of DNN models. In this work, we present a comprehensive survey of methods that study, understand, attack, and defend explanations of DNN models. We also present a detailed review of different metrics used to evaluate explanation methods, as well as describe attributional attack and defense methods. We conclude with lessons and take-aways for the community towards ensuring robust explanations of DNN model predictions.Comment: Under Review ACM Computing Surveys "Special Issue on Trustworthy AI

Assessment of the CHIRPS-Based Satellite Precipitation Estimates

At present, satellite rainfall products, such as the Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) product, have become an alternative source of rainfall data for regions where rain gauge stations are sparse, e.g., Northeast Brazil (NEB). In this study, continuous scores (i.e., Pearson’s correlation coefficient, R; percentage bias, PBIAS; and unbiased root mean square error, ubRMSE) and categorical scores (i.e., probability of detection, POD; false alarm ratio, FAR; and threat score, TS) were used to assess the CHIRPS rainfall estimates against ground-based observations on a pixel-to-station basis, during 01 January 1981 to 30 June 2019 over NEB. Results showed that CHIRPS exhibits better performance in inland regions (R, PBIAS, and ubRMSE median: 0.51, −3.71%, and 9.20 mm/day; POD, FAR, and TS median: 0.59, 0.44, and 0.40, respectively) than near the coast (R, PBIAS, and ubRMSE median: 0.36, −5.66%, and 12.43 mm/day; POD, FAR, and TS median: 0.32, 0.42, and 0.26, respectively). It shows better performance in the wettest months (i.e., DJF) than in the driest months (i.e., JJA) and is sensitive to both the warm-top stratiform cloud systems and the sub-cloud evaporation processes. Overall, the CHIRPS rainfall data set could be used for some operational purposes in NEB

Real-time Simulation of Dynamic Vehicle Models using a High-performance Reconfigurable Platform

A purely software-based approach for Real-Time Simulation (RTS) may have difficulties in meeting real-time constraints for complex physical model simulations. In this paper, we present a methodology for the design and im-plementationofRTS algorithms,basedontheuseof Field-ProgrammableGateArray(FPGA) technologytoimprove the response time of these models. Our methodology utilizes traditional hardware/software co-design approaches to generate a heterogeneous architecture for an FPGA-based simulator. The hardware design was optimized such that it efficiently utilizes the parallel nature of FPGAs and pipelines the independent operations. Further enhancement is obtained through the use of custom accelerators for common non-linear functions. Since the systems we examined had relatively low response time requirements, our approach greatly simplifies the software components by porting the computationally complexregionsto hardware.We illustratethe partitioningofa hardware-based simulator design across dual FPGAs, initiateRTS usinga system input froma Hardware-in-the-Loop (HIL) framework, and use these simulation results from our FPGA-based platform to perform response analysis. The total simulation time, which includes the time required to receive the system input over a socket (without HIL), software initialization, hardware computation, and transferof simulation results backovera socket, showsa speedup of 2× as compared to a simi-lar setup with no hardware acceleration. The correctness of the simulation output from the hardware has also been validated with the simulated results from the software-only design

Computer-Aided Assembly Sequence Planning for High-Mix Low-Volume Products in the Electronic Appliances Industry

Electronic appliance manufacturers are facing the challenge of frequent product orders. Based on each product order, the assembly process and workstations need to be planned. An essential part of the assembly planning is defining the assembly sequence, considering the mechanical product’s design, and handling of the product’s components. The assembly sequence determines the order of processes for each workstation, the overall layout, and thereby time and cost. Currently, the assembly sequence is decided by industrial engineers through a manual approach that is time-consuming, complex, and requires technical expertise. To reduce the industrial engineers’ manual effort, a Computer-Aided Assembly Sequence Planning (CAASP) system is proposed in this paper. It compromises the components for a comprehensive system that aims to be applied practically. The system uses Computer-Aided Design (CAD) files to derive Liaison and Interference Matrices that represent a mathematical relationship between parts. Subsequently, an adapted Ant Colony Optimization Algorithm generates an optimized assembly sequence based on these relationships. Through a web browser-based application, the user can upload files and interact with the system. The system is conceptualized and validated using the CAD file of an electric motor example product. The results are discussed, and future work is outlined

Evaluation of mustard genotypes [Brassica juncea (L.) Czern and Coss] for quantitative traits and character association of seed yield and yield components at sub Himalayan region of West Bengal (India)

