Search

BACKGROUND Gestational hypertension and preeclampsia are major causes of an array of adverse maternal & foetal outcome. Even though previous history is the strongest risk factor among multigravida, the incidence of preeclampsia is on raise with life style changes. High prepregnancy BMI and increase in the BMI between pregnancies contribute significantly to an adverse outcome. Birth interval is more is usually associated with increase in maternal age and more chance for maternal weight gain. Prior preterm delivery is also known to increase the risk of preeclampsia/ gestational hypertension in women with & without preeclampsia in previous pregnancy. Increase in maternal age and exorbitant gestational weight gain are known to increase the risk of preeclampsia. This prospective observational study was conducted to determine the incidence of primary gestational hypertension/ preeclampsia in multigravida & to delineate its risk factors. MATERIALS AND METHODS This study was carried out between February 2009 and January 2011 in a tertiary care hospital among multigravid pregnant women booked at the antenatal clinic. Multigravida with 2 or more singleton pregnancies with records of previous pregnancies furnishing lack of evidence of GHT/ preeclampsia and those with complications like HT, DM, renal disease, autoimmune disease with their onset in the interpregnancy period were included in the study. Data was analysed for the risk variables among the total group and the results were expressed as percentages. Qualitative analysis was done using the chi square test. Value of less than 0.05 was taken as significant. RESULTS After all exclusions, the final cohort consisted of 723 women with 2 or more consecutive singleton pregnancies. Incidence of primary gestational hypertension/ preeclampsia among parous women in the study population was 4.8%. Incidence of gestational hypertension was 3%, while preeclampsia was 1.7%. Majority of patients among GHT were in the 31-35 yrs age group (36.4%) while preeclampsia was more frequent in > 35yrs (38.5%). Elderly gravida was observed to be a notable risk factor. The percentage of overweight & obese women was more among cases compared with the remaining multigravida. Change in BMI of more than 1 unit compared to previous pregnancy was seen to be an important risk factor. Exorbitant gestational weight gain, chronic hypertension & diabetes mellitus were also significant risk factors for primary onset of GHT/preeclampsia in multigravida. CONCLUSION This study infers that there is a significant association between- high prepregnancy BMI (overweight/ obesity), change in prepregnacy BMI between pregnancies (of more than 1 unit), advanced maternal age (>35yrs), excessive gestational weight gain in pregnancy, chronic hypertension and diabetes mellitus prior to present pregnancy with their onset in the interpregnancy period, with gestational HT/ preeclampsia in the index pregnancy among parous women with previous normal pregnancies. [ABSTRACT FROM AUTHOR]

Background: Induction of mutation plays an important role in the breeding programme among modern methods of plant breeding. Genetic variability is prerequisite for crop improvement and through induced mutation it was found to be very effective for creating variability in the quantitative and qualitative characters. Hence, the present study was aimed to induce genetic variability within short time. In the present investigation positive as well as negative impact on quantitative traits were recorded. Methods: The experiment material comprised of seeds of horsegram [Macrotyloma uniflorum (Lam.) Verdc] variety Paiyur 2 which was subjected to ethyl methane sulphonate (02, 0.3, 0.4 and 0.5%), gamma radiation (100, 200, 300 and 400 Gy) and combination treatments. The mutations affecting gross morphological changes in growth and yield characters such as plant habit, flowering, pod morphology, maturity and seed yield were scored as quantitative characters. The micro mutations at population level can be easily detected in the form of increased variations for quantitative traits in the segregation of mutagen treated populations. Micro mutations can alter morpho-physiological characters hence they are of a particular interest to the plant breeders. ANOVA test was performed to determine the significant differences and Duncan's multiple range test (p=0.05) to compare the differences among treatment means. Result: Among the twenty-five treatments studied both the mutagens, gamma radiations and Ethyl Methane Sulphonate proved to be very effective to induce variability in quantitative traits in M2 and M3 generations. The results of Duncan's multiple range test analysis revealed that the treatment of mutagens in combinations induced more positive effects as compared to that of using alone. The combined treatments were found positive for improvement of primary branches per plant, no. of pods per plant, pod length, no. of seeds/pod and seed yield per plant in M2 and M3 generations whereas the treatment of gamma irradiation imparted its significant role for improvement of plant height, days required for 50% flowering, days to maturity and 1000 seed weight in both M2 and M3 generations whereas the treatment with Ethyl Methane Sulphonate is useful for improving no. of pods per plant and no. of seeds/pod in M2 generation alone. [ABSTRACT FROM AUTHOR]

