Search

This study aimed to determine whether autochthonous high-intensity D. repens microfilaremia leads to haematological changes in companion dogs. Dogs with hypermicrofilaremia presented to the District Veterinary Centre, Kannur were selected for the study. A total of 100 dogs were positive for hypermicrofilariaemia with D. repens based on peripheral blood smear examination and Knott's test. Of these, 3 dogs were concurrently positive for sheathed microfilaria (MF) of Brugia spp. Interestingly, an adult live worm of D. repens approximately eight cm in length was detected on a subcutaneous mass on the hind limb of a hypermicrofilaremic dog in the study. We compared the hematological parameters of 100 autochthonous hypermicrofilaremic dogs and 15 uninfected dogs. The hematological findings in the study are mild to moderate anemia, moderate to severe thrombocytopenia, leucocytosis with granulocytosis, lymphocytosis and monocytosis as compared to the uninfected group of dogs. The pathogenicity of naturally occurring hypermicrofilaremia is poorly studied, and knowledge of its epidemiology, host-parasite relationship and impact on various organs is warranted for better prevention and control, especially in hot-spot areas. [ABSTRACT FROM AUTHOR]

The grading of mangoes is an essential aspect of providing quality fruits to consumers and control the needs of the fruit processing industry. Manual visual inspection leads to inconsistencies, and it is human labour intensive. This paper is focused on improving the accuracy of the automatic mango grading system by doing multi-level grading using Deep Learning, Computer Vision and Image processing techniques. The proposed system is based on the mango maturity ripening stage, shape, texture features, colour and defects to identify the mango variety and classify based on quality. The maturity ripening stage of the mango is extracted using the Convolutional Neural Network (CNN). Computer Vision and Image processing techniques are used to extract shape, texture features and defects. The extracted features are input to the Random Forest classifier to identify the mango variety and grade the mango quality into three classes Notfit, Average and Good. The system has been validated on the dataset created for this study across three different varieties, Banganapalli, Neelam and Rumani, the most popular in Tamil Nadu. The proposed system using features extracted from CNN enhanced the system's efficiency with an accuracy of 93.23% for variety recognition and 95.11% for quality grading. Hence the proposed system is fully automated, commercially viable and has improved accuracy in variety recognition and quality grading of mangoes across different varieties. [ABSTRACT FROM AUTHOR]

Purpose: This paper presents a contemporary direction on the reduction of vibration and acoustic noise in Switched Reluctance Motor (SRM) using Soft Magnetic Composite (SMC) blank. Methods: Soft magnetic composite materials are composed of iron powder and resin. The particles are compacted, together with a lubricant and possibly a binder, at high pressure into a bulk material. Soft magnetic composite materials are characterized by three-dimensional isotropic ferromagnetic behaviour and very low eddy current loss. The competence of Soft Magnetic Composite (SMC) material in Switched Reluctance Motor (SRM) on vibration related issues has been investigated through Finite Element Analysis and experimentation. Results: To analyze the magnetic, vibration, and acoustic noise characteristics two motor configurations, viz., M19-SRM (M19- Switched Reluctance Motor) and SMC–SRM (Soft Magnetic Composite - Switched Reluctance Motor) are considered. Conclusion: The efficacy of SMC–SRM (Soft Magnetic Composite - Switched Reluctance Motor) prototype in vibration mitigation has been validated. [ABSTRACT FROM AUTHOR]

The electroencephalogram (EEG) signal is very important in the diagnosis of epilepsy. Long-term EEG recordings of an epileptic patient contain a huge amount of EEG data. Therefore, detecting epileptic activity is a very demanding process that requires a detailed analysis of the entire length of the EEG data, usually performed by an expert. This paper evaluates machine learning classifiers' performance with their paradigms for classification of raw EEG signals into two classes, i.e., seizure and non-seizure. Here, the 13 descriptive features are taken into consideration and fed to the classifiers. Here, CHB-MIT Scalp EEG Database is used, which comprises paediatric subjects of 24 records. The performance of classifiers is evaluated categorically concerning gender and in total. The results confirmed that the fine KNN is the best classifier in males, females, and all subjects. [ABSTRACT FROM AUTHOR]

A slow evaporation method has grown the sodium 4-nitrophenolate dehydrate (S4NPD) crystals. FTIR and Raman spectra have analyzed the chemical structure of synthesized S4NPD. The single crystal XRD and Powder XRD studies confirmed S4NPD crystal contains the orthorhombic crystal system. The UV–Vis absorption and transmittance analysis reveal that the grown crystal possesses an optical transmittance in the visible and NIR regions. The cut-off wavelength of the S4NPD is 435 nm, and these features are more appropriate for emerging optical fields. The photoluminescence spectrum shows the peak absorbed at 517 nm, indicating green light emission. The nonlinear optical properties with the enhancing role of the growth crystal’s second and third-harmonic generation efficiencies. The laser threshold damage (LDT) value shows the suitability of crystal coupled with high-power laser output applications. A chemical etching study was carried out to examine the growth pattern of the S4NPD crystal. [ABSTRACT FROM AUTHOR]

