Search

A broad spectrum of advanced medications appears yearly following the accelerated evolution of the chemical and pharmaceutical industry. In this paper, various degree-based and neighborhood degree sum-based topological indices of some anti-HIV drugs are explored applying the M-polynomial and NM-polynomial formulations. Moreover, QSPR analysis is carried out for the topological indices with regard to the physico-chemical properties of the anti-HIV drugs. The activity of nucleoside and non-nucleoside reverse transcriptase inhibitors is implemented as in drug configuration to manifest the significance of topological indices in the medicinal world. The procured outcomes affirm that topological indices being stud- ied reflect effective correlation in accordance to physical and chemical properties of the anti-HIV drugs and consequently can assist in development of advanced and promising pharmaceutical for HIV medication.

Topological indices serve as a crucial component in chemical graph theory linked with some molecular structure. The First and Second Zagreb Indices are one among the earliest and extensively explored molecular descriptors. The study on equitable zagreb indices have been initiated earlier by Akram Alqesmah, Anwar Alwardi and R. Rangarajan based on the equitable degree of the vertices. In this paper, we introduce the first and second equitable and non-equitable zagreb polynomials and compute the exact values of the respective equitable and non-equitable zagreb indices for polycyclic aromatic hydrocarbons. We have also utilised certain formulations for the determination of the corresponding relative equitable and non-equitable zagreb indices of the chemical graph. Further, QSPR analysis is carried out for the topological indices with regard to the physico-chemical properties of the polycyclic hydrocarbon molecules.

Effector CD8+ T cells rely primarily on glucose metabolism to meet their biosynthetic and functional needs. However, nutritional limitations in the tumor microenvironment can cause T-cell hyporesponsiveness. Therefore, T cells must acquire metabolic traits enabling sustained effector function at the tumor site to elicit a robust antitumor immune response. Here, we report that IL12-stimulated CD8+ T cells have elevated intracellular acetyl CoA levels and can maintain IFNγ levels in nutrient-deprived, tumor-conditioned media (TCM). Pharmacological and metabolic analyses demonstrated an active glucose–citrate–acetyl CoA circuit in IL12-stimulated CD8+ T cells supporting an intracellular pool of acetyl CoA in an ATP-citrate lyase (ACLY)–dependent manner. Intracellular acetyl CoA levels enhanced histone acetylation, lipid synthesis, and IFNγ production, improving the metabolic and functional fitness of CD8+ T cells in tumors. Pharmacological inhibition or genetic knockdown of ACLY severely impaired IFNγ production and viability of CD8+ T cells in nutrient-restricted conditions. Furthermore, CD8+ T cells cultured in high pyruvate–containing media in vitro acquired critical metabolic features of IL12-stimulated CD8+ T cells and displayed improved antitumor potential upon adoptive transfer in murine lymphoma and melanoma models. Overall, this study delineates the metabolic configuration of CD8+ T cells required for stable effector function in tumors and presents an affordable approach to promote the efficacy of CD8+ T cells for adoptive T-cell therapy.Significance:IL12-mediated metabolic reprogramming increases intracellular acetyl CoA to promote the effector function of CD8+ T cells in nutrient-depleted tumor microenvironments, revealing strategies to potentiate the antitumor efficacy of T cells.

Supplementary Table from Intracellular Acetyl CoA Potentiates the Therapeutic Efficacy of Antitumor CD8+ T Cells

The network systems and graphical analysis through the study ofstructural characteristics is a vast field of growing importance inresearch. Topological indices have a significant and crucial role inthe study of structure–property relationships. In this paper, weexamine constructional transformed networks constructed by unique vertex-edge incidence and mutual adjacency associations. Expres-sions for the first and second hyper Zagreb indices and co-indices of these transformed networks and their complements are obtained. MSC Classification: 05C09 , 05C90 , 05C92