Microseismic signals are characterized by a low signal-to-noise ratio and a high degree of non-stationary noise. Therefore, attenuation of noise in the microseismic signal is a very challenging task. In this article, a hybrid denoising technique is proposed based on variational mode decomposition (VMD) with adaptive non-local means filtering. VMD is an adaptive signal processing technique that divides a signal into bandlimited intrinsic mode functions (BIMFs). To improve the algorithm's flexibility and finesse, sample entropy is applied to distinguish the levels of the BIMFs. These BIMFs are filtered adaptively using NLM. Further, these new BIMFs are added and filtered using soft thresholding. Initially, evaluation is carried out on a synthetic seismic signal to reveal the dominance of the suggested method against the other described denoising approaches. Then, the performance of the proposed method is verified on a real microseismic signal. The results reveal that the proposed method can effectively remove the noise and is superior to other described methods. [ABSTRACT FROM AUTHOR]

The goal of this work concentrates on MRI (Magnetic Resonance Imaging) brain tumor findings by utilizing the BRATS dataset images. At first, it undergoes preprocessing criteria using an enhanced DWT (Discrete Wavelet Transform) filtering to decrease the noise level in the picture. Following this, segmentation has to extricate the tumor region dependent on improved thresholding activity. At that point, its effectiveness has processed by using the performance measurements, for example, Normalized cross-correlation, PSNR (Peak Signal to Noise Ratio), NAE (Normalized Absolute Error), and AD (Average Difference). The reproduction results show that unrivaled outcomes on the proposed thresholding task contrasted with comparable techniques. Furthermore, this was better than the other strategies for both Rician and Gaussian noise. The proposed approach supports the experts in identifying the exact location of the tumor and broadening their lifetime. [ABSTRACT FROM AUTHOR]

Background: Under nutrition is a condition due to insufficient intake of energy and nutrients to meet an individual's needs to maintain good health. Cereals and millets based supplementary foods represents good source of essential nutrients. Recently, millets are tagged as nutri-cereals and its health promoting benefits are attracting consumers worldwide. The current study was aimed to develop millet based ready-to-use composite mix and to evaluate its quality in terms of usage in various traditional foods and shelf life. Methods: RTU composite mix was developed using locally available cereals, millets, pulses and oilseeds. The nutrient composition of developed mix was analyzed. The traditional region specific foods namely Dose, roti and Mudde (Ragi ball) was prepared and subjected for sensory evaluation. Further mix was stored up to three months at room temperature and evaluated for microbial load, moisture, free fatty acid and peroxide value. Result: Protein, fat, carbohydrate and energy content of the mix were 18.5 g, 9.56 g, 58.21 g and 393.24 kcal per 100 g respectively. Roti was best accepted (7.63), followed by mudde (7.50) and dose (7.03). Free Fatty Acid (FFA) was increased from 1.08 per cent to 1.56 per cent oleic acid, whereas peroxide value (PV) was increased from 7.46 to 9.35 mEq O2/kg of oil during storage. Total bacterial count (TBC) was increased from 4.5x102 to 8.1x103. The developed RTU mix which has nutritional potential needs to be popularized to address under nutrition and for overall good health of the society. [ABSTRACT FROM AUTHOR]

In this study, a unique generative adversarial network (GAN) architectural variation was suggested, which engages in adversarial game serve by preserving an appropriate distance in the latent dimension of the network. This method overcomes the mode collapse problem with a small dataset. Extensive experiments are conducted using the segmented medical leaf dataset with various classes and the generator network is able to produce all the artificial image classes. This is accomplished by combining a unique training technique with a reasonably simple model design. [ABSTRACT FROM AUTHOR]