This paper presents a design of 4 bit differential current steering(DCS) DAC as a part of 16bit PAM transmitter (4-b/symbol) for achieving 4Gb/s data rate in 45-nm CMOS technology. The 4-bit folding flash ADC circuit is used in the receiver to complete the transceiver chain for the wireless communication. 4-b ADC and the binary to thermometer converter block will convert the single-ended continuous time input to 15-b thermometer code at 1 GHz clock. The 4-bit thermometer DCS DAC which takes the 15-b digital input and provides output current to drive the channel. The channel is terminated at the receiver with a terminating resistor (RT) and a terminating voltage (VT). All the IC design challenges are suitable with the CMOS technology for the communication devices and internet of things. Hence DAC is designed in 45-nm technology for the proposed work and overall achieved parameter results are compared with different topologies. For the 1 V applied voltage the whole system has the power consumption as 11.244mW and the ENOB of 3.953@29Mhz. [ABSTRACT FROM AUTHOR]

Breast cancer rates are rising. It also remains the second principal reason for cancer-related mortality in females, and the mortality rate is also drastically rising. In recent years, MicroRNAs (miRNAs) have emerged to have a large potential as biomarkers because of their effective roles in human disease diagnosis (including breast cancer). miRNAs are small (short), regulatory, and evolutionarily conserved non-coding RNAs (ncRNAs) molecules (with a length of about 22 nucleotides) that are present in all eukaryotic cells. There are many studies available in the literature that focus on recent circulating miRNAs research, their relationships to human diseases, their role as a potential biomarker, etc. Therefore, in this study we used three key techniques for classification of breast cancer using miRNAs features: Linear Discriminant Analysis (LDA), Random Subspace Ensemble (RSE) and Bayesian Hyperparameter optimization (BHO). Linear Discriminant Analysis (LDA) is a simple but most practical and computationally attractive classification approach. Random Subspace Ensemble (RSE) is capable of producing a robust ensemble for classification. Some previous research showed applications of Bayesian optimization in many engineering optimization problems. Notably, it is a recently applied for hyperparameter tuning in various ensemble classifiers. Therefore, the potential application of the RSE of LDA classifiers (LDA as a base classifier) with BHO method to boost the predicting accuracy of breast cancer diagnosis using miRNAs profiling dataset, has been studied in this study. A publicly available dataset of serum miRNA profiles obtained from the GEO dataset (accession code GSE106817) has been applied for validation. A variety of output measurements were employed to determine the performances and efficiencies of the proposed model and other classifiers. The proposed approach exhibited successful overall performance. The results were directly compared with the individual LDA classifier and other established state-of-the-art classifiers. The outcomes point out that the approach is superior in terms of different efficiency indicators to the LDA and all established state-of-the-art models used in the study. Study simulations, outcomes, and mathematical investigations have illustrated that the technique presented is a practical and advantageous model for the classification of breast cancer from miRNA profiling. This model may usefully be employed in other cancer classifications from miRNA profiling. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) in association with cloud technologies are the raising stars in information technology industry, which provides a lot of innovative gadgets to several industries to automate their needs as well as monitoring the events properly without any human interventions. The most common and emerging needs now-a-days is the development of new gadgets to support healthcare industry to rectify the medical flaws and save the human life. In one side the booming technologies such as Internet of Things and Cloud platforms are available and the other hand a drastic need to introduce an intelligent gadget for medical oriented needs to save one's life in critical situations. This paper aims to create a bridge between the two and introduce a new device to combine healthcare with recent technological developments. The proposed approach introduces a new algorithm called iCloud Assisted Intensive Deep Learning (iCAIDL), which provides support to healthcare medium as well as patients by means of applying the intelligent cloud system along with machine learning strategies and this proposed algorithm is derived from the base of deep learning norms. An iCloud Assisted Intensive Deep Learning algorithm initially begins with the flow of collecting the existing health records from the data repository and train the system with deep learning principles. Once the data training phase ends the proposed algorithm begins to get the live data from patient and this data is assumed as a testing data, which will be processed by using intensive deep learning principles and store the resulting summary into the Cloud repository by means of enabling Internet of Things feature in association with the proposed algorithm called iCAIDL. This is transparent in both the state of users like doctors as well as the patients to monitor the health records in intelligent manner. A Smart Medical Gadget is designed to collect the health record from patients and maintain it into the medical repository for testing phase, in which it collects the patient heart rate, pressure level, blood flow in intensive manner. The logic of IoT is connected with the machine learning process such as: the data accumulated from the smart Medical Gadget needs to be send to the Server end for processing, here the processing is mentioned as the machine learning based processing, in which the received data is considered to be the testing data and the results are emulated accordingly. Once the results are emulated that also will be coming for training part for the upcoming testing data. So, that the data coming from the Medical Gadget is considered to be the testing data and once the processing is done it will be considered to be the training data for further medical summaries. The performance evaluations of the proposed approach is estimated based on the following metrics such as data transfer ratio from Smart medical Gadget to the server end, storage accuracy and the communication efficiency. Empirical results are attained using simulation, in which it produces a drastical improvement of healthcare parameters by merge the proposed algorithm called iCloud Assisted Intensive Deep Learning. [ABSTRACT FROM AUTHOR]