An attempt is made in this study to forecast the central pressure drop (PD) and maximum sustained wind speed (MSWS) associated with cyclonic systems at the stage of the highest intensity over Arabian Sea using artificial neural network models. The cyclonic systems include the phases from deep depression to extreme severe cyclones. The sea surface temperature, mid-tropospheric relative humidity, surface to middle tropospheric equivalent potential temperature gradient, inverse of wind shear and vertical wind velocity at 200 hPa level are evaluated as the most suitable predictors through principal component analysis. Various neural network models with different architectures have been trained with the data from 1990 to 2012 to select the best forecast model. The prediction skill of the intelligent models is evaluated by different accuracy measures. The results show that the multi-layer perceptron (MLP) model with five input layers, one hidden layer with four nodes and one output layer is the best model for forecasting PD with minimum prediction error of 0.14 at 36 h lead time, whereas the MLP model with five input layers, one hidden layer with five nodes and one output layer is found to be the best model for forecasting MSWS with minimum prediction error of 0.19 at 48 h (h) lead time. The results are well validated with the observations from 2013 to 2018. The forecast skill of MLP model is compared with multiple linear regression model and existing operational and numerical weather prediction models.

The present research intends to develop a neuro-computing based adaptive intelligent model to predict the pressure drop (PD) at centre and maximum sustained wind speed (MSWS) linked to vortical convective system at the stage of the utmost strength over the Bay of Bengal (BOB) of the North Indian Ocean (NIO). The vortical convective systems considered in this study incorporate the stages from deep depression to extreme severe cyclones. The low level vorticity (LLV), mid-tropospheric relative humidity (MRH), upward wind speed at 850, 500 and 200 hPa pressure levels are obtained as the most suitable input parameters through factor analysis. The adaptive neural network models are trained with the data from 1990 to 2015 to forecast the PD and MSWS over BOB. The result reveals that the multilayer perceptron (MLP) model provides good accuracy at 6 and 30 h lead time in forecasting the PD. But minimum error is obtained at 6 h time before in anticipating the PD at the highest intensity stage of vortical convective system. The result further shows that the MLP model is the most competent for projecting MSWS at the peak intensity stage of vortical convective systems with minimum forecast error at 60 h lead time. The model outputs are compared to the existing conventional models and subsequently the outcomes are supported with observations from 2016 to 2019.

Background: Care giving of children with leukemia involves considerable stress and anxiety on the part of family caregivers. Although caregivers’ burden is a crucial predictor of the health of both the child and the caregiver, it is often overlooked. Aim and Objectives: The present study aimed to assess the burden faced by caregivers of pediatric leukemia patients attending a tertiary care hospital in West Bengal, to elicit their sociodemographic characteristics and patients’ profile, and to find out relationship among these, if any. Materials and Methods: The study was descriptive observational type with cross-sectional design. It was conducted among caregivers of pediatric leukemia patients. Data were collected from 38 caregivers using predesigned, pretested, semi-structured schedule, and patients’ records. Burden was measured using Zarit Burden Interview, which is a 22 item 5-point Likert scale. Data were compiled and analyzed in Microsoft Excel and Statistical Software for the Social Sciences 20.0 for statistical analysis. Sociodemographic and clinical variables were expressed as number, percentages, mean, and standard deviations. To find out the association between different factors and caregiver burden, a logistic regression model was used. P < 0.05 was considered as statistically significant. Results: Majority of the caregivers were the mothers of the patients (68.42%), and most of the families of caregivers belonged to lower middle class according to modified BG Prasad Scale. Half of the caregivers (50%) experienced moderate–to-severe burden according to Zarit Burden Interview. Association was found between burden experienced and duration of disease and treatment. However, socioeconomic status was found to be the most significant determinant of burden as per multiple logistic regression by ENTER method. Conclusions: Majority of the caregivers were having moderate to severe and severe burden, which was significantly more among people coming from lower socioeconomic status. Prolonged disease duration and treatment were also found to be associated with increased burden of the caregivers.

