Showing papers by "SRM University published in 2019"

Effectiveness of 2% Articaine as an anesthetic agent in children: randomized controlled trial.

Abstract: The aim of this study was to compare the effectiveness of 2% articaine and 2% lignocaine in achieving adequate anesthesia in children between the age group of 6–13 years using inferior alveolar nerve block. A triple blinded randomized controlled trial was conducted in 180 participants (90 patients- 2% articaine, 90 patients-2% lignocaine). Effectiveness of the anesthetic agent was determined at 3 points determined by subjective evaluation of pain using pain scales (FPS-R). Paired sample t-test and chi square test were performed for statistical significance. Anesthetic success for 2% articaine were 64.4%, 42.2% and 81.8% respectively. The anesthetic success of 2% lignocaine was 66.7%, 48.9% and 85.7% at point one, point two and point three respectively (p > 0.05). This study concludes that 2% articaine in 1:2,00,000 did not demonstrate superior clinical effectiveness in comparison to 2% lignocaine. Lignocaine has always been considered the gold standard. With its unique chemical structure and increased potency, Articaine has been gaining popularity. Its efficacy in 2% concentration had not been compared to 2% lignocaine. 2% articaine did not show clinical superiority but its comparable effectiveness with lignocaine can encourage further research in using articaine in reduced concentrations to improve effectiveness.

A review on ZnO nanostructured materials: energy, environmental and biological applications.

Abstract: Zinc oxide (ZnO) is an adaptable material that has distinctive properties, such as high-sensitivity, large specific area, non-toxicity, good compatibility and a high isoelectric point, which favours it to be considered with a few exceptions. It is the most desirable group of nanostructure as far as both structure and properties. The unique and tuneable properties of nanostructured ZnO shows excellent stability in chemically as well as thermally stable n-type semiconducting material with wide applications such as in luminescent material, supercapacitors, battery, solar cells, photocatalysis, biosensors, biomedical and biological applications in the form of bulk crystal, thin film and pellets. The nanosized materials exhibit higher dissolution rates as well as higher solubility when compared to the bulk materials. This review significantly focused on the current improvement in ZnO-based nanomaterials/composites/doped materials for the application in the field of energy storage and conversion devices and biological applications. Special deliberation has been paid on supercapacitors, Li-ion batteries, dye-sensitized solar cells, photocatalysis, biosensors, biomedical and biological applications. Finally, the benefits of ZnO-based materials for the utilizations in the field of energy and biological sciences are moreover consistently analysed.

Brain Tumor Segmentation Using Convolutional Neural Networks in MRI Images.

Abstract: In medical image processing, Brain tumor segmentation plays an important role. Early detection of these tumors is highly required to give Treatment of patients. The patient’s life chances are improved by the early detection of it. The process of diagnosing the brain tumoursby the physicians is normally carried out using a manual way of segmentation. It is time consuming and a difficult one. To solve these problems, Enhanced Convolutional Neural Networks (ECNN) is proposed with loss function optimization by BAT algorithm for automatic segmentation method. The primary aim is to present optimization based MRIs image segmentation. Small kernels allow the design in a deep architecture. It has a positive consequence with respect to overfitting provided the lesser weights are assigned to the network. Skull stripping and image enhancement algorithms are used for pre-processing. The experimental result shows the better performance while comparing with the existing methods. The compared parameters are precision, recall and accuracy. In future, different selecting schemes can be adopted to improve the accuracy.

Crop Residue Burning in India: Policy Challenges and Potential Solutions.

Abstract: India, the second largest agro-based economy with year-round crop cultivation, generates a large amount of agricultural waste, including crop residues. In the absence of adequate sustainable management practices, approximately 92 seems a very small number of metric tons of crop waste is burned every year in India, causing excessive particulate matter emissions and air pollution. Crop residue burning has become a major environmental problem causing health issues as well as contributing to global warming. Composting, biochar production and mechanization are a few effective sustainable techniques that can help to curtail the issue while retaining the nutrients present in the crop residue in the soil. The government of India has attempted to curtail this problem, through numerous measures and campaigns designed to promote sustainable management methods such as converting crop residue into energy. However, the alarming rise of air pollution levels caused by crop residue burning in the city of Delhi and other northern areas in India observed in recent years, especially in and after the year of 2015, suggest that the issues is not yet under control. The solution to crop residue burning lies in the effective implementation of sustainable management practices with Government interventions and policies. This manuscript addresses the underlying technical as well as policy issues that has prevented India from achieving a long-lasting solution and also potential solutions that have been overlooked. However, effective implementation of these techniques also requires us to look at other socioeconomic aspects that had not been considered. This manuscript also discusses some of the policy considerations and functionality based on the analyses and current practices. The agricultural waste sector can benefit immensely from some of the examples from other waste sectors such as the municipal solid waste (MSW) and wastewater management where collection, segregation, recycling and disposal are institutionalized to secure an operational system. Active stakeholder involvement including education and empowerment of farmers along with technical solutions and product manufacturing can also assist tremendously. Even though the issue of crop residue burning touches many sectors, such as environment, agriculture, economy, social aspects, education, and energy, the past governmental efforts mainly revolved around agriculture and energy. This sectorial thinking is another barrier that needs to be broken. The government of India as well as governments of other developing countries can benefit from the emerging concept of nexus thinking in managing environmental resources. Nexus thinking promotes a higher-level integration and higher level of stakeholder involvement that goes beyond the disciplinary boundaries, providing a supporting platform to solve issues such as crop residue burning.

