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Deep Learning (DL) based downscaling has recently become a popular tool in earth sciences. Multiple DL methods are routinely used to downscale coarse-scale precipitation data to produce more accurate and reliable estimates at local scales. Several studies have used dynamical or statistical downscaling of precipitation, but the availability of ground truth still hinders the accuracy assessment. A key challenge to measuring such a method's accuracy is comparing the downscaled data to point-scale observations, which are often unavailable at such small scales. In this work, we carry out DL-based downscaling to estimate the local precipitation using gridded data from the India Meteorological Department (IMD). To test the efficacy of different DL approaches, we apply SR-GAN and three other contemporary approaches (viz., DeepSD, ConvLSTM, and UNET) for downscaling and evaluating their performance. The downscaled data is validated with precipitation values at IMD ground stations. We find overall reasonably well reproduction of original data in SR-GAN approach as noted through M.S.E., variance statistics and correlation coefficient (CC). It is found that the SR-GAN method outperforms three other methods documented in this work (CCSR-GAN = 0.8806; CCUNET = 0.8399; CCCONVLSTM = 0.8311; CCDEEPSD = 0.8037). A custom V.G.G. network, used in the SR-GAN, is developed in this work using precipitation data. This DL method offers a promising alternative to other existing statistical downscaling approaches. It is noted that superiority in the SR-GAN approach is achieved through the perceptual loss concept, wherein it overcomes the issue of smooth reconstruction and is consequently able to capture better fine-scale details of data considered. [ABSTRACT FROM AUTHOR]

The application of twisted tape inserts in heat exchangers allows higher heat transfer rates with a simultaneous loss of energy due to turbulence and friction. In a conventional approach, the twisted tape is placed in the entire length of the heat exchanger. The present study explores the effect of the length of the twisted tape insert at a different twist ratio (TR) for 4700 < Re < 22,800. The insert length ratio (LR) ranges from 0.25 to 1 and the TR ranges from 1.5 to 6. The maximum Nusselt number corresponds to the LR of 0.75 at a TR of 1.5. The maximum thermo-hydraulic performance is found to be 3.2 for the LR of 0.75 at a TR of 1.5. [ABSTRACT FROM AUTHOR]

This article presents the application of machine learning (ML) algorithms in modeling the heat transfer correlations (e.g., Nusselt number and friction factor) for a heat exchanger with twisted tape inserts. The experimental data for the heat exchanger at different Reynolds numbers (Re), twist ratio (t), percentage of perforation (p), and a varied number of twisted tapes (n) were used for the correlation modeling. Three ML algorithms: polynomial regression (PR), random forest (RF), and artificial neural network (ANN) were used in the data-driven surrogate modeling. The hyperparameters of the ML models were carefully optimized to ensure generalizability. The performance parameters (e.g., R2 and mean absolute error (MAE)) of different ML algorithms were analyzed. It was observed that the ANN predictions of heat transfer coefficients outperform the predictions of PR and RF across different test datasets. Based on our analysis we make recommendations for future data-driven modeling efforts of heat transfer correlations and similar studies. [ABSTRACT FROM AUTHOR]

We develop a deep learning model (DL) for Indian Summer Monsoon (ISM) short-range precipitation forecasting using a ConvLSTM network. The model is built using daily precipitation records from both ground-based observations and remote sensing. Precipitation datasets from the Tropical Rainfall Measuring Mission and the India Meteorological Department are used for training, testing, forecasting, and comparison. For lead days 1 and 2, the correlation coefficient (CC), which was determined using predicted data from the previous five years and corresponding observational records (from both in-situ and remote sensing products), yielded values of 0.67 and 0.42, respectively. Interestingly, the CCs are even higher over the Western Ghats and Monsoon trough region. The model performance evaluated based on skill scores, Normalized Root Mean Squared Error (NRMSE), Mean absolute percentage error (MAPE) and ROC curves show a reasonable skill in short-range precipitation forecasting. Incorporating multivariable-based DL has the potential to match or even better the forecasts made by the stateof-the-art numerical weather prediction models. [ABSTRACT FROM AUTHOR]

The present experimental investigation incorporates the winglet twisted tapes as an insert to determine the thermal and hydraulic performance of a heat exchanger tube. The purpose of connecting the winglet to the twisted tape is to improve the heat transmission while minimizing the pressure loss by not disrupting the flow at the core portion. The thermal performance of a heat exchanger with turbulent promoters is assessed by varying geometric factors, such as the size of the promoters, Twist ratio ( y / W), Winglet pitch ratio ( P w / L T ), and Winglet height ratio ( h w / b w ). Experiments were carried out for Reynolds numbers (Re) ranging from 3,000 to 21,000. For a set of geometric parameters, the greatest thermohydraulic performance achieved was 1.58. Regression analysis is used to build a statistical association for Nusselt number N u and friction factor f , and the anticipated data obtained is of acceptable accuracy. The entropy generation is expressed in the form of entropy generation number and the Bejan number to fetch the dominance of thermal or friction entropy using winglet twisted tape. [ABSTRACT FROM AUTHOR]

This study focuses on the current problems in earth system science (ESS), where machine learning (ML) algorithms can be applied. It provides an overview of previous studies, ongoing work at the Ministry of Earth Sciences, Government of India, and future applications of ML algorithms to some significant earth science problems. We compare previous studies, a mind map of multidimensional areas related to ML and Gartner's hype cycle for ML in ESS. We mainly focus on the critical components in earth sciences, including studies on the atmosphere, oceans, biosphere, hydrogeology, human health and seismology. Various artificial intelligence (AI)/ML applications to problems in the core fields of earth sciences are discussed, in addition to gap areas and the potential for AI techniques. [ABSTRACT FROM AUTHOR]