To look for early breast cancer signs and indications, mammography screening is one of the best approaches available. Screening mammograms are the most commonly recognized procedure and remain the gold standard for early breast cancer screening. But many times, a relatively low positive predictive rate of breast biopsy demonstrated by this diagnostic technique leads to unneeded biopsies for abnormal findings that are ultimately proven benign in many cases. Random Forest (RF)—which evolves from Decision Trees (DTs)—is one of the most practical and powerful ensemble learning concepts (or meta estimators). Breast Imaging Reporting and Data System (BI-RADS) is developed as a standardized system or tool for reporting breast mammograms. This technique is used to locate unusual findings into groups. In this study, the RF classifier with Chi-Square (χ2) and Mutual Information (MI) procedures of relevant Feature Selection (FS) has been applied successfully, in an attempt to predict cancer biopsy outcomes from BI-RAD findings and the patient's age. For validation purposes, the UCI Mammographic Mass dataset has been used and assessed using accuracy, AUC, and several other performance criteria through a 10-fold CV approach. The prediction findings from the proposed method were very encouraging (84.70% accuracy and AUC 0.9023). Similarly, the proposed system gave better results in terms of MCC and F1-score. The results were directly compared with the RF classifiers and other state-of-the-art classification methods. This comparative analysis indicates that the proposed model is superior in terms of various efficiency indicators to the RF classifier and all standard models used in the study. These findings also confirm that the χ2 and MI FS approaches correctly as well as efficiently obtained the relevant and discriminating feature subset. The result also points out that the suggested approach is a comparable approach to different classification models present in the relevant literature. It is an advantageous, practical, and sound method to predict cancer biopsy outcomes. [ABSTRACT FROM AUTHOR]

The article titled "Retraction Note: An adaptive neuro-fuzzy logic based jamming detection system in WSN" has been retracted by the publisher due to concerns about compromised editorial handling and peer review processes. The authors, K. P. Vijayakumar, P. Ganeskumar, P. Vijayakumar, and T. Karthick, have not responded to correspondence regarding the retraction. The retraction note highlights issues with inappropriate references and being out of scope for the journal or guest-edited issue. [Extracted from the article]

In Asian countries, there is high occurrence of tuberculosis (TB) among captive wild elephants due to close association with humans and other domestic livestock. The present study envisages on utilization of serological, molecular, and proteomic diagnostic assays for tuberculosis diagnosis. The usage of urine as a biological sample for the identification of biomarkers for tuberculosis forms the prime focus of the study. Seroprevalence of tuberculosis (TB) in elephants in Kerala were found to be 37.2% (n = 86) using Chembio DPP VetTB assay and nine (10.46%) were positive for acid fast bacilli using trunk wash sediment smear. On comparison with DPP VetTB assay, acid fast staining shows low sensitivity of 28.13%, specificity 100%, kappa statistics value of 0.329. The presence of Mycobacterium tuberculosis was confirmed in trunk wash using PCR targeting gene IS6110, at 245 bp amplicon size and 25 seropositive elephants (78.2%) were confirmed positive. Custom sequencing and phylogenetic analysis revealed that the isolate obtained were Mycobacterium tuberculosis. The urine of six TB confirmed elephants and six healthy elephants were selected for proteomic analysis. The protein in urine was precipitated, quantified, and subjected to SDS-PAGE, enzymatic digestion, and HRLCMS analysis. Mass spectrometry data analysis revealed 49 proteins identified in TB-infected group, 68 proteins identified in control group and Galactosylgalactosylxylosylprotein 3-beta-glucuronosyltransferase was the protein exclusively present in TB-infected group. Galactosylgalactosylxylosylprotein 3-beta-glucuronosyltransferase plays a major role in glycosaminoglycan biosynthesis. This is the first report of the presence of galactosylgalactosylxylosylprotein 3-beta-glucuronosyltransferase protein in urine of elephant. [ABSTRACT FROM AUTHOR]

In this paper, we have proposed a novel deep learning-based underwater image dehazing method. The images taken under water are affected by light transportation properties like refraction, reflection, scattering, and absorption. Deep learning techniques give great results in the removal of haze in underwater degraded images. But the major challenge we are facing is the need of many images from the same location to train the model. The proposed system addressed this challenge by using CycleGAN, capable of producing synthetic underwater images from RGB in-air images, and is validated using images taken from different locations and with different characteristics. Qualitative evaluation has been done based upon visual analysis. Quantitative analysis is based upon the calculation of various parameters such as MSE, RMSE, and Euclidean distance. In addition, SSIM Loss has also been evaluated and compared. The model is tested for underwater images taken under various circumstances, and the quantitative and qualitative results obtained for these images are quite satisfactory. [ABSTRACT FROM AUTHOR]