A critical review of organic manure biorefinery models toward sustainable circular bioeconomy: Technological challenges, advancements, innovations, and future perspectives

Abstract: Total livestock emissions account for up to 14.5% of man-made greenhouse gas emissions. Counteractive measures, such as circular economy concepts and negative emission technologies are necessary to limit global warming below 1.5 °C. Possible treatment options for organic manure include anaerobic digestion, combustion, gasification, hydrothermal liquefaction and composting. The choice of treatment varies depending on the economics, the requirement of a specific product, and sociocultural factors. Commercialization of these treatments needs a blend of appropriate technology, feasible economics, policy support and agreeable socio-cultural conditions. Key findings of this study include the following: 1. Increasing scientific awareness about manure management and treatment; 2. Building a sustainable cooperative model to commercialize technologies; 3. Creating a market for manure recycling products; 4. The role of policy in supporting technologies and consumers; and 5. The codigestion of substrates for better efficacy. Current trends show minimal actions in place as opposed to the high-rate of acceleration that is necessary.

Compact Switched Capacitor Multilevel Inverter (CSCMLI) With Self-Voltage Balancing and Boosting Ability

Abstract: This letter presents a compact switched capacitor multilevel inverter (CSCMLI) topology with reduced switch count and with self-voltage balancing and boosting ability. The operational mode of the proposed CSCMLI is discussed. A comparative analysis in terms of number of switches and blocking voltages is presented against recent switched capacitor multilevel inverter topologies. Further to enhance the quality of the output voltage, a new level shifted multicarrier pulsewidth modulation (PWM) technique is recommended. This modulation technique produces low THD and high rms voltage. The proposed modulation technique is implemented in the nine-level CSCMLI with single dc source and two capacitors. The simulated and experimental results are verified for a switching frequency of 50 Hz and 2.5 kHz using the proposed PWM control.

Consumer's response to CSR activities: Mediating role of brand image and brand attitude

Abstract: Corporate social responsibility (CSR) is a well‐touted term in management disciplines that connects the business goals and societal values. CSR is used as a strategic approach that gives competitive differentiation through coagulation of both business and overarching societal goals. Organizations believe that goodwill created by CSR activities bestows the strategic competitive advantage and sustainable development. The objective of the study is to measure the impact of CSR activities on purchase intention either directly or indirectly; for this purpose, the study has administered a structured questionnaire and collected responses from Indian citizens purchasing products from FMCG companies topping the CSR spending list and used structural equation modeling to validate the results. The findings suggest that customers process CSR details unconsciously and may not remember the explicit detail, but they are more likely to include the brand in the consideration set evokedby positive attitudes trailing behind.

FeCo Alloy Nanoparticles Coated by an Ultrathin N-Doped Carbon Layer and Encapsulated in Carbon Nanotubes as a Highly Efficient Bifunctional Air Electrode for Rechargeable Zn-Air Batteries

Abstract: Development of inexpensive, efficient, and stable nonprecious-metal-based bifunctional catalysts for oxygen reduction (ORR) and evolution (OER) reactions remains an enormous challenge. This work re...