In diagnosing and treating Diabetic Retinopathy, segmenting and classifying retinal images is a difficult job. Fundus Retinal Imaging is used to diagnose diabetics and it provides additional detail for obtaining Retinal Image sequences. The proposed study uses a Fractional Jaya Optimizer-based Deep Convolutional Neural Network (FJO-DCNN) to classify blood vessels in retinal images segmented by the optic disc. The segments are created using a clustering mechanism known as Particle Swarm Optimization (PSO), which ensures the efficacy of optimum segment placement, allowing for more precise detection of the optic disc. Finally, using this hybrid algorithm, the intensity degree is determined, and a better output score is obtained, despite the Fuzzy judgement mapping. The proposed study computed the best values for accuracy, sensitivity, and specificity in FJO-DCNN for blood vessel classification. [ABSTRACT FROM AUTHOR]

Characterization of 80 pigeonpea genotypes using 17 morphological traits was done at different stages of plant growth. The traits stem colour, pod constriction and pod pubescence were monomorphic. Five traits viz., plant growth habit, leaf shape, pod length, number of seeds per pod and seed colour pattern were dimorphic. Seven traits viz., plant branching pattern, time of flowering, colour of base of petal, pod colour, plant height, seed shape and seed size were trimorphic. The trait pattern of streaks on standard petal was tetramorphic. The accessions used in this study exhibited five different seed colours and it was dominated by brown seed colour while the frequency of accessions with other colours was very low. Phenotypic diversity in the studied collection proves it to be suitable for developing superior varieties with prefarable features. The pigeonpea genotypes were subjected to cluster analysis which grouped them into five clusters. Cluster II was big with 39 genotypes and cluster IV was small with two genotypes. Cluster I consisted of 10 genotypes and cluster III comprised of 15 genotypes. Thirteen genotypes were placed in cluster V. The pigeonpea genotypes ICPL 11255 and ICPL 20338 are very early, thus can be utilized in future breeding programmes for development of early maturing varieties. [ABSTRACT FROM AUTHOR]

Background: The major abiotic stress limiting the plant growth and productivity across the globe is salinity. This may be overwhelmed by growing salt tolerant varieties. Hence, the present study has been figured out to sort out the salt tolerant and salt sensitive cultivars of finger millet. Methods: In this study 15 cultivars of finger millet (Eleusine coracana L.) seeds were grown at different NaCl concentrations (50 mM, 100 mM, 150 mM and 200 mM) on germination stage. Germination percentage, root length, shoot length, fresh weight, dry weight and vigour index of the seedlings were measured using different concentrations of NaCl. Result: Salt tolerant cultivars were discovered to be GPU 28, GPU 67, ML 365, Udurumallige, PYR1 and GPU 48 at 150 mM and ML 365 at 200 mM salt accumulation, while cultivars such as VL 400 and KM252 were very much sensitive to NaCl. Accessions with tolerance to salinity are precious genetic material for future crop improvement program. [ABSTRACT FROM AUTHOR]

Air pollution is a major concern for the global community due the environmental degradation and human health related issues. Along with vehicular gaseous discharges, there are microbial contaminants in our atmospheric air causing health problems. Different types of innovations have been carried to produce efficient face masks suitable to filter both particulate and microbial contaminants. In this paper, low cost and highly stable nanofibrous ZnO/PVA/PVP composite films created utilizing electrospinning technique, and their various properties, including antimicrobial activities are reported in the first time. Zinc Oxide (ZnO) nanoparticles dispersed homogeneously mixed PVA/PVP polymer blend solution was used in the electrospinng system to prepare ZnO/PVA/PVP composite nanofiber. The nanofiber properties have been investigated utilizing scanning electron microscope (SEM), Fourier transform infrared (FTIR) spectroscopy, Raman spectroscopy, UV–Visible spectroscopy and X-Ray Diffraction (XRD). Antimicrobial activity study conducted on the fibers showed good results, indicating the usefulness of the prepared nanofibrouse material for antimicrobial face masks. [Display omitted] [ABSTRACT FROM AUTHOR]