The NCAR Command Language (NCL) is a popular scripting language used in the geoscience community for weather data analysis and visualization. Hundreds of years of data are analyzed daily using NCL to make accurate weather predictions. However, due to its sequential nature of execution, it cannot properly utilize the parallel processing power provided by High-Performance Computing systems (HPCs). Until now very few techniques have been developed to make use of the multi-core functionality of modern HPC systems on these functions. In the recent trend, open-source languages are becoming highly popular because they support major functionalities required for data analysis and parallel computing. Hence, developers of NCL have decided to adopt Python as the future scripting language for analysis and visualization and to enable the geosciences community to play an active role in its development and support. This study focuses on developing some of the widely used NCL routines in Python. To deal with the analysis of large datasets, parallel versions of these routines are developed to work within a single node and make use of multi-core CPUs to achieve parallelism. Results show high accuracy between NCL and Python outputs and the parallel versions provided good scaling compared to their sequential counterparts. [ABSTRACT FROM AUTHOR]

The aim of this paper is to determine the relaxation behavior of the therapeutic tape under different thermomechanical conditions over different time spans and to analyze the physical and mechanical properties of selected kinesiology tapes. The relaxation test was conducted under a static condition with two extended levels (25% and 50%) for one hour and a dynamic condition for 300 cycles with different loading-unloading values, strain rates, and temperatures. For both static and dynamic conditions, at a lower strain rate and higher load and temperature, the therapeutic tapes showed higher loss of internal stress and faster losses of efficiency. Under all selected conditions, the tape's stress has decreased rapidly. [ABSTRACT FROM AUTHOR]

Downscaling is necessary to generate high-resolution observation data to validate the climate model forecast or monitor rainfall at the micro-regional level operationally. Available observations generated by automated weather stations or meteorological observatories are often limited in spatial resolution resulting in misrepresentation or absence of rainfall information at these levels. Dynamical and statistical downscaling models are often used to get information at high-resolution gridded data over larger domains. As rainfall variability is dependent on the complex spatio-temporal process leading to non-linear or chaotic spatio-temporal variations, no single downscaling method can be considered efficient enough. In the domains dominated by complex topographies, quasi-periodicities, and non-linearities, deep learning (DL)–based methods provide an efficient solution in downscaling rainfall data for regional climate forecasting and real-time rainfall observation data at high spatial resolutions. We employed three deep learning-based algorithms derived from the super-resolution convolutional neural network (SRCNN) methods in this work. Summer monsoon season data from India Meteorological Department (IMD) and the tropical rainfall measuring mission (TRMM) data set were downscaled up to 4 times higher resolution using these methods. High-resolution data derived from deep learning-based models provide better results than linear interpolation for up to 4 times higher resolution. Among the three algorithms, namely, SRCNN, stacked SRCNN, and DeepSD, employed here, the best spatial distribution of rainfall amplitude and minimum root-mean-square error is produced by DeepSD-based downscaling. Hence, the use of the DeepSD algorithm is advocated for future use. We found that spatial discontinuity in amplitude and intensity rainfall patterns is the main obstacle in the downscaling of precipitation. Furthermore, we applied these methods for model data post-processing, in particular, ERA5 reanalysis data. Downscaled ERA5 rainfall data show a much better distribution of spatial covariance and temporal variance when compared with observation. This study is the first step towards developing deep learning-based weather data downscaling model for Indian summer monsoon rainfall data. [ABSTRACT FROM AUTHOR]

Direct Numerical Simulation (DNS) of turbulent cloud parcels are presented where particles evolve in response to the local values in supersaturation (s) led by turbulent fluctuations. A pseudo-spectral DNS is modified to incorporate aerosol particles and Cloud Condensation Nuclei (CCN) activation applying a droplet growth equation based on κ -Köhler theory that works for the whole range of warm cloud particles, from un-activated deliquesced aerosol particles to activated cloud droplets, that grow by condensation. The Lagrangian microphysics applied ensures that each particle experiences a supersaturation (fluctuations added to the mean) corresponding to its near-particle gas phase surroundings, which differs from the uniform parcel view where an average value of supersaturation, s ¯ , is applied to every particle in the domain. A non-turbulent Lagrangian parcel model with similar mean thermodynamics and CCN properties is compared with turbulent DNS parcels of varying fluctuation intensities to distinguish the impact of turbulence on CCN activation. It is shown that, in a given distribution, a subset of aerosols respond to fluctuations rather than the mean thermodynamics allowing particles of similar dry size to co-exist as un-activated haze particles as well as cloud droplets. The cloud microphysical properties are analysed in a series of DNS experiments with contrasting thermodynamic and aerosol properties. DNS results agrees with the general understanding of aerosol activation and cloud droplets evolution in response to various background conditions such as pristine and polluted aerosol distributions, composition of CCN with respect to organic - inorganic components and magnitude of vertical velocity. DNS considers turbulence-microphysics interactions in such problems providing additional knowledge on the role of turbulence in clouds. It is argued that incorporating turbulent fluctuations in simulating the CCN activation and droplet growth is well reasoned and a constructive way forward. [Display omitted] • Impact of turbulence fluctuations on activation and growth of cloud particles is studied via Direct Numerical Simulations. • Activation of CCN is impacted by turbulence fluctuations • Supersaturation field fluctuates, enabling coexistence of particles as unactivated haze and cloud droplets • Pollution, composition of aerosols and vertical velocity can alter the cloud microphysical properties. • DNS is useful for cloud microphysics under changing conditions and CCN characteristics, incorporating turbulence impacts. [ABSTRACT FROM AUTHOR]

The thermal performance of heat exchanger is considerably enhanced by the use of inserts. Twisted tape inserts are known for producing large heat transfer enhancements at the expense of fairly large friction penalty. With the objective to explore the effect of twisted tape with perforations and V cuts, the present study investigates the thermo-hydraulic performance of solid twisted tape, perforated twisted tape, and perforated twisted tape with double V cuts for the Reynolds number range of 2000–25000. During the experiments, the twist ratio of tapes is varied in the range of 2–6, while the depth ratio and width ratio of V cuts for perforated twisted tape with double V cuts are varied in the range of 0.2–0.27. The maximum enhancements in Nusselt number and friction factor were found to be 3.5 and 9.63, respectively, corresponding to the perforated twisted tape with double V cuts having V cut depth ratio and width ratio of 0.27 and twist ratio of 2. [ABSTRACT FROM AUTHOR]