LSTM Model for Prediction of Heart Failure in Big Data

Abstract: The combination of big data and deep learning is a world-shattering technology that can make a great impact on any industry if used in a proper way. With the availability of large volume of health care datasets and progressions in deep learning techniques, systems are now well equipped in diagnosing many health problems. Utilizing the intensity of substantial historical information in electronic health record (EHR), we built up, a conventional predictive temporal model utilizing recurrent neural systems (RNN) like LSTM and connected to longitudinal time stepped EHR. Experience records were contribution to RNN to anticipate the analysis and prescription classes for a resulting visit during heart disappointment (e.g. diagnosis codes, drug codes or method codes). In this paper, we also investigated whether use of deep learning to model temporal relations among events in electronic health records (EHRs) would enhance the model performance in predicting initial diagnosis of heart failure (HF) compared to some of the traditional methods that disregard temporality. By examining these time stamped EHRs, we could recognize the associations between various diagnosis occasions and finally predicate when a patient is being analyzed for a disease. In any case, it is hard to access the current EHR data straightforwardly, since almost all data are sparse and not standardized. Along these lines, we proposed a robust model for prediction of heart failure. The fundamental commitment of this paper is to predict the failure of heart by means of a neural network model based on patient's electronic medicinal information. In order to, demonstrate the diagnosis events and prediction of heart failure, we used the medical concept vectors and the essential standards of a long short-term memory (LSTM) deep network model. The proposed LSTM model uses SiLU and tanh as activation function in the hidden layers and Softmax in output layer in the network. Bridgeout is used as a regularization technique for weight optimization throughout the network. Assessments subject to the real-time data exhibit the favorable effectiveness and feasibility of recommended model in the risk of heart failure prediction. The results showed improved accuracy in heart failure detection and the model performance is compared using the existing deep learning models. Enhanced prior detection could expose novel chances for deferring or anticipating movement to analysis of heart failure and diminish cost.

Effect of B4C and MOS2 reinforcement on micro structure and wear properties of aluminum hybrid composite for automotive applications

Abstract: The utilization of particulate reinforced aluminium hybrid metal matrix composites is being increased in automotive applications due to its distinct properties. In the present study, an endeavour has been made to synthesize Al7075 aluminium alloy with reinforcement of B4C and MoS2 as lubricant under various weight percentages of 4%, 8% and 12% using stir casting process. The compressive strength, tensile strength, hardness, micro structural analysis and tribological behavior of the synthesized hybrid composites have been analyzed and investigated. From the experimental investigation, it has been observed that the reinforcement particles are uniformly distributed in the matrix alloy as fine dendrites in alumnium solid solutions. The tensile strength, compressive strength, and hardness of the reinforced composites could be increased by adding the reinforcement compared to monolithic alloy. The significant improvement of wear resistance and coefficient of friction of aluminium hybrid composites has been achieved owing to inclusion of solid lubricant (MoS2) along with hard ceramic reinforcement particles (B4C) in the matrix alloy.

Nanocomposites of Zr(IV)-Based Metal–Organic Frameworks and Reduced Graphene Oxide for Electrochemically Sensing Ciprofloxacin in Water

Abstract: Rapid determination of trace antibiotics is critical for environmental monitoring and the ecosystem. In this study, a sensitive and selective electrochemical sensor for ciprofloxacin (Cip) detectio...

Effects of Silicon Carbide and Tungsten Carbide in Aluminium Metal Matrix Composites

Abstract: In the present study, an attempt has been made to synthesis Al6061/SiC/WC hybrid aluminium composites using stir casting method under various mass percentage of reinforcement. The mechanical properties such as compressive strength, tensile strength, hardness and wear resistance have been characterized and investigated. From the micro structural analysis of hybrid composites, it has been observed that reinforcement particles have been uniformly distributed without clustering of particles in matrix alloy. The precipitate of Mg2Si and un-dissolved Al6 (Fe, Mn) in aluminium solid solution has been observed as interfacial reaction. The hardness of hybrid composites has been increased due to incorporation of stiffer and stronger reinforcement in the matrix material. The presence of SiC and WC reinforcement in the matrix alloy can significantly enhance the compressive, tensile strength and wear resistance of aluminum hybrid composite.

A Self-Balancing Five-Level Boosting Inverter With Reduced Components

Abstract: Two-Stage boosting multilevel inverters (MLIs), which are highly suitable for photovoltaic power plants, are known to suffer because of the high voltage stress on the switches of second stage. One of the ways to confront this issue is through eliminating the front-end booster. However, this leads to increased structural and control complexity of the resulting integrated boosting MLI. This letter presents a single-stage boosting MLI requiring lesser number of switches, diodes, and capacitors for renewable power generation applications. It requires nine switches and only one capacitor for five-level voltage generation. The topology has inherent self-balancing capability, thereby does not need additional balancing circuitry. The proposed topology has a uniform peak inverse voltage stress on the switches of value equal to the input dc voltage. A less complicated logic-form-equations-based gating pulse generation scheme is designed for enabling the proposed MLI to maintain its capacitor voltage. Further, a comparative study with state-of-the-art topologies is carried out to demonstrate the superior performance of the proposed topology. Finally, the feasibility of the proposed topology is validated through experimental tests and the corresponding results are elucidated.