The threat of epidemic outbreaks like SARS-CoV-2 is growing owing to the exponential growth of the global population and the continual increase in human mobility. Personal protection against viral infections was enforced using ambient air filters, face masks, and other respiratory protective equipment. Available facemasks feature considerable variation in efficacy, materials usage and characteristic properties. Despite their widespread use and importance, face masks pose major potential threats due to the uncontrolled manufacture and disposal techniques. Improper solid waste management enables viral propagation and increases the volume of associated biomedical waste at an alarming rate. Polymers used in single-use face masks include a spectrum of chemical constituents: plasticisers and flame retardants leading to health-related issues over time. Despite ample research in this field, the efficacy of personal protective equipment and its impact post-disposal is yet to be explored satisfactorily. The following review assimilates information on the different forms of personal protective equipment currently in use. Proper waste management techniques pertaining to such special wastes have also been discussed. The study features a holistic overview of innovations made in face masks and their corresponding impact on human health and environment. Strategies with SDG3 and SDG12, outlining safe and proper disposal of solid waste, have also been discussed. Furthermore, employing the CFD paradigm, a 3D model of a face mask was created based on fluid flow during breathing techniques. Lastly, the review concludes with possible future advancements and promising research avenues in personal protective equipment.

The current research aims at investigating role of three different types of surfactants and their binary mixtures in producing high cooling rate during jet impingement on a hot steel plate (100 mm × 100 mm × 6 mm) having initial surface temperature above 900 °C. The surfactants used are Sodium dodecyl sulphate (anionic), cetyltrimethylammonium bromide (cationic) and Polysorbate 20 (Tween 20, non-ionic). The surface tension values of the surfactants and their mixed systems have been measured and it has been observed that the binary mixtures at specific compositions show lower surface tension compared to the pure ones mainly due to synergism. The cooling results reveal that the mixture of cationic and non-ionic surfactants produces the highest cooling rate amongst all the systems. The maximum cooling rate achieved is 182 °C/s for the composition of 25 vol% CTAB and 75 vol% Tween 20 and it is 67% more than that of pure water, 23% more compared to pure CTAB and and 7.7% more than that of pure Tween 20. Thus it can be seen that ultrafast cooling of a 6 mm thick steel plate can be achieved by using optimized concentrations of mixed surfactant additives and this leads to improvement of quality of steel produced.

In the current work, authors have performed extensive spray cooling experiments on a 6 mm thick hot stainless steel plate (>900 °C). The work has been separated into two distinctive parts. The first part involves optimization of water flow rate and spray impingement height based on maximum surface cooling rate and heat flux value. The highest cooling rate and heat flux of 133.7 °C/s and 2.21 MW/m2 were attained for a water flow rate of 16 lpm and impingement height of 6 cm. In the second part, different surfactants (cationic, CTAB; anionic, SDS; non-ionic, Tween 20), and polymer (PVP, water soluble) were added in to the water to study its impact on heat transfer parameters such as surface cooling rate, heat flux, and heat transfer coefficient. Amongst all the additives, the maximum enhancement in cooling rate and critical heat flux was achieved for non-ionic (Tween 20) based water solution which is 25.6% (168.2 °C/s) and 19.91% (2.65 MW/m2) higher than what had been attained by water spray. High speed photography was used at a lower temperature to visualize a single droplet impact and to understand the effect of surface tension and underlying physics on the heat transfer phenomenon. This study revealed that upon impingement, surfactant and polymer added drops disintegrate into multiple drops, increasing the overall contact area, and thereby enhancing the heat transfer rate.

The focus of the present study is to investigate the effect of surfactant addition on thermo-physical properties, stability, and heat transfer performance of Cu-Zn-Al LDH nanofluid. For this purpose, both an anionic (Sodium dodecyl Sulfate (SDS), concentration: 200–800 ppm) and a non-ionic surfactant (Tween 20, concentration: 28–70 ppm) have been used at different concentrations with Cu-Zn-Al LDH nanofluid at a fixed concentration. Among both the surfactants, SDS displayed better compatibility and thermo-physical properties when combined with Cu-Zn-Al LDH nanofluid compared to LDH-Tween 20 combination. The addition of both the surfactants into the nanofluid suspension has led to reduced surface tension and viscosity value which is highly desired for better wettability and improved contact between the coolant and the hot surface. The maximum increment in thermal conductivity value was attained in the case of Cu-Zn-Al LDH at 600 ppm SDS concentration which is 20.9% higher than the water. In terms of stability analysis, the highest zeta potential value of −52.7 mV was also observed for Cu-Zn-Al LDH at 800 ppm SDS loading. The highest cooling rate of 174.8 °C/s was attained by Cu-Zn-Al LDH-SDS (600 ppm) nanofluid which is 30.7% higher than what had been achieved by water based cooling. However, the use of Tween 20 in LDH nanofluid has displayed detrimental impact on poor thermal conductivity, zeta potential, and heat transfer results for the LDH nanofluid.