Introduction: Chemicals that are present in cigarette/bidi smoke and gutka have been known to cause subclinical changes in myelin sheaths of peripheral nerves. Despite the antiquity and popularity of smoking and gutka chewing, its effect has not been investigated systematically in young adults. Aim: To investigate the chronic effects of smoking and gutka chewing on Nerve Conduction Velocity (NCV). Materials and Methods: This was a case-control study involving 40 male smokers (age group 20-60 years), 40 gutka chewers (age group 20-60 years) along with 40 age matched healthy male controls. The nerve conduction study was performed by using fully computerised Electromyography (EMG) and NCV machine. Sensory Nerve Conduction Velocity (SNCV) and Motor Nerve Conduction Velocity (MNCV) test of median and ulnar nerves was performed on subjects. Data was analysed by using unpaired t-test. Results: In this study of comparative analysis of total 120 subjects, [40 controls and 80 cases (40 cases of smokers and tobacco chewers each)], statistically significant changes (p-value<0.05) were found in the sensory NCV of both the nerves and motor NCV of median nerve in smokers whereas no such changes were found in motor NCV of both nerves in gutka chewers. Conclusion: It can be concluded that smoking causes more reduction in NCV than gutka chewing. [ABSTRACT FROM AUTHOR]

Present study investigates the heat transfer and friction characteristics of heat exchanger tube fitted with perforated twisted tape (PTT) insert having V cuts. A copper tube of 1 m length and 0.032 m inner diameter is used as test section to collect the experimental data by varying the twist ratio of PTT from 2 to 6 for the Reynolds number range of 2,700–23,400. V cuts are introduced in the PTT and the V-cut relative pitch ratio is varied from 1 to 2. The maximum thermo-hydraulic performance parameter is found to be 1.58. [ABSTRACT FROM AUTHOR]

The present work deals with the study of entropy generation in circular tube fitted with perforated twisted tape (PTT) insert with multiple V cuts. Experimental data pertaining to heat transfer and frictional losses are collected for solid twisted tape (STT), PTT, double V cut PTT, and PTT with multiple V cuts by varying the twist ratio in the range of 2-6 for the Reynolds number range of 2000-25,000. The entropy generation rate of heated tube with insert is found to be less than the smooth tube in most of the cases under similar operating conditions. The minimum value of entropy generation number corresponds to the PTT having twist ratio of 3. [ABSTRACT FROM AUTHOR]

The present study has been carried out on the calves less than one month of age suffering from clinical Theileriosis. All the cases came to Referral veterinary polyclinic, IVRI, Izatnagar, Bareilly for treatment during 2015. Erythrocytic LPO in clinically affected calves were significantly (P<0.05) higher than healthy animals. GSH, and SOD values in ailing calves were significantly (P<0.05) lower than healthy control and postreated calves. Catalase was also higher in infected calves but non significant. The hemoglobin concentration was significantly (P<0.05) lower in ailing animals. The erythrocyte fragility at 0.9%, 0.8% and 0.6% NaCl concentration was significantly (P<0.05) higher than the control group. However, there were less erythrocytic fragility observed in NaCl 0.4% and 0.2% concentration in infected animals. In conclusion, anemia occurs in Theileria annulata infection is due to corpuscular oxidative damage as revealed from lipid peroxidation and antioxidant status which contribute to RBC fragility and consequent anemia. [ABSTRACT FROM AUTHOR]

The dynamics and lifetime of atmospheric clouds are tightly coupled to entrainment and turbulent mixing. This paper presents direct numerical simulations of turbulent mixing followed by droplet evaporation at the cloud‐clear air interface in a meter‐sized volume, with an ensemble of up to almost half a billion individual cloud water droplets. The dependence of the mixing process on domain size reveals that inhomogeneous mixing becomes increasingly important as the domain size is increased. The shape of the droplet size distribution varies strongly with spatial scale, with the appearance of a pronounced negative exponential tail. The increase of relative dispersion during the transient mixing process is strongly dependent on the scale of the mixing and therefore on the Damköhler number, defined as the turbulence large‐eddy time scale divided by the cloud supersaturation relaxation time. Plain Language Summary: Clouds in the atmosphere are still one of the biggest uncertainty factors for more reliable weather and climate prognoses. Their dynamics and lifetime as a whole is tightly coupled to entrainment processes and subsequent turbulent mixing at their interface. Our work presents high‐resolution direct numerical simulations in a meter‐sized volume at the cloud‐clear air interface that study the turbulent motion down to the dissipative scales and describe the liquid water content as a population of up to half a billion individual droplets. The goal of the present numerical simulations is to provide a systematic analysis of the dependence of the mixing process on the simulation size. We show that inhomogeneous mixing, which is primarily caused by large‐scale vortices that sweep through the cloud interface, becomes increasingly important as the domain size is enlarged. The inhomogeneous mixing process enhances the width of the cloud droplet size distribution, with the enhancement getting stronger with increasing simulation size. Our work sheds new light on the multiple feedbacks in cloud dynamics that couple turbulence with the highly nonlinear thermodynamics of phase changes on multiple scales. Key Points: Scale dependence of microphysical response to entrainment and mixing investigated by varying simulation domain sizeMixing diagrams do not show significant scale dependence at cloud‐scale, but variability increases with large‐eddy time scale of turbulenceChange in relative dispersion of droplet size upon mixing shows a strong dependence on scale of mixing [ABSTRACT FROM AUTHOR]