Data publishing can infringe individual privacy. When there is a necessity to extract knowledge from data mining results, there should be a discipline followed by not disclosing individual information. There is an opportunity for the user to interpret specific individual information from data mining results and further misuse the interpreted results, resulting in infringement of privacy. Privacy preserving data publishing research attempts to guarantee accurate results yet preserves privacy of individual information. The proposed Secured Segmentation technique guarantees better accuracy (41.5) and privacy when dealing with record linkage and attribute linkage attacks. Secured Segmentation technique demonstrates K-anonymity to retain privacy when dealing with record linkage attacks. It also demonstrates L-diversity and t-closeness to retain privacy when dealing with attribute linkage attacks. [ABSTRACT FROM AUTHOR]

Stock market data is a time-series data in which stock value varies depends on time. Prediction of the stock market is an endeavor to assess the future value of a company's stock rate which will increase the investor's profit. The accurate prediction of stock market analysis is still a challenging task. The proposed system predicts stock price of any company mentioned by the user for the next few days. Using the predicted stock price and datasets collected from various sources regarding a certain equity, the overall sentiment of the stock is predicted. The prediction of stock price is done by regression and candlestick pattern detection. The proposed system generates signals on the candlestick graph which allows to predict market movement to a sufficient level of accuracy so that the user is able to judge whether a stock is a 'Buy/Sell' and whether to short the stock or go long by delivery. The prediction accuracy of the stock exchange has analyzed and improved to 85% using machine learning algorithms. [ABSTRACT FROM AUTHOR]

A new DC–DC converter capable of working with more than one source for harvesting energy from clean energy sources is proposed. Key features of this proposed converter are single inductor and reduced total number of components. In addition the converter has reduced stresses and power losses. Dual input and output modes, with its operation and steady-state analysis are discussed. Comparative study of the topologies given in literature with a proposed topology for parameters considered like the number of components and voltage gain is presented. Compatibility of the proposed converter is proved with reduced losses using loss distribution analysis of the converter and it is more reliable for energy system in telecom applications, which is validated using reliability analysis, is also highlighted. Finally, to substantiate the working of the non isolated DC–DC converter considered the test results are presented. [ABSTRACT FROM AUTHOR]

A unified power quality conditioner (UPQC) is a combination of shunt and series converter used to mitigate various power quality issues. In this work the shunt and series converters are designed with reduced number of switches. The new UPQC with reduced switches is controlled using SRF based Carrier Double Zero Sequence Signal Modulation (CDZSSM) technique to mitigate the various power quality issues like voltage sag, current ripples and Total Harmonic Distortion in voltage and current waveforms. This reduced switch UPQC with CDZSSM control inherits all the merits of the conventional UPQC system, but the proposed UPQC system has better utilization of DC link voltage and moreover the voltage stresses across the switches are reduced. The results obtained from simulation and hardware of the reduced switch UPQC are compared and presented. [ABSTRACT FROM AUTHOR]

In today's era of socioeconomic and environmental concerns, conventional energy sources are incapable of meeting increasing energy demands which leads to the significance of Microgrid (MG) systems incorporating renewable energy sources. An ideally designed microgrid capable of operating in standalone and grid connected mode is considered with photovoltaic panels, wind turbines, fuel cell, battery and Microturbines (MT) as sources. The two noteworthy disadvantages of microgrid are very expensive power supply and intermittency of power generation. Besides ensuring a steady supply, the power delivered should be of moderate cost. So, this work focuses on reducing the cost associated with its operation and emission by simultaneously analyzing the impact of uncertainty. The uncertainties can be caused due to different DGs present in MG and the load varations. The variations of uncertainty are included as outage cost. The MG operating under islanded and grid connected modes are analyzed for different scenarios to obtain optimal value of customer outage cost and operating cost. So a heuristic optimization technique which can handle the multi-objective problem is considered. The optimal solution for different operational scenarios of grid connected and islanded mode are obtained using Multi-Objective Particle Swarm Optimization (MOPSO) algorithm. [ABSTRACT FROM AUTHOR]

The article titled "Learning-based approach to underwater image dehazing using CycleGAN" has been retracted by the Editor-in-Chief and the publisher of the Arabian Journal of Geosciences. The retraction was due to concerns regarding compromised editorial handling and peer review process, inappropriate references, and the article not being within the scope of the journal. One of the authors disagrees with the retraction, while the contact information for another author could not be obtained. The remaining authors have not responded to correspondence regarding the retraction. [Extracted from the article]