Release of large quantity of dyes into water bodies by textile industries poses serious environmental implications. Removal of these dyes from contaminated stream is a major concern, due to persistent and recalcitrant nature of the pollutants. Technologies, like, physical removal, chemical treatment and biological degradation have been developed for removal of dyes from wastewater. However, most of these processes have their inherent limitations, like, sludge generation, slow removal rate and high adsorbent quantity. On the other hand, membrane filtration has gained popularity due to its high efficiency, small footprint and easy scale-up. However, conventional membrane-based technologies are associated with some inherent drawbacks, such as, high energy consumption, fouling, low water flux and removal percentages. Therefore, the current chapter focuses on the development of novel antifouling thin film nanocomposite membranes and their application in the removal of dyes from contaminated stream. These membranes have film coatings, which assist in enhanced uptake of dyes from wastewater and increased water flux in comparison to conventional nanofiltration and reverse osmosis membranes, with low energy consumption.

Due to the multifaceted life that humans have, mental health has come to be of significant concern. With work hours spanning for over 8 hours, COVID invading the world and people working from home - the balance between professional and personal life has lost balance and more than ever we see the necessity to put oneself first and to indulge in self-care. This leads to cognitive-load due to the mental strain from multiple frontiers at the same time. The increase in cases of people suffering from mental health and the "new normal" in the post-pandemic world, we see the ever more necessity of Cognitive Behavioural Therapy. Through this paper, we propose a design-led intervention in Cognitive Behavioural Therapy (CBT) through user study to understand the different aspects of CBT and how the user experience of the same can be improved.

This chapter explores novel, cheap and widely distributed feedstock i.e. lignocellulosic biomass extracted from biomass. Vanillin is one of the members of the class of benzaldehydes which carry methoxy (-CH3) and hydroxy (-OH) groups at two different positions. Vanillin possesses a high level of antimicrobial and antioxidant properties. Synthetic vanillin as an alternative to natural vanillin extract is from time to time used as a flavoring agent and food preservative in many bakery items, ice creams and soft drinks, and as a precursor in the synthesis of other flavoring agents. Vanillin produced through microbial transformation using natural and renewable feedstocks can be a better choice for the customer to enhance the market demand for vanillin. Production of complex molecules within living organisms or cells, or vanillin from simple carbon sources like glucose, which is cheaper and easily available on the market, is an attractive way to produce a high-value product like vanillin.

Cooling rate in Run Out Table (ROT) in steel industries tailors microstructure which lead to improved mechanical properties. The current work aims to increase cooling performance of steel using TiO...

The current experimental investigation deals with the thermo-physical attributes of Cu-Zn-Al LDH nanofluid its use in high temperature steel cooling. Here, authors used three metals (Copper, Aluminium, and Zinc) having high thermal conductivity to synthesize a brand new nanofluid for heat transfer application. Authors have achieved moderate increment (13.9%) in thermal conductivity value compared to water. A section of this work also aims to maximize the cooling rate which aids in improving mechanical properties of quenched steel plate. The maximum cooling rate of 158.4 °C/s was attained at 160 ppm of nanofluid concentration which is 18.5% higher than that attained by water. In addition to enhanced thermal conductivity, nanoparticle deposition on the cooling surface also contributes to the heat transfer enhancement by providing additional nucleation site. It is also to be considered that above an optimum nanofluid concentration both thermal conductivity and cooling rate values decline. Such trend is owed to several factors namely poor suspension stability, high agglomeration tendency and formation of nanoparticle layer on steel surface which prevents contact between coolant and surface.