The prediction of surface ozone is essential attributing to its impact on human and environmental health. Volatile organic compounds (VOCs) are crucial in driving ozone concentration; particularly in urban areas where VOC limited regimes are prominent. The limited measurements of VOCs, however, hinder assessing the VOC-ozone relationship. This work applies machine learning (ML) algorithms for temporal forecasting of surface ozone over a metropolitan city in India. The availability of continuous VOCs measurement data along with meteorology and other pollutants during 2014–2016 makes it possible to deduce the influence of various input parameters on surface ozone prediction. After evaluating the best ML model for ozone prediction, simulations were carried out using varied input combinations. The combination with isoprene, meteorology, NO x, and CO (Isop + MNC) was the best with RMSE 4.41 ppbv and MAPE 6.77%. A season-wise comparison of simulations having all data, only meteorological data and Isop + MNC as input showed that Isop + MNC simulation gives the best results during the summer season (RMSE: 5.86 ppbv, MAPE: 7.05%). This shows the increased ability of the model to capture ozone peaks (high ozone during summer) relatively better when isoprene data is used. The overall results highlight that using all available data doesn't necessarily give best prediction results; also critical thinking is essential when evaluating the model results. [Display omitted] • Influence of VOCs on surface ozone formation has been quantified using machine learning models. • Isoprene proves out to be a useful input parameter for predicting ozone peaks. • Season-wise comparison of ozone prediction results shows low accuracy for summer. [ABSTRACT FROM AUTHOR]

Inserts are used to enhance the heat transfer rates between the two fluids in heat exchanger tubes. A variety of tube inserts such as twisted tape, wire coil, swirl flow generator have been investigated for their effect on heat transfer rates and fluid friction. This paper reviews the works pertaining to the application of different class of tube inserts in order to comprehend the prevailing mechanism of fluid flow and heat transfer. An attempt has been made to elucidate the fluid flow behaviour sustained by the particular class of insert that controls the heat transfer rates across the thermal boundary layer attached to the tube wall. [ABSTRACT FROM AUTHOR]

Present Study has been carried out on the animals suffering from clinical bovine babesiosis in the Patna districts of Bihar, India. A total number of 36 lactating cows of different breeds and ages were included in the study to develop a prognostic indicator card for better and economic management of disease. There are two types of prognostic indicator systems that has been evolved viz numerical and categorical on the basis of oxidant marker, antioxidant status, trace mineral status, hematological changes and vital parameter changes between dead and survived suffering animals. Erythrocytic LPO in succumbed cases were significantly (P<0.01) higher than recovered ones. GPx, SOD and catalase in succumbed cases were significantly (P<0.01) lower than recovered ones. Trace elements Zn, Cu & Se in succumbed cases were significantly (P<0.01) lower than recovered ones. The body temperature, respiration and heart rate in dead cases were significantly (P<0.01) higher than recovered ones. In conclusion, Prognostic indicator card developed in the present study may be helpful in the management of clinical babesiosis in field condition . [ABSTRACT FROM AUTHOR]

A correction is presented for the article discussing response of droplets in cloudy filament due to turbulent mixing with dry air, and series of direct numerical simulations (DNS).

A direct numerical simulation (DNS) with the decaying turbulence setup has been carried out to study cloud-edge mixing and its impact on the droplet size distribution (DSD) applying thermodynamic conditions observed in monsoon convective clouds over Indian subcontinent during the Cloud Aerosol Interaction and Precipitation Enhancement EXperiment (CAIPEEX). Evaporation at the cloud-edges initiates mixing at small scale and gradually introduces larger-scale fluctuations of the temperature, moisture, and vertical velocity due to droplet evaporation. Our focus is on early evolution of simulated fields that show intriguing similarities to the CAIPEEX cloud observations. A strong dilution at the cloud edge, accompanied by significant spatial variations of the droplet concentration, mean radius, and spectral width, are found in both the DNS and in observations. In DNS, fluctuations of the mean radius and spectral width come from the impact of small-scale turbulence on the motion and evaporation of inertial droplets. These fluctuations decrease with the increase of the volume over which DNS data are averaged, as one might expect. In cloud observations, these fluctuations also come from other processes, such as entrainment/mixing below the observation level, secondary CCN activation, or variations of CCN activation at the cloud base. Despite large differences in the spatial and temporal scales, the mixing diagram often used in entrainment/mixing studies with aircraft data is remarkably similar for both DNS and cloud observations. We argue that the similarity questions applicability of heuristic ideas based on mixing between two air parcels (that the mixing diagram is designed to properly represent) to the evolution of microphysical properties during turbulent mixing between a cloud and its environment. [ABSTRACT FROM AUTHOR]

In the present work, sound power radiation response of a clamped rectangular plate with attached discrete masses and discrete patches is analysed. Four different thickness variations with taper ratios (Hx) 0.3, 0.6 and 0.9 are considered. Rayleigh integral is used to predict the sound radiation characteristics. Plate with four patches with linearly increasing - decreasing thickness variation at taper ratio (Hx = 0.3) is most effective in achieving the minimum peak sound power level. With this configuration (linearly increasing - decreasing), a wider choice of taper ratio of (0.15-0.45) is possible for obtaining minimum peak sound power level for all the cases considered. [ABSTRACT FROM AUTHOR]

In current practice of compression therapy, there has been a challenge of compression controlling and need for multiple devices to achieve different functions. Herein, the potential of a thermal-sensitive memory polymer, namely, polyurethane (MPU), is explored in designing a prototype that acts as a flexible bandage system to provide dual benefits (heat and pressure) simultaneously for a desired compression. After preconditioning, the thermomechanical behavior of the MPU becomes repeatable and consistent, which can be programmed to remember (store) and retrieve reversibly a prescribed internal stress, responsive to an external stimulus around its transition temperature ( T trans ). The smart bandage system is then built using the MPU actuator which integrates electric resistive wires as both a heat source for thermal therapy and stimulus for trigger control. The compression can also be easily switched between static and dynamic (massage) modes using a pro-set thermal stimulus. This paper also addresses several challenging issues and design considerations for the prototype. Theoretical analyses have been applied to predict the device performance, showing excellent agreement with experimental results. This work sheds insights for broadening the applications of stress memory and for engineering smart products needing stimulus responsive forces such as dynamic cushions, pressure garment and electronic actuators. [ABSTRACT FROM AUTHOR]