Focusing on simplicity and industrial viability, polymer solar cells with configuration indium tin oxide (ITO)/ZnO/P3HT:PCBM/Ag were fabricated and characterized. Differing from the usual trend of using glove box for polymer device fabrication, here electron transport and active layer of the devices were deposited and stored in open air atmosphere without any encapsulation. Effect of active layer thickness on device performance was analyzed. Choosing the optimum thickness of 220 ± 20 nm, a number of devices were fabricated with same configuration and the effect of annealing on the photovoltaic parameters was investigated. Unlike annealing studies reported in literature, particular emphasis was given here to study the influence of annealing in ambient atmosphere, at temperature of 50 °C, for 30 s. This short period, low temperature annealing enhanced the device parameters mainly short circuit current density and hence efficiency. Lifetime measurements were done by monitoring the device and measuring its J–V parameters periodically for 1 year. X-ray photoelectron spectroscopy depth profile analysis was employed to demonstrate that surface modified ZnO effectively hinders the diffusion of indium from ITO to active layer. [ABSTRACT FROM AUTHOR]

Cloud computing is a very rapidly growing technology with more facilities but also with more issues in terms of vulnerabilities before and after deploying the applications into the cloud. The vulnerabilities are assessed before the applications are deployed into the cloud. However, after deploying the applications, periodical checking of systems for vulnerabilities is not carried out. This paper assesses the applications online for vulnerabilities at regular intervals and if any changes are made in the code, Webhook will trigger the vulnerability checking tool based on Hashing algorithm to check for vulnerabilities in the updated application. The main aim of this system is to constantly scan the applications that are deployed in the cloud and check for vulnerabilities as part of the continuous integration and continuous deployment process. This process of checking for vulnerabilities after every update in the application should be included in the software development lifecycle. [ABSTRACT FROM AUTHOR]

The present study was carried out to evaluate the in vitro cytoprotective effects of Psidium guajava and their isolated quercetin fraction to reduce the CCl4 (carbon tetrachloride) induced toxicity in HepG2 cell lines (Hepatocellular carcinoma G2). Silymarin was used as a standard drug to compare the protective effects of plant extracts in infected cell lines. MTT (3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyl-tetrazolium bromide) assay, cell viability assay, leakage parameters [Aspartate aminotransferase (AST), Alanine aminotransferase (ALT) and Lactate dehydrogenase (LDH)], lipid peroxidation and reduced glutathione (GSH) levels were used to find out the protection of human derived HepG2 cells against CCl4-induced damage. The levels of cytotoxicity, viability and GSH were reduced. While the activities of AST, ALT, LDH and lipid peroxidation was increased in CCl4-treated groups. The treatment of P. guajava and their isolated quercetin fractions (100, 200, 300 µg/mL) decreased the elevated levels of all these parameters. The results of the present study suggest that the ethanolic extract of P. guajava leaf and their isolated quercetin fractions can able to reduce the CCl4-induced cytotoxicity in HepG2 cell lines. [ABSTRACT FROM AUTHOR]

Wireless sensor network (WSN) is employed in variety of applications ranging from agriculture to military. WSN is vulnerable to various security attacks, in which jamming attacks obstruct and disturb the exchange of information between sensor nodes in WSN by transmitting signals to jam legitimate transmission to cause a denial of service. Hence, it is essential to secure the sensor networks from jamming attacks. In this paper, two approaches: fuzzy inference system (FIS) and adaptive neuro-fuzzy inference system (ANFIS)-based jamming detection system are proposed for detecting the presence of jamming by computing two jamming detection metrics, namely, packet delivery ratio and received signal strength indicator. FIS approach is based on Takagi–Sugeno fuzzy logic which optimizes the jamming detection metrics. ANFIS approach combines fuzzy logic and learning ability of the neural network to optimize the metrics for detecting various types of jamming. The proposed approaches are compared with existing system and themselves. The simulation result shows that the proposed ANFIS approach detects the jamming attacks as high as true detection ratio. [ABSTRACT FROM AUTHOR]

Feature selection is the approach of choosing subset of given dataset based on some feature. It can be used to minimize dimensions of the huge data set. So that it removes unnecessary data in the data source and produces prediction or output accurately in big data analytics. In the proposed work, feature selection algorithm process is implemented for text categorization using the algorithms ant colony optimization (ACO) and artificial neural network (ANN). This hybrid approach simulated using Reuter's data set and proved its efficiency. [ABSTRACT FROM AUTHOR]