In the current study, authors have synthesized Cu-Al Layered Double Hydroxide nanofluid at different molar ratios of Cu and Al by using co-precipitation technique and utilized this as a coolant in a pressure atomized spray to achieve high cooling rates in the temperature range of 900–600 °C for a 6 mm thick steel plate. The study initially focuses on the effect of Cu: Al molar ratio variation on thermal conductivity, stability as well as its heat transfer potential in steel quenching. Post thermal conductivity and stability analysis, spray cooling experiments were conducted in two parts. The first part involves optimization of Cu: Al molar ratio by varying the ratio (Cu: Al = 2:1, 4:1 and 6:1) at a fixed nanofluid concentration (120 ppm) to select the best Cu: Al molar ratio based on heat transfer results. The results show that the highest cooling rate and average heat flux were achieved at a Cu and Al molar ratio of 4:1 among all molar ratio combinations. Once, the optimized molar ratio is selected, the second part of the spray cooling experiments was performed to study the effect of nanofluid concentration variation (40–240 ppm, at an optimized molar ratio of Cu: Al = 4:1) on spray cooling results. With respect to concentration optimization, the maximum cooling rate of 168.6 °C/s was attained at a concentration of 160 ppm which is 26% higher than what was achieved by normal water spray. Results obtained from the spray cooling experiments were further verified by the thermal conductivity analysis where highest enhancement of 15.17% was also observed at 160 ppm nanofluid concentration.

The current work aims to investigate the efficiency of a jet array in cooling of a hot steel plate having surface temperature above 900 °C. The entire study has been divided into two phases. The first phase consists of experiments which are aimed to optimize the jet array impingement height and the water flow rate. It has been found that the cooling rate is enhanced by 60% in case of a jet array compared to a single jet at the same water flow rate and impingement height. In both the single jet and the jet array used in the present work, free falling flow occurs under gravity. In the second phase, the effect of seven different additives on heat transfer performance during cooling has been studied at the optimized values of water flow rate and impingement height. Sodium Dodecyl Sulphate (SDS), Cetyltrimethyl Ammonium Bromide (CTAB) and Tween 20 have been used as surfactant additives, Polyvinylpyrrolidone (PVP) as a polymer additive, Titanium dioxide (TiO2), Cu-Al layered double hydroxide (LDH) and PVP dispersed in TiO2 have been used as nanofluid additives. The results indicate that a maximum cooling rate of 143 °C/s has been achieved for PVP based coolant which is 28% more than that obtained for pure water. The results also prove that ultrafast cooling can be attained by using additive based jet array impingement.

Enhancement of thermal conductivity by the addition of nanofluid is found to improve the rate of cooling of a steel plate. In the present research work, alumina nanofluid at the previously optimized concentration of 10 ppm along with a non–ionic surfactant is employed for jet impingement cooling. The steel plate (100 × 100 × 6 mm) is cooled from an initial surface temperature of 900 °C. The concentration of non-ionic surfactant polyoxyethylene (20) sorbitan monolaurate (Tween 20) is optimized, and the surfactant is characterized based on its thermal properties. A maximum thermal conductivity enhancement of 21% and a minimum contact angle of 40.48° were exhibited by surfactant added nanofluid at 55 ppm. Inverse heat conduction method was employed to estimate the heat flux and temperature at the plate surface based on the internal thermocouple data. A maximum heat transfer rate of 139 °C/s with a critical heat flux (CHF) of 2.93 MW/m 2 was attained at a surfactant concentration of 55 ppm. SEM and EDAX analysis of the plate surface after jet impingement confirmed the presence of the nanoparticles.

The current study comprises of the synthesis and characterization of Zn-Al layered double hydroxide (LDH) nanofluid for use as a potential coolant in the steel industry. Coprecipitation method was used in the preparation of Zn-Al LDH nanoparticles by using the nitrate salts of Zn, Al and Na, in the ratio of 2:1:2. The nanofluids were characterized based on their particle size, stability, surface tension, thermal conductivity and viscosity. TEM analysis revealed that the nanoparticles were needle-shaped with an average particle size of 45.61 nm and aspect ratio of 7.3. Different concentrations of the nanofluid, from 40 ppm to 240 ppm, were used to analyze the effect of particle concentration on the enhancement in thermal conductivity and viscosity. Stability analysis of the nanofluid exhibited good results, even without any stabilizer. An optimum cooling rate of 125 °C/s was obtained for a nanofluid concentration of 160 ppm, which is 1.29 times when compared to water.