Proper level of pressure or compression generated by medical stocking or hosiery is the key element for successful treatment or management of chronic venous disorders such as oedema, leg ulcers, etc. However achieving the recommended compression level and, more importantly, sustaining it using stockings has been a major challenge to the health practitioners supervising the treatment. This work aims to investigate and design a smart compression stocking using shape-memory polymer that allows externally controlling the pressure level in the wrapped position on the leg. Based on thermodynamical rubber theories, we first derived several criteria that have to be satisfied simultaneously in order to achieve the controlled pressure adjustment using external heat stimuli. We then presented a case where such a stocking is developed using a blend yarn consists of selected shape-memory polyurethane and nylon filaments. Extensive experimental work has also been conducted to demonstrate the feasibility and explore the influencing factors involved. [ABSTRACT FROM AUTHOR]

A comparison of sound radiation behavior of plate in air medium with attached discrete patches/point masses having different thickness variations with different taper ratio of 0.3, 0.6, and 0.9 is analysed. Finite element method is used to find the vibration characteristics while Rayleigh integral is used to predict the sound radiation characteristics. Minimum peak sound power level obtained is at a taper ratio of 0.6 with parabolic increasing-decreasing thickness variation for plate with four discrete patches. At higher taper ratio, linearly increasing-decreasing thickness variation is another alternative for minimum peak sound power level suppression with discrete patches. It is found that, in low frequency range, average radiation efficiency remains almost the same, but near first peak, four patches or four point masses cause increase in average radiation efficiency; that is, redistribution of point masses/patches does have effect on average radiation efficiency at a given taper ratio. [ABSTRACT FROM AUTHOR]

Background Padding bandage is an essential component of the multi-layer compression system used for chronic venous management. Padding plays a critical role in managing pressure over bony prominences and ensuring uniform pressure distribution around the limb circumference. Moreover, it helps in the management of heat, moisture and body fluids or exudates during the course of treatment to provide comfort to the patients. Objective To study the effect of structural and constructional parameters on the compressional (pressure absorption or distribution) and comfort (air, moisture and heat transmission) characteristics of the padding. Methods This research focuses on the examination of polypropylene based nonwoven padding samples. Critical factors, i.e., fiber linear density, needling density and mass per unit area, have been chosen for this study to find their significance on the performance of padding. Simple laboratory based methods have been proposed to examine pressure reduction and comfort characteristics of the padding. Results Pressure absorption by the padding decreases with increase in mass per unit area and needling density of the padding. A padding composed of thicker fiber absorbs more pressure compared to padding made from thinner fiber. On examining comfort, it was found that the air and moisture vapor transmission increase with decrease in mass per unit area and needling density but have opposite effects with fiber linear density (p < 0.01). The heat transmission decreases with increase in both mass per unit area and fiber linear density but has opposite effect for needling density. Conclusion Padding composed of thick fiber with low mass per unit area and needling density could be more effective in pressure management and ensuring comfort. These results could be very useful for health practitioners, fabric engineers and manufactures to understand the significance of fibrous materials and their role in compression management, and could be further used as design consideration to optimized padding performance. [ABSTRACT FROM AUTHOR]

Padding is an essential component in a multilayer compression bandaging system, used inside the compression bandage through which substantial amount of pressure is exerted on the limb of patient for treatment of venous leg ulcers. As a result, the liquid transmission behavior of padding is also critical in managing body fluids or sweat exuded from the affected limb, reducing the excessive moisture build-up around the wound and thereby ensuring comfort to and hence a better compliance from the patients. This study investigates the in-plane fluid transport characteristics of needle-punched nonwoven padding bandages. It first reviewed the existing studies related to the problems, and discussed their limits and possible improvements in dealing with complex fluid transport issues in textile porous media. The measurement of fluid transport under different pressure levels was then done using a newly designed apparatus capable of simultaneously tracing the liquid in-plane spreading along different directions, and obtaining several transport characteristics of a testing sample, e.g. the liquid flow anisotropy, the rate of movement, the area of wet surface with time, etc. Also the effects of several important factors, such as the levels of pressure applied, the specimen bulk density, and needling density of the padding products, have been experimentally investigated. In addition, based on an extended Lucas–Washburn theory, we calculated the liquid flow distance, both instantaneous speed and a more useful time-averaged speed vav at any given direction, and also defined a flow anisotropy index IA as a convenient parameter to represent the material flow anisotropy. The applications of vav and IA to actual samples have demonstrated the usefulness of these parameters in characterizing the flow nature and behavior of the materials. [ABSTRACT FROM AUTHOR]

The wax present in petroleum sludge, generated by refineries and at crude production sites, consists of paraffin hydrocarbons (C18–C36) known as paraffin wax and naphthenic hydrocarbons (C30–C60). The present study is aimed at the recovery of wax from petroleum oily sludge by microwave-assisted solvent extraction using a Toluene/MEK mixture and subsequently de-crystallizing the wax. The process variables affecting the microwave-assisted solvent extraction are optimized for recovery of wax. The simultaneous effects of process variables such as irradiation time (2–10 minutes), solvent to sludge ratio (40–80 wt%), reactant volume (100–300 ml), and microwave power (80–400 W) on the recovery of wax were evaluated. A central composite design and response surface methodology were used for the optimization of the extraction process. Based on the central composite design, quadratic models were developed to correlate the extraction process variables with the responses and the models were analyzed using appropriate statistical methods for analysis of variance. Optimization of process variables shows the maximum recovery of wax was about 79.57% at 300 ml of reactant volume with microwave power output of 400 W at 7.6 minutes of retention time with 56.56% of Toluene/MEK to sludge ratio. [ABSTRACT FROM AUTHOR]