Educational data mining (EDM) has emerged as a research area in recent years for researchers all over the world from different and related research areas. The EDM obtained knowledge can be used to offer suggestions to the academic planners in higher education institutes to enhance their decision-making process. Literature has suggested various prediction models for predicting the student's performance. This work proposes the cluster based distributed architecture for predicting the student's performance. The proposed cluster-based distributed architecture performs the prediction with clustering through Bayesian fuzzy clustering, feature extraction through Kernel-based principal component analysis, and prediction through the proposed Lion–Wolf based deep belief network (LW-DBN). The proposed architecture uses the LW algorithm to find the optimal weights for the DBN. The experimentation of the proposed work is done by collecting a real-time database and measuring the prediction performance through the mean square error (MSE) and root MSE (RMSE). The proposed LW-DBN model has achieved lower error performance than other models with MSE and RMSE values of 0.222606 and 0.050435, for the database. [ABSTRACT FROM AUTHOR]

n-Type SnS:Cu thin films are fabricated using chemical spray pyrolysis and are used successfully for solar cell device fabricationwith the configuration ITO/CZTS/SnS:Cu/ZnO:Al/Ag for the first time. The device has high open-circuit voltage (Voc) of 810 mV, short circuit current density (Jsc) of 0.87 mA/cm2, fill factor (FF) of 51% and an efficiency of 0.36%. Similar device structure is not reported so far. Even though the Jsc obtained is less, we could achieve a good Voc and FF value which are comparable with the parameters obtained for well established solar devices. The structural, morphological, electrical and optical properties of SnS:Cu films used for the cell fabrication are studied using X-ray diffraction, X-ray photoelectron spectroscopy, Raman spectroscopy, Scanning electron microscopy, Hall measurements and UV-Vis-NIR spectroscopy. The oxygen concentration is decreased from 49 to 8% as the Sulfur concentration is increased and hence proved that adjustment of precursor ratio is a very effective method to control the oxygen content of the samples, which is a determining factor in the performance of the device. This work suggests an easily adoptable method for preparing n-type SnS:Cu thin films favorable for device fabrication by varying tin to sulphur ratio. [ABSTRACT FROM AUTHOR]

This paper investigates the operation and analysis of the photovoltaic water pumping system in detail. Power electronic controllers were designed and developed for the water pumping system using a boost converter along with an inverter followed by an induction motor pump set. The proposed system could be employed in agricultural irrigation under any operating condition of varying natures of solar irradiances and temperatures. The configuration and implementation of the system were described in detail. Further, the detailed method of analysis and simulation characteristics of such PV water pumping system was also presented.With the concern of shortage of fossil fuel, global warming and energy security, the proposed PV based water pumping system can meet the significant demand of electricity and serve for the agricultural sector. [ABSTRACT FROM AUTHOR]

Objective: This study was undertaken to analyze indications, complications, outcome and the factors influencing neonatal mechanical ventilation.Methods: Prospective observational study conducted on 102 consecutive newborns, who required mechanical ventilation in a medical college tertiary neonatal care setting.Results: The commonest indication was birth asphyxia (37.3%), followed by hyaline membrane disease (HMD) (31.4%), meconium aspiration syndrome (MAS) (21.2%), septicemia (14.7%) and apnea of prematurity (5.9%). The overall survival rate in our study was 51%. Babies weighing less than 1.5 kg and less than 32 weeks of gestation had survival rates of 30% and 25% respectively. The best outcome among various indications was observed in babies with MAS (63.6%) followed by pneumonia (62.5%) and HMD (53.1%). Babies with birth asphyxia and septicemia had a low survival rate of only 42% and 40% respectively. The overall complication rate in the study was 58.8%. Common complications encountered were septicemia (42%), tube block (36%) and air leak (15%).Conclusion: About half (51%) of newborns requiring mechanical ventilations for various indications survived and more than half (58.8%) developed complications. The study also reconfirms that survival rate increases with birth weight and gestational age irrespective of indication. [ABSTRACT FROM AUTHOR]

Photothermal techniques rely on light induced heating mechanisms to evaluate various optical, thermal and electronic properties of materials. In this work, photothermal beam deflection technique is employed to investigate non-radiative transitions occurring within the conduction band and defect bands of β-InS thin films. Heat generation from β-InS thin films is triggered using laser beams of wavelength 488, 532 and 632 nm. A probe laser beam of wavelength 546 nm is used to measure the heat generation and distribution in the samples. Thermal diffusivity ( D), electronic carrier mobility ( μ), lifetime $$\left( \tau \right)$$ and surface recombination velocity ( V) are measured by fitting the theoretical and experimental photothermal response. The photothermal response and transport properties of the β-InS thin films with varying percentage of chlorine as dopant is studied to understand the role of chlorine. The presence of chlorine in these films have increased the electronic mobilty and carrier lifetime by an order of 10 by passivation of surface defects. [ABSTRACT FROM AUTHOR]

Jamming attack is a serious security threat in wireless sensor networks. Therefore, it is important to frame a mechanism to protect wireless sensor networks from various jamming attacks. Jammer intrusion detection and jamming detection are two separate issues. In this paper, a novel jammer detection framework to detect the intrusion of jammer and the presence of jamming in a cluster-based wireless sensor network is proposed. The proposed framework is novel in three aspects: whenever the cluster head receives a packet, it first verifies whether the source node is a legitimate, new node, or a jammer node. Second, when the source node is declared as a new one in the first step, then the framework validates whether the new node is legitimate node in the previous cluster or a jammer node by using cluster head code. Third, the framework observes the behavior of the newly joined node and the existing nodes to identify whether the nodes in the cluster is jammed or not. Additionally, it also classifies the types of jamming, if the presence of jamming is detected. Simulation result shows that the proposed framework performs extremely well and achieves jamming detection rate as high as 99.88 %. [ABSTRACT FROM AUTHOR]