The current work contains a detailed experimental investigation on the alteration of heat transfer characteristics during jet impingement cooling of a hot steel plate using Copper-Aluminium layered double hydroxide (Cu-Al LDH) nanoparticle as an additive. The experiments have been performed on steel plate having initial surface temperature well above the Leidenfrost point. A new breed of nanoparticle named Cu-Al LDH has been prepared via co-precipitation method and the effect of its concentrations on surface tension, thermal conductivity and viscosity have been studied. The results show that the cooling rate increases with the increasing concentration of nanoparticle in coolant upto an optimum level beyond which it declines. A maximum cooling rate of 154 °C/s has been achieved at a nanoparticle concentration of 120 ppm which is 41% higher than that obtained with pure water. The study reveals that ultrafast cooling rate can be achieved by Cu-Al LDH nanofluid jet which is essential for the production of high strength steel for various industrial applications.

The current research is focused on the cooling of a hot moving steel plate by using air atomized spray cooling technique. A new type of coolant, Cu-Al LDH nanofluid, has been prepared and used for heat flux removal. Preparation method of nanofluid and its characteristics has been reported. The cooling effectiveness is reported in terms of cooling rate by varying the concentration of nanofluid in five levels. The results indicate that the cooling rate increases at very low concentration of LDH with respect to base fluid. However, beyond a certain concentration a decreasing trend of cooling rate has been observed.Abbreviations: CHF: Critical heat flux; HTC: Heat transfer coefficients; LDH:Layered double hydroxide; TEM: Transmission electron microscopy.

In the current work, TiO2 nanofluid has been synthesized via two-step co-precipitation method. TEM analysis has been carried out to measure the average particle size and to check the particle distributions which confirm the formation of a suspension having an average particle size of

Context: Maternal anxiety has an association with low birth weight. However, studies are scarce to determine any association between maternal anxiety and fetal growth. Aims: This study aims to determine the effect of maternal anxiety on fetal growth, measured by gestational age-dependent increase in fetal abdominal circumference (AC). The secondary objective is to determine the effect of maternal anxiety on other fetal parameters (biparietal diameter [BPD], head circumference [HC], femur length [FL]). Settings and Design: This cross-sectional study was conducted in a tertiary care hospital, Kolkata. Materials and Methods: Four hundred and ten pregnant mothers, between 14 and 40 weeks of gestation, were interviewed with socioeconomic and obstetric profile questionnaire and examined for anthropometric profile and presence and severity of pallor. Anxiety was assessed using Generalized Anxiety Disorder-7 (GAD) questionnaire. HC, AC, BPD, and FL were measured by ultrasound biometry. Analysis Used: A multivariable logistic regression analysis was done to determine the predictors of small-for-gestational-age (SGA). A robust mediation analysis was done to determine mediating effect of anxiety on gestational age-dependent increase in fetal AC. Results: Mild (odds ratio [OR]Adjusted = 6.23, [2.41, 16.15]) and moderate (ORAdjusted = 22.42, [5.00, 100.57]) anxiety was significantly associated with SGA fetus. Anxiety increased with the progression of gestation (βGAD: 0.011 [0.007–0.015]) and it had a negative effect on fetal growth (standardized indirect effect of gestational age-mediated by anxiety on AC: −0.037 [−0.059, −0.022]). Anxiety also attenuated gestational age-dependent increment of HC. Conclusion: Mother's anxiety has a gestational age-dependent temporally incremental negative effect on fetal growth and brain development.