This study was conducted to examine the sensitivity of weather parameters and CO2 concentration to wheat production under two irrigation regimes viz. full irrigation and limited irrigation, using CERES-Wheat model. Field experiment data from the 2016-17 and 2017-18 rabi seasons on wheat cultivar HD-2967 with three sowing dates and five irrigation regimes were used to calibrate and validate the CERES-Wheat crop simulation model. Validation results indicated very good agreement between simulated and observed values under five, four, and three irrigations regimes as compared to lower irrigation regimes. Under full irrigation and limited irrigation, grain yield sensitivity to incremental unit of mean temperature from 1 to 3°C revealed a decrease of 6 to 22% and 8 to 16%, respectively. Temperature decreases of 1-3°C resulted in a gradual increase in yield of 10-28 and 6.5-20%, respectively, under full and limited irrigation. The combined effect of higher mean temperature and lower solar radiation revealed that wheat yield was more sensitive to temperature than solar radiation. Furthermore, the combined effect of mean temperature and CO2 level revealed that higher levels of CO2 concentration yielded the greatest benefits with a 1 °C increase in temperature, but further increases in temperature reduced the beneficial effect of elevated CO2 level under both irrigation conditions. [ABSTRACT FROM AUTHOR]

ABSTRACT Like shape memory polymers, a novel phenomenon of stress memory was shown in which the stress of a material can respond to an external stimulus. This concept was further enlightened by a switch-spring-frame model that would eliminate the limitation of existing models which overlooked the stimulus responsive nature of such polymers. The discovery being reported in this article was stemmed from a real case study into shape memory polymer fibers in compression stocking for varicose veins. The breakthrough of stress memory enabled researchers to develop applications needing stimuli-responsive forces, which can broaden the horizon of such smart polymers in emerging smart products in many multidisciplinary fields such as sensors, stress garments, and massage devices, electronic skins, and artificial muscles. © 2015 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2015, 53, 893-898 [ABSTRACT FROM AUTHOR]

The entrainment of clear air and its subsequent mixing with a filament of cloudy air, as occurs at the edge of a cloud, is studied in three-dimensional direct numerical simulations that combine the Eulerian description of the turbulent velocity, temperature, and vapor fields with a Lagrangian cloud droplet ensemble. Forced and decaying turbulence is considered, such as when the dynamics around the filament is driven by larger-scale eddies or during the final period of the life cycle of a cloud. The microphysical response depicted in n d − 〈 r3〉 space (where n d and r are droplet number density and radius, respectively) shows characteristics of both homogeneous and inhomogeneous mixing, depending on the Damköhler number. The transition from inhomogeneous to homogeneous mixing leads to an offset of the homogeneous mixing curve to larger dilution fractions. The response of the system is governed by the smaller of the single droplet evaporation time scale and the bulk phase relaxation time scale. Variability within the n d − 〈 r3〉 space increases with decreasing sample volume, especially during the mixing transients. All of these factors have implications for the interpretation of measurements in clouds. The qualitative mixing behavior changes for forced versus decaying turbulence, with the latter yielding remnant patches of unmixed cloud and stronger fluctuations. Buoyancy due to droplet evaporation is observed to play a minor role in the mixing for the present configuration. Finally, the mixing process leads to the transient formation of a pronounced nearly exponential tail of the probability density function of the Lagrangian supersaturation, and a similar tail emerges in the droplet size distribution under inhomogeneous conditions. [ABSTRACT FROM AUTHOR]

The article focuses on prospective applications of artificial intelligence/machine (AI/ML) learning techniques in earth sciences. Topics include the application of AI/ML to earth sciences problems has conducted, the main aim of the meeting was to gather researchers working on AI/ML and scientists from different areas of earth sciences to exchange knowledge, and the delegates has shared their opinions about prospective work has pursued on topics has related to earth sciences.

Turbulent mixing and entrainment at the boundary of a cloud is studied by means of direct numerical simulations that couple the Eulerian description of the turbulent velocity and water vapor fields with a Lagrangian ensemble of cloud water droplets that can grow and shrink by condensation and evaporation, respectively. The focus is on detailed analysis of the relaxation process of the droplet ensemble during the entrainment of subsaturated air, in particular the dependence on turbulence timescales, droplet number density, initial droplet radius and particle inertia. We find that the droplet evolution during the entrainment process is captured best by a phase relaxation time that is based on the droplet number density with respect to the entire simulation domain and the initial droplet radius. Even under conditions favoring homogeneous mixing, the probability density function of supersaturation at droplet locations exhibits initially strong negative skewness, consistent with droplets near the cloud boundary being suddenly mixed into clear air, but rapidly approaches a narrower, symmetric shape. The droplet size distribution, which is initialized as perfectly monodisperse, broadens and also becomes somewhat negatively skewed. Particle inertia and gravitational settling lead to a more rapid initial evaporation, but ultimately only to slight depletion of both tails of the droplet size distribution. The Reynolds number dependence of the mixing process remained weak over the parameter range studied, most probably due to the fact that the inhomogeneous mixing regime could not be fully accessed when phase relaxation times based on global number density are considered. [ABSTRACT FROM AUTHOR]

Understanding the stress relaxation behavior of the compression bandage could be very useful in determining the behavior of the interface pressure exerted by the bandage on a limb during the course of the compression treatment. There has been no comprehensive study in the literature to investigate the pressure profile (interface pressure with time) generated by a compression bandage when applied at different levels of strain. The present study attempts to describe the pressure profile, with the use of a quasi-linear viscoelastic model, generated by a compression bandage during compression therapy. The quasi-linear viscoelastic (QLV) theory proposed by Fung (Fung, 1972, "Stress Strain History Relations of Soft Tissues in Simple Elongation," Biomechanics: Its Foundations and Objectives, Y. C. Fung, N. Perrone, and M. Anliker, eds., Prentice-Hall, Englewood Cliffs, NJ, pp. 181-207). was used to model the nonlinear time- and history-dependent relaxation behavior of the bandage using the ramp strain approach. The regression analysis was done to find the correlation between the pressure profile and the relaxation behavior of the bandage. The parameters of the QLV model, describing the relaxation behavior of the bandage, were used to determine the pressure profile generated by the bandage at different levels of strain. The relaxation behaviors of the bandage at different levels of strain were well described by the QLV model parameters. A high correlation coefficient (nearly 0.98) shows a good correlation of the pressure profile with the stress relaxation behavior of the bandage The prediction of the pressure profile using the QLV model parameters were in agreement with the experimental data. The pressure profile generated by a compression bandage could be predicted using the QLV model describing the nonlinear relaxation behavior of the bandage. This new application of the QLV theory helps in evaluating the bandage performance during compression therapy as scientific wound care management. [ABSTRACT FROM AUTHOR]