In order to examine the influence of forcing (river flow and tides) and anthropogenic activities (dredging and dam regulation) on stratification, a study was conducted over a period of 19 months (June 2008-December 2009) in the Gautami-Godavari estuary (G-GE) during spring and neap tide periods covering entire spectrum of discharge over a distance of 36 km from the mouth. The bathymetry of the estuary was recently changed due to dredging of ∼20 km of the estuary from the mouth for transportation of barges. This significantly changed the mean depth and salinity of the estuary from its earlier state. The variations in the distribution of salinity in the Godavari estuary are driven by river discharge during wet period (June-November) and tides during dry period (December-May). The weak stratification was observed during high discharge (July-August) and no discharge (January-June) periods associated with dominant fresh water and marine water respectively. The strong stratification was developed associated with decrease in discharge during moderate discharge period (October-December). Relatively stronger stratification was noticed during neap than spring tides. The 15 psu isohaline was observed to have migrated ∼2-3 km more towards upper estuary during spring than neap tide suggesting more salt enters during former than latter period. Total salt content was inversely correlated with river discharge and higher salt of about 400×10 m psu was observed during spring than neap tide. Flushing times varied between less than a day and more than a month during peak and no discharge periods respectively with lower times during spring than neap tide. The flushing times are controlled by river discharge during high discharge period, tides during dry period and both (river discharge and tides) under moderate discharge period. This study suggests that modification of discharge, either natural due to weak monsoon, or artificial such as dam constructions and re-routing the river flow, may have significant impact on the stratification and biogeochemistry of the Godavari estuary. [ABSTRACT FROM AUTHOR]

Nanocrystalline oxygen-deficient ZnO thinfilm sensors were prepared by spray pyrolysis technique using zinc acetate dissolved in propanol and water as precursor. Response of the sensor to target gases NO2 and H2S is studied. At optimum temperature of 200.C, the sensors have a response of 3.32 to 7 ppm NO2 and 1.4 to 18 ppm of H2S gas. The analytical characterizations of the prepared sensors were performed using X-ray diffraction measurement, scanning electron microscopy, energy-dispersive X-ray spectroscopy and Raman spectroscopy. Dynamic response of sensors to different concentrations of NO2 and H2S gas was tested at optimum temperature. Experimental data revealed the sensors to be more selective to NO2 gas with satisfactory response and recovery time. [ABSTRACT FROM AUTHOR]

In this paper, it is demonstrated that the photothermal beam deflection technique can be used for measuring the series resistance, optimum load resistance, and conversion efficiency of thin-film solar cells. This technique is also used for determining the carrier transport properties of an absorber and window layer of $$\hbox {CuInS}_{2}/\hbox {In}_{2}\hbox {S}_{3}/\hbox {Ag}$$ -based solar cells during different stages of cell fabrication. Transport properties such as the carrier mobility, lifetime, and surface recombination velocity of the individual absorber and window layer are shown to influence the open-circuit voltage and short-circuit current of the final photovoltaic device. The cell parameters measured using the photothermal technique agree well with the electrical measurements. The principle of the technique is explained on the basis of the 'mirage effect' and maximum power transfer theorem. [ABSTRACT FROM AUTHOR]

Besides several thematic campaigns, utilizing a variety of platforms including satellites, ground-based networks have been established to improve our understanding of the role of aerosols in the changing monsoon climate. Two such widely known networks over the globe are 'SKYNET' and 'AERONET' with sun-sky radiometers as the principal equipment that characterizes aerosols and gases over different geographical locations under varied air mass conditions. Pune (18°43′N, 73°51′E, 559 m above mean sea level), a fast growing low-latitude, urban city in India, is one of the sites where Prede (POM-01L, SKYNET) and Cimel (CE-318, AERONET) Sun-sky radiometers have been in operation since 2004. These radiometers have been extensively used in several studies related to stand-alone and coupled aerosol-cloud-climate processes. The Prede instrument at this site is being augmented for the network of the Global Atmospheric Watch program of the World Meteorological Organization to facilitate data coordination through the World Data Center for Aerosols. The present study envisages understanding the response of atmospheric constituents, through simultaneous operation of the radiometers amongst others, for the rainfall activity over Pune during two contrasting monsoon years of 2008 (active, 98 % of long period average (LPA) rainfall over the whole country) and 2009 (weak, 78 % of LPA). The synthesis of data indicates that, apart from excellent agreement between the direct Sun observations, both radiometers capture well the monsoon features within the instrument density and efficacy of data retrieval algorithms involved. The meteorological fields from the ECMWF re-analysis and NOAA-HYSPLIT air-mass back-trajectory analysis during the study period have been utilized to explain the variations observed in the radiometer products. [ABSTRACT FROM AUTHOR]