Low thermal conductivity has been found to be a major constraint in developing energy efficient heat transfer fluids in several industrial applications. Nanofluids, prepared by the suspension of nanoparticles in water, have been found to enhance the thermal conductivity of the base fluid, and thereby the cooling rate of the steel surface. In this study, alumina nanofluid has been used to enhance the rate of cooling of a steel surface of dimension 100 mm × 100 mm × 6 mm, from an initial surface temperature of 900 °C. The sub-surface temperature data collected through thermocouple was used for inverse heat conduction calculation in order to estimate the temperature histories and heat flux at the surface. TEM analysis revealed that the nanoparticles were spherical in shape, having an average size of 14 nm. The concentration of the nanofluids was varied from 1 to 20 ppm in this study. A maximum cooling rate of 104 °C/s and critical heat flux (CHF) of 2.10 MW/m2 was obtained for a concentration of 10 ppm, which was 1.2 times and 1.5 times that attained in case of pure water, as depicted by the enhancement in thermal conductivity. Lower concentrations are used in order to strike a balance between surface roughness study and cooling applications. The surface roughness of the plate after the nanofluid jet impingement depicted an enhancement of 7.74%, thereby enhancing the number of nucleation sites and augmenting the value of CHF.

The cooling rate of steel strips on a Run-out Table (ROT) in a hot strip mill affects both the metallurgical microstructure and mechanical properties. The current study focuses on the enhancement of heat transfer rate of an AISI 304 steel plate in both transition and nucleate boiling regimes by jet impingement methodology. The heat transfer studies during jet impingement have been carried out in the case of a steel plate (100 mm × 100 mm × 6 mm) from an initial temperature of around 900 °C at the surface. Nanofluid is used along with the base fluid in order to improve the thermal properties which affect the rate of heat transfer. The nanofluid employed here is Cu–Al layered double hydroxide (LDH) at 120 ppm along with different additives at their optimized concentrations, namely sodium dodecyl sulfate (SDS), cetyltrimethylammonium bromide (CTAB), polyoxyethylene (20) sorbitan monolaurate (Tween 20) and polyvinylpyrrolidone (PVP). The nanofluid based additives have been characterized based on the thermo physical properties. The maximum rate of cooling was attained in the case of Cu–Al LDH/Tween 20 nanofluid, as supported by the enhancement of thermal conductivity and reduction in surface tension.

The current research focuses on the enhancement of heat transfer of a hot steel plate by introducing polymer additive, polyvinylpyrrolidone (PVP) in jet cooling. The characterization of PVP solution has been done in order to understand the reason for increment in heat transfer. The concentration of PVP has been varied at levels ranging from 50 to 150 ppm along with the variation of flow rate from 13.3 × 10−5 to 33.33 × 10−5 m3/s (8 to 20 lpm). The results indicate that the addition of PVP in water jet leads to an appreciable increase in cooling rate and surface heat flux compared to that of water which leads to lesser coolant consumption. A PVP concentration of 110 ppm in water is found to provide a maximum cooling rate of 231 °C/s and a maximum critical heat flux of 3.01 MW/m2 which are higher than that of water by 111.18% and 19% respectively.

Children residing in high malaria transmission regions are particularly susceptible to malaria. This early-life window is also a critical period for development and maturation of the nervous system, and inflammatory insults during this period may evoke a persistent increase in vulnerability for psychopathology. We employed a two-hit model of juvenile mild malaria and a two-week chronic unpredictable mild stress (CUMS) regime, commencing 60 days post-parasite clearance, to assess whether a history of juvenile infection predisposed the mice towards mood-related behavioral alterations and neurocognitive deficits. We showed that a dult mice with a h istory of j uvenile mal aria (A-H/JMAL) exhibited heightened CUMS-associated anxiety-like behavior, with no observable change in cognitive behavior. In contrast, mice with a history of adult malaria did not exhibit such enhanced stress vulnerability. At baseline, A-H/JMAL mice showed increased activated microglia within the hippocampal dentate gyrus subfield. This was accompanied by a decrease in proliferating neuronal progenitors, with total number of immature hippocampal neurons unaltered. This neuroinflammatory and neurogenic decline was further exacerbated by CUMS. At day-14 post-CUMS, hippocampi of A-H/JMAL mice showed significantly higher microglial activation, and a concomitant decrease in progenitor proliferation and number of immature neurons. Taken together, these results suggest that a history of juvenile mild malaria leaves a neuroinflammatory mark within the hippocampal niche, and this may contribute to a heightened stress response in adulthood. Our findings lend credence to the idea that the burden of malaria in early-life results in sustained CNS changes that could contribute to increased vulnerability to adult-onset neuronal insults.