Brassica juncea is an important industrial and commercial oilseed crop grown primarily in India. This study aimed to assess 56 genotypes of Indian mustard to quantify genetic diversity, which aids the breeder in identifying genetically divergent parents to evaluate the proportional contributions of various components towards overall divergence. All the 56 Indian mustard genotypes were tested in RBD with three replications for 2 consecutive years i.e. 2016-17 and 2017-18 during the rabi season. Observations were recorded for 11 yield and its attributing traits. The findings revealed that height up to first branching, aphid count, penetration force and seed yield per plant had maximum PCV and GCV signifying that genetic factors have a greater impact on the inflow of these traits. Height up to first branching, secondary branches per plant, primary branches per plant, siliquae per plant, aphid count and 1000 seed weight had strong heritability combined with GA as % of mean. These indicate that the traits were controlled by additive gene action. Seed yield per plant was significantly correlated with penetration force and siliquae per plant. As a result, it's reasonable to predict that improving these traits by selection, could lead to significant yield gains. Four of the eleven PCs had eigen values greater than 1.0, accounting for 69.94% of the variance. PC I, which explained 30.31% of the overall variance. Mahalanobis D2 statistics revealed considerable genetic diversity among the genotypes. 56 genotypes were distributed into 7 clusters. This is anticipated that genotypes within a cluster are almost genetically related to one another. Cluster VII and II showed maximum inter-cluster divergence. From a breeding perspective, a divergence analysis revealed that genotypes like SKJM-05, RNWR-09-3, RW-351, B-85, DRMR-4001, RGN-386, TM52 276 and SKM-1313 can be selected as genetically divergent parents for hybridization to obtain desirable segregants

Trend Analysis of Streamflow and Rainfall in the Kosi River Basin of Mid-Himalaya of Kumaon Region, Uttarakhand

Due to climate change phenomenon and substantial decrease in water resources, analyzing the streamflow trend is of significant importance. In the present study, investigation was carried out to find rainfall and streamflow trends in the Kosi river watershed at different timescales from 1986 to 2016. Kosi river is one of the principal rivers in the Kumaon region. The different methods employed for trend detection of streamflow and rainfall were the Mann–Kendall (MK) test and the Sen’s slope (SS) estimator. Results showed a statistically significant decreasing trend in pre-monsoonal and annual rainfall with a Sen’s slope of -2.27 and -1.49 mm/year, respectively. The decreasing trends in pre-monsoon, post-monsoon, and winter streamflow were found during 1986–2016, which were not statistically significant. The results of the study help in understanding the variation and availability of rainfall and streamflow in different seasons of the year and motivate to adopt effective water management and agricultural practices for rainfed hills

Scaling of heavy rainy days with upper air profiles over Chennai during Northeast monsoon

This study aims to scale the heavy rainy days (rainfall > 64 mm per day) with the surface and upper-air parameters overChennai (12.80° N and 80.03° E), located on the east coast of India, during the Northeast (NE) monsoon (October toDecember) from 2001 to 2015. The daily rainfall and radiosonde observations that are available from India MeteorologicalDepartment (IMD), Outgoing Long-wave Radiation (OLR) from Very High Resolution Radiometer (VHRR) Kalpana-1Indian satellite, and Total Column Liquid Water (TCLW) and vertical velocity from ERA-Interimre analysis are used. Thestudy commences with the comparison of mean daily Integrated Water Vapor (IWV) and rainfall over Chennai. Further, thestudy proceeds ahead by analyzing the IWV, TCLW, Instantaneous Condensation Rate (ICR) and precipitation extremeefficiency during the heavy rainy days. The results are such as (i) the heavy rainy days are better scaled using IWV andTCLW than with surface air temperature and OLR (ii) ICR during the all heavy rainfall days found high at 700 mb level,and (iii) the precipitation extreme efficiency which is estimated using the ratio of precipitation extreme (obtained fromvertical velocity, specific humidity gradient) and the ICR has shown a linear relationship with the surface reaching rainfallthrough the temporal and spatial smearing of raindrops expected

Scaling of heavy rainy days with upper air profiles over Chennai during Northeast monsoon

153-161This study aims to scale the heavy rainy days (rainfall > 64 mm per day) with the surface and upper-air parameters over Chennai (12.80° N and 80.03° E), located on the east coast of India, during the Northeast (NE) monsoon (October to December) from 2001 to 2015. The daily rainfall and radiosonde observations that are available from India Meteorological Department (IMD), Outgoing Long-wave Radiation (OLR) from Very High Resolution Radiometer (VHRR) Kalpana-1 Indian satellite, and Total Column Liquid Water (TCLW) and vertical velocity from ERA-Interimre analysis are used. The study commences with the comparison of mean daily Integrated Water Vapor (IWV) and rainfall over Chennai. Further, the study proceeds ahead by analyzing the IWV, TCLW, Instantaneous Condensation Rate (ICR) and precipitation extreme efficiency during the heavy rainy days. The results are such as (i) the heavy rainy days are better scaled using IWV and TCLW than with surface air temperature and OLR (ii) ICR during the all heavy rainfall days found high at 700 mb level, and (iii) the precipitation extreme efficiency which is estimated using the ratio of precipitation extreme (obtained from vertical velocity, specific humidity gradient) and the ICR has shown a linear relationship with the surface reaching rainfall through the temporal and spatial smearing of raindrops expected