Following our previous investigation of the turbulence impact on cloud-base single-size CCN activation, this study considers a similar problem assuming CCN size distribution obtained from field measurements. The total CNN concentration is taken as either 200 cm−3 to represent clean conditions, or as 2000 cm−3 to represent polluted conditions. CCN is assumed to be sodium chloride. The CCN activation in the rising nonturbulent adiabatic parcel is contrasted with the activation within a rising adiabatic parcel filled with inertial-range homogeneous isotropic turbulence. The turbulent parcel of 643 m3 and the turbulent kinetic energy dissipation rate of 10−3 m−2 s−3 are used in most of the simulations. Results for a range of mean parcel ascent rates, between 0.125 and 8 m s−1, are discussed. Overall, the adiabatic turbulent parcel simulations show results consistent with the adiabatic nonturbulent parcel, with higher activated CCN concentrations for stronger parcel ascent rates. The key difference is a blurriness of the separation between dry CCN size bins featuring activated and nonactivated (haze) CCN, especially for weak mean ascent rates. The blurriness comes from CCN getting activated and subsequently deactivated in the fluctuating supersaturation field, instead of all becoming cloud droplets above the cloud base. This leads to significantly larger spectral widths in turbulent parcel simulations compared to the nonturbulent parcel when activation is completed. Modeling results are discussed in the context of the impact of turbulent fluctuations on CCN activation documented in laboratory experiments using the Pi chamber. [ABSTRACT FROM AUTHOR]

A case of an unusual occurrence of mature solid teratoma of the rectum is reported with a review of the literature. A 30-year-old woman presented with bleeding per anum without any alteration in her bowel habits. Sigmoidoscopy revealed a pedunculated polypoidal mass arising from the posterior wall of the rectum. A polypectomy specimen on microscopy showed the components of all the three germ layers. This may be the largest polypoidal type of rectal teratoma reported in the English literature to date. A review of the literature indicated only 50 previously reported cases, with all except one being female. The common presentations include prolapse and bleeding per anum. [ABSTRACT FROM AUTHOR]

Entrainment and mixing processes occur during the entire life of a cloud. These processes change the droplet size distribution, which determines rain formation and radiative properties. Since it is a microphysical process, it cannot be resolved in large scale weather forecasting models. Small scale simulations such as Direct Numerical Simulations (DNS) are required to resolve the most minute scale of these processes. The DNS of cloud dynamics are performed by integrating two mathematical models, Eulerian and Lagrangian, in a coupled way. Running DNS is a tedious task as it requires a huge amount of computational resources. In this work, we provide a projection of the required resources for running DNS in different size domains. Visualizing these large simulations presents an added challenge, as they generate petabytes of data. Visualization plays a vital role in analyzing and understanding these huge data outputs. Here, we experimented with multiple tools to conduct a visual analysis of this data. Two of these tools are well established and tested technologies: ParaView and VAPOR. The others are emergent technologies in the development phase. This data simulation and visualization, in addition to exploring DNS as mentioned above, provided an opportunity to test and improve development of several tools and methods. • Simulation of entrainment and mixing process at cloud edge. • Projection of computational requirement for different domain sizes. • Super-linear scaling. • 3D visualization of DNS data. • Emergent tool for visual analysis. [ABSTRACT FROM AUTHOR]

Abstract: In this study we discuss in detail various strategies involved in evolving MIMD parallel algorithms for preconditioners such as ILU, SSOR, etc., on a cluster of PCs under ANULIB message passing environment. The task flow graphs used as logical basis in designing parallel algorithms are introduced. Parallel preconditioners are used in accelerating the convergence of Krylov solvers such as GMRES, CGM. The preconditioned iterative solvers are tested for performance on heat transfer applications such as (a) convection in trapezoidal and square porous enclosure and (b) reaction–diffusion problem, etc. [Copyright &y& Elsevier]

In this study we introduce strategies for a load-balanced parallelization of sparse matrix computations on a cluster of PCs with minimum communication overhead. Based on these strategies a parallel sparse Conjugate Gradient Algorithm for CFD computations is evolved. The proposed parallel algorithm is implemented on Anu-cluster, a cluster of eight PCs, under ANULIB message passing environment. The parallel sparse code is tested both on linear and non-linear problems and found to give good performance. Results are compared with those from dense matrix computations. [Copyright &y& Elsevier]

In this study, parallel numerical algorithms for Krylov methods such as GMRES(k), Bi-CGM, Bi-CGSTAB, etc., for handling large-scale linear systems resulting from finite-difference analysis (FDA) and finite-element analysis (FEA) of coupled nonlinear partial differential equations (PDEs) describing problems in heat transfer applications are discussed. Parallel code has been successfully implemented on an eight-noded cluster under ANULIB message-passing library environment. Bi-CGM and ILU-GMRES(k) are found to give good performance for linear systems resulting from FEA, whereas Bi-CGSTAB is seen to give good performance with linear systems resulting from FDA. [ABSTRACT FROM AUTHOR]