Introduction: Globally, every year, more than 6 million people die because of tobacco use. 20% of all global deaths attributed to tobacco occur in India. The behavioral difference in the rural and urban communities is an important aspect of tobacco problem in the country. In this context, we conducted a community-based cross-sectional study to determine the effect of area (rural-urban) in predicting tobacco consumption pattern. Materials and Methods: A community-based observational, cross-sectional study was conducted in a rural and an urban community of West Bengal from May 2014 to April 2015. A predesigned pretested schedule adapted from the Global Adult Tobacco Survey India Questionnaire was used for data collection. Males above 15 years of age, residing in the study areas, were interviewed during house-to-house visit. Results: Data obtained from the interview of 704 males (352 each from urban and rural area) above 15 years revealed that the prevalence of current tobacco use in any form is significantly higher in rural area (75.6%) than in urban area (67.6%). This was related to the fact that awareness and perception of the people in rural areas are significantly less than their urban counterparts. In bivariate analysis satisfactory consumption pattern was significantly more in urban area but when adjusted with all potentially explanatory variables, the odds of satisfactory consumption pattern in urban area was attenuated significantly. Conclusion: An appropriate intervention strategy, based on local area-wise behaviors of people to curb out the menace of tobacco use, is the need of the hour.

The study of ultrafast cooling of a hot moving surface is very important, as it is applicable in many industries, such as cooling of a hot steel strip on the run out table in steel industry. In general, the run out table is fitted with laminar water jets where the achieved cooling rate is very less because of the Leidenfrost phenomenon. The current research is focused on the comparative study of the cooling processes; by using water jet and air atomized spray cooling techniques on the hot stationary and moving surface. The coolant used in both the cases is surfactant added water with varying concentration of surfactants. In case of stationary bed, the maximum cooling rates achieved for both jet and air atomized spray cooling are at a surfactant concentration of 225 ppm, the values being 167 and 224 °C/s, respectively. On the contrary, for moving surface, highest cooling rates of 163 and 127 °C/s are obtained at a low surfactant concentration of 75 ppm for jet and spray cooling respectively. It is interesting to observe that addition of surfactant has a negative effect on cooling rate for a hot moving surface.

In the current study, a hot moving steel plate of 6 mm thickness with an initial temperature of 900°C has been considered for jet impingement cooling. The experiment has been designed with the help of Design of Expert software to optimize the process parameters based on the highest cooling rate. The various subsurface transient temperature histories have been measured during the cooling process. The surface heat flux and surface temperature were calculated with the help of a commercial inverse heat transfer solver called INTEMP. The experimental result has been presented in terms of cooling rate and critical heat flux.

Synthesis of pristine Cu–Al layered double hydroxide (LDH) nanofluid via one step method and study of its thermal properties are the core essence of the current work. Nitrate salts of Cu, Al and Na were mixed in a particular molar ratio at constant pH to produce desired Cu–Al LDH. Different dispersion techniques were utilized to uniformly disperse Cu-Al LDH in water to obtain Cu–Al LDH nanofluids. Broadly used characterization techniques were implemented to identify and characterize pristine Cu–Al LDH nanoparticle. These techniques were used to determine crystallite size, composition, morphology and characteristics vibration of interlayer anion present in the nanoparticle. The nanofluids were characterized for particle size, cluster size, surface tension and thermal conductivity. Particle size analysis was carried out to confirm the formation of nanofluid. Dynamic light scattering (DLS) method had been employed to measure the clustering tendency of nanofluid. Effect of nanofluid loading on thermal conductivity was studied in depth. Influence of particle size, shape and composition on thermal conductivity of nanofluid had also been selected as an essential topic of investigation. Zeta potential and visual phase separation study were carried out to measure the stability of concerned nanofluid.