The Kochi Backwater (KB) is the second largest wetland system in India. It is connected to the sea at Fort Kochi and Munambam (Pallipuram) (30 km north of Kochi). As the tide is forced through two openings, its propagation in the backwater system is very complicated, particularly in the northern arm of the estuary. Using synchronous water level (WL) and current measurements in the KB from a network of stations during 2007-2008, it was convenient to demarcate the northern KB into two distinct regions according to the tidal forcing from the north (Pallipuram) and south (Vallarpadam). This demarcation is useful for computing the propagation speeds of the dominant tidal constituents in the northern branch of the KB with dual opening for opposing tides. WL variations indicated that M tide (Principal lunar semidiurnal constituent) dominated in the sea level variance, followed by the K constituent (Luni-solar declinational diurnal constituent). The M tidal influence was the strongest near the mouth and decayed in the upstream direction. The propagation speed of the M tide in the southern estuary was ~3.14 m/s. The ratio of the total annual runoff to the estuarine volume is ~42 that indicates the estuary will be flushed 42 times in a year. KB can be classified as a monsoonal estuary where the river discharge exhibits large seasonal variation. [ABSTRACT FROM AUTHOR]

Shear deformation and higher order theories of plates in bending are (generally) based on plate element equilibrium equations derived either through variational principles or other methods. They involve coupling of flexure with torsion (torsion-type) problem and if applied vertical load is along one face of the plate, coupling even with extension problem. These coupled problems with reference to vertical deflection of plate in flexure result in artificial deflection due to torsion and increased deflection of faces of the plate due to extension. Coupling in the former case is eliminated earlier using an iterative method for analysis of thick plates in bending. The method is extended here for the analysis of associated stretching problem in flexure. [ABSTRACT FROM AUTHOR]

Thin films of tin disulphide on glass substrates were prepared by spray pyrolysis technique using precursor solutions of SnCl·2HO and n-n dimethyl thiourea at different substrate temperatures varied in the range 348-423 K. Using the hot probe technique the type of conductivity is found to be n type. X ray diffraction analysis revealed the polycrystalline nature with increasing crystallinity with respect to substrate temperature. The preferential orientation growth of SnS compound having hexagonal structure along (002) plane increased with the substrate temperature. The size of the tin disulphide crystallites with nano dimension were determined using the Full Width Half Maximum values of the Bragg peaks and found to increase with the substrate temperature. The surface morphology had been observed on the surface of these films using scanning electron microscope. The optical absorption and transmittance spectra have been recorded for these films in the wavelength range 400-800 nm. Thickness of these films was found using surface roughness profilometer. The absorption coefficient ( α) was determined for all the films. Direct band gap values were found to exist in all the films deposited at different substrate temperatures. The value of room temperature resistivity in dark decreased from 5.95 × 10 Ω cm for the amorphous film deposited at low temperature (348 K) to 2.22 × 10 Ω cm for the polycrystalline film deposited at high temperature (423 K) whereas the resistivity values in light decreased from 1.48 × 10 to 0.55 × 10 Ω cm respectively, which is determined using the four probe method. Activation energy of these thin films was determined by Arrhenius plot. [ABSTRACT FROM AUTHOR]

ZnSeTe films were deposited by the electron beam evaporation technique at a substrate temperature of 300 °C on glass and ITO coated GaAs substrates. The films exhibited cubic structure. Photoluminescence (PL) was studied at room temperature using an excitation wavelength of 320 nm. The films deposited on glass substrates exhibited band edge luminescence and self activated luminescence bands at 2.69 and 2.39 eV respectively. Atomic force microscopic studies indicated that the grain size increased with increase of Te content in the ternary. PL studies on the ZnSeTe/GaAs/ITO strucrure was made with an excitation of 265 nm. The films exhibited band edge emission at 2.33 eV which confirms the incorporation of Te in ZnSe. Another peak ar 2.56 eV was also observed. [ABSTRACT FROM AUTHOR]

ZnTeSe films were deposited on glass substrates kept at 200 °C by the electron beam evaporation technique. These films exhibited cubic structure and the lattice parameter increased with increase of Tellurium concentration in the films which confirmed the solid solution formation. The grain size is found to increase with Te content. The dislocation density and lattice strain show a decreasing trend with increasing of Te content. Band gap values of 2.73 eV, 2.63 eV, 2.52 eV and 2.41 eV have been calculated for the films of composition ' x' = 0.2, 0.4, 0.6 and 0.8, respectively, which confirmed the formation of solid solution between ZnSe and ZnTe. Refractive index of the films increased from 2.535 to 2.826 as the concentration of Te increased. All the films showed high resistivity values. Laser Raman spectral studies of ZnTeSe revealed LO phonon frequencies whose values are located in between the LO phonon frequencies of ZnSe and ZnTe. [ABSTRACT FROM AUTHOR]