Inhibition of proteasome activity is associated with a reduction in proliferation and apoptosis in cancer cells, depending upon the extent of inhibition. We have reported that a minimal inhibition of proteasome activity prevented adenosine 3′5′-cyclic monophosphate (cAMP)-induced differentiation and caused apoptosis in murine neuroblastoma (NB) cells in culture. In order to establish whether an elevated cAMP level increases the sensitivity of proteasome to its inhibitors, MG-132 and lactacystin (proteasome inhibitors) were added concomitantly with a stimulator of adenylate cyclase (prostaglandin A1) and an inhibitor of cyclic nucleotide phosphodiesterase (RO20-1724). Results showed that concentrations of MG-132 that did not reduce or that minimally inhibited proteasome activity also did not affect the proliferation of undifferentiated NB cells. However, these concentrations of MG-132 in the presence of an elevated cAMP level markedly inhibited proteasome activity and caused extensive cell death. Similar results were obtained with lactacystin. In normal murine fibroblasts, cAMP-induced reduction in proliferation was not affected by any concentration of MG-132 used in this study. These results suggest that proteasome exhibits increased sensitivity to its inhibitors following an elevation of cAMP level in NB cells, but not in normal fibroblasts, and that this may account for the enhanced cell death in NB cells. Thus, the strategy of using low doses of a proteasome inhibitor in combination with a cAMP-stimulating agent may be useful in pre-clinical and clinical studies on NB tumor because of the selectivity of the effect on cancer cells. [Copyright &y& Elsevier]

A correction to the article "Lagrangian mixing dynamics at the cloudy-clear air interface," by B. Kumar and colleagues published in an issue of the "Journal of Atmospheric Science."

Intensive mono-cropping without a balanced supply of nutrients and declining water resources are degrading soil health, and as a consequence, agriculture production is becoming unsustainable and causing environmental degradation. The field experiment was conducted during Rabi season to assess the effect of an irrigation schedule, nutrient management, and wheat (Triticum aestivum L.) varieties on soil microbial biomass carbon (SMBC) and soil enzymes activities. Two nutrient levels, recommended rate of chemical fertilizer (RDF) and 50% RDF + 50% recommended dose of nitrogen (RDN) through farmyard manure (FYM) designated as Integrated Nutrient Sources (INS), and three irrigations levels, one irrigation at crown root initiation (CRI), two irrigations at CRI and flowering stages, and five irrigations at all main stages of the crop (CRI, tillering, jointing, flowering, and grain filling) were allocated to main-plots while four varieties of wheat, HD 2967, WR 544, HD 2987, and HD 2932, were allocated to sub-plots. The results revealed that SMBC and activities of dehydrogenase, alkaline phosphatase enzymes, and acid phosphatase were higher under restricted irrigation (irrigation at CRI stage) than other irrigation schedules. SMBC, dehydrogenase, acid phosphatase, and alkaline phosphatase activities were 73.0 µg g soil−1, 86.0 µg TPF g soil−1d−1, 39.6 µg PNP g soil−1 h1, and 81.8 µg PNP g−1 soil h−1, respectively, with the use of INS that was higher than RDF. Root weight and root volume followed a similar pattern. Applying single irrigation at CRI left behind the maximum available nitrogen (166.4 kg ha−1) in soil compared to other irrigation schedules and it was highest (149.31 kg ha−1) with the use of INS. Moreover, total organic carbon (TOC) was 0.44 and 0.43% higher with irrigation at CRI stages and the use of INS, respectively. The INS with single irrigation at the CRI stage is important to improve the root growth, SMBC dehydrogenase, alkaline phosphatase, and acid phosphatase enzyme activity in the wheat production system. [ABSTRACT FROM AUTHOR]

The article discusses workshop on cloud dynamics, micro-physics and small-scale simulations held at the Indian Institute of Tropical Meteorology in Pune, India from August 13-17, 2018. It is mentioned that Workshop aims to bring together scientists and students to exchange ideas and improve our understanding on the physics of clouds and their numerical simulations. The article adds scientists including W. W. Grabowski, Suryachandra A. Rao, and David Richter presented various papers.

This paper examines the impact of cloud-base turbulence on activation of cloud condensation nuclei (CCN). Following our previous studies, we contrast activation within a nonturbulent adiabatic parcel and an adiabatic parcel filled with turbulence. The latter is simulated by applying a forced implicit large-eddy simulation within a triply periodic computational domain of 643 m3. We consider two monodisperse CCN. Small CCN have a dry radius of 0.01 μm and a corresponding activation (critical) radius and critical supersaturation of 0.6 μm and 1.3%, respectively. Large CCN have a dry radius of 0.2 μm and feature activation radius of 5.4 μm and critical supersaturation 0.15%. CCN are assumed in 200-cm−3 concentration in all cases. Mean cloud-base updraft velocities of 0.33, 1, and 3 m s−1 are considered. In the nonturbulent parcel, all CCN are activated and lead to a monodisperse droplet size distribution above the cloud base, with practically the same droplet size in all simulations. In contrast, turbulence can lead to activation of only a fraction of all CCN with a nonzero spectral width above the cloud base, of the order of 1 μm, especially in the case of small CCN and weak mean cloud-base ascent. We compare our results to studies of the turbulent single-size CCN activation in the Pi chamber. Sensitivity simulations that apply a smaller turbulence intensity, smaller computational domain, and modified initial conditions document the impact of specific modeling assumptions. The simulations call for a more realistic high-resolution modeling of turbulent cloud-base activation. [ABSTRACT FROM AUTHOR]

The article presents a clinical study of four cases on canine ehrlichiosis and associated corneal opacity. Four out of eleven blood smear examination of the dogs with corneal opacity were positive for Ehrlichiosis. The vision of the dogs was restored with the combination therapy of glucocorticoid intraocular, diuretic and oxytetracycline and doxycycline.

The article presents a case study regarding neonatal calf diarrhea. The subject of the study includes 30 calves with bacterial origin diarrhea. These calves were taken for study on clinical symptoms, haematobiochemical changes, and therapeutic study on the basis of culture and sensitivity of faeces. The article examines the treatment efficacy based on the clinical improvement, reduction in degree of dehydration and gross changes in faecal consistency.