Switched-Capacitor-Based Quadruple-Boost Nine-Level Inverter

Abstract: This letter describes a novel nine-level inverter based on switched capacitors (SCs) with quadruple-boost ability requiring reduced components. The structure of the proposed topology relies on the series/parallel connection of SCs. It consists of 12 switches and two SCs. As opposed to similar SC-based inverters, the proposed topology does not employ a back-end H-bridge and the voltage stress of all the switches does not exceed twice the input dc voltage. A simple logic-gate-based pulsewidth-modulation scheme is developed for gating the switches of the proposed topology. A comprehensive comparison against the state-of-the-art topologies in terms of the required number of components is performed to attest the outperforming merits of the proposed topology. Finally, various experimental results are presented to validate the feasibility and operability of the proposed topology.

Environmentally Sustainable Synthesis of a CoFe2O4-TiO2/rGO Ternary Photocatalyst: A Highly Efficient and Stable Photocatalyst for High Production of Hydrogen (Solar Fuel).

Abstract: Herein, a magnetically separable reduced graphene oxide (rGO)-supported CoFe2O4–TiO2 photocatalyst was developed by a simple ultrasound-assisted wet impregnation method for efficient photocatalytic H2 production. Integration of CoFe2O4 with TiO2 induced the formation of Ti3+ sites that remarkably reduced the optical band gap of TiO2 to 2.80 eV from 3.20 eV. Moreover, the addition of rGO improved the charge carrier separation by forming Ti–C bonds. Importantly, the CoFe2O4–TiO2/rGO photocatalyst demonstrated significantly enhanced photocatalytic H2 production compared to that from its individual counterparts such as TiO2 and CoFe2O4–TiO2, respectably. A maximum H2 production rate of 76 559 μmol g–1 h–1 was achieved with a 20 wt % CoFe2O4- and 1 wt % rGO-loaded TiO2 photocatalyst, which was approximately 14-fold enhancement when compared with the bare TiO2. An apparent quantum yield of 12.97% at 400 nm was observed for the CoFe2O4–TiO2/rGO photocatalyst under optimized reaction conditions. This remarkable e...

Performance, emission and combustion study on neat biodiesel and water blends fuelled research diesel engine

Abstract: This work investigates the experimental study to examine the operation characteristics of an orange peel oil biodiesel (BD100) along with water as an oxygenated additive in various volume fractions. Hard water is mixed into 100% of BD100 at 4 and 8% volume. Span 80 was employed as a nonionic surfactant, which emulsifies water into biodiesel. The experimental investigation on diesel engine reveals that the addition of water to BD100 resulted in enhancement of brake thermal efficiency (BTE) with a reduction in brake specific fuel consumption (BSFC). The tested emission parameters such as CO, HC, NOx and smoke were decreased by 11.4, 9.89, 3.36 and 5.14% for BD94W4S2 (94% volume of biodiesel) + (4% volume of water) + (2% volume of surfactant) and 12.22, 10.11, 4.85 and 6.18% for BD90W8S2 (90% volume of biodiesel) + (8% volume) + (2% volume) respectively when compared to BD100. Further, the cylinder pressure and heat release rate and were enhanced by adding water to base fuel (BD100). Overall, improvement in ignition characteristics of the engine was finer by adding, 4 and 8% volume of water to BD100 on account of its chemical properties.

MnO2 Nanoflowers Deposited on Graphene Paper as Electrode Materials for Supercapacitors

Abstract: We recently reported a simple and cost-effective green method to produce free-standing, flexible, and highly conductive electrochemically exfoliated graphene paper (GrP) for a supercapacitor applic...

Hybrid improved firefly-pattern search optimized fuzzy aided PID controller for automatic generation control of power systems with multi-type generations

Abstract: This article deals with frequency control of five area power systems employing a technique which based on the hybridization of improved Firefly optimization Algorithm and Pattern Search technique (hIFA-PS) to tune the parameters of fuzzy aided PID controller. The performance of original firefly algorithm (FA) is improved by adding memory, newborn fireflies and using a new updating formula of fireflies which eliminate the wandering movement of the fireflies during the iteration process. The proposed hIFA-PS technique gets the benefits of FA's global explore capability and local search ability of PS. At first, an interconnected five area thermal power system with appropriate Generation Rate Constraints (GRC) and Dead Bands (DB) is considered and the integral constants are optimized by FA. To demonstrate the superiority of the proposed hIFA-PS algorithm results are compared with other soft computing approaches. To improve the dynamic performance, different controller structures are considered and a comparative study of hIFA-PS optimized I/PI/PID/Fuzzy aided PID is presented. The proposed design method is also applied to a five area ten unit system consisting of diverse generation sources such as thermal, hydro, wind, diesel, gas turbine. Performance analysis of the designed controller has been carried out for different system parameters and loading conditions. It has been observed that the designed hIFA-PS based fuzzy logic PID controller performs satisfactorily with varied conditions. The superiority of proposed AGC approach over some recently published AGC approaches is also demonstrated.