In order to explore the genetic architecture of finger millet through combining ability studies, the present investigation was carried out using 20 hybrids which were produced using five lines and four testers in a Line x Tester mating design. Among the parents, the line GPU 48 and the tester KMR 301 were found to be the good general combiners with significant per se for most of the traits studied. Hybrids viz., GPU 48 x KMR 301, GPU 48 x PR 1506, PYR1 x KMR 301 and Udurumallige x PR 1506 showed significant positive values for per se performance, sca effect, mid parent heterosis and better parent heterosis for grain yield per plant. The cross GPU 48 x KMR 301 derived from high x high general combining parents exhibited higher positive significant value for all the three types of heterosis for grain yield per plant. The hybrids GPU 48 x KMR 301, GPU 48 x PR 1506, PYR1 x KMR 301 and Udurumallige x PR 1506 were good specific combiners for yield and yield contributing traits. In all these crosses, at least one good general combining parent is involved which indicates that good general combiners serve as the best tool in enlightening the crop yield by manipulating the genetic architecture. Combining ability variances indicated that even if GCA and SCA variances were profound, SCA variances were higher than GCA variances for all the characters studied representing the predominance of non-additive type of gene action in the inheritance of traits under present study. [ABSTRACT FROM AUTHOR]

The present study was designed to evaluate the effect of Celastrus paniculatus seeds methanolic extract (CPME) against lipopolysaccharide (LPS)-induced paw edema and nociception in rats. Moreover, in-vitro test for soluble epoxide hydrolase (sEH) inhibition activity of CPME was conducted to study its possible mode of action. Celastrus paniculatus seeds were extracted with methanol by cold maceration for 7 days. The obtained dark brown coloured extract was evaluated for preliminary phytochemical screening and subjected for HPTLC analysis. Then the extract was evaluated for its action against LPS-induced paw edema in rats at the dose of 100, 200 and 400 mg/kg body weight by measuring the paw edema, nociceptive bioassays and estimating 5-HETE in serum. In addition, CPME was evaluated for in-vitro sEH inhibition activity. Administration of CPME attenuates LPS-induced paw edema by 22.85% and serum 5-HETE levels by 9.56% (P<0.001) and elevated pain threshold by 112.19% (P<0.001). The CPME inhibits human, mouse and rat sEH activity with IC50 of 4.60 µg/mL, 4.17 µg/mL and 5.18 µg/mL, respectively. The present study results indicate that CPME has protective effect against LPS-induced inflammation and pain in rats. The possible mode of action is attenuation of 5-HETE levels and sEH inhibition. However, further research is warranted to elucidate and isolate the active constituents from Celastrus paniculatus seeds. [ABSTRACT FROM AUTHOR]

Machine learning has extensive application in diverse medical fields. With advancements in medical technologies, access has been given to data for the identification of diseases in theirearly stages. Alzheimer's Disease (AD) is a chronic illnessthat will cause degeneration of the brain cells and ultimately will lead to memoryloss. AD causedcognitive mental problems like forgetfulness and confusion, as well as other symptoms such aspsychologicaland behavioralproblems, are further recommended to undergo test procedures usingneuroimagingtechniques. This work's objective is to utilize the machinelearning algorithms for processing the data acquired via neuroimaging technologies for early-stage AD detection. The framework extracts featuresusingcurvelet transform from MRI brain image. This work will also present the Decision Tree, the Adaptive Boosting (AdaBoost), and the Extreme Gradient Boosting (XGBoost) classifiers. In machine learning, Population-Based Incremental Learning (PBIL) is an optimization algorithm, in spite of being simpler than a conventional genetic algorithm, the PBIL algorithm is able to achieve much better results in several cases.PBIL is used to optimize the AdaBoost and XGBoost classifiers to improve AD classification. The experimental outcomes will demonstrate the proposed approach's superior performance over that of other existing approaches. [ABSTRACT FROM AUTHOR]

This paper presents Magnetic Resonance Imaging (MRI) brain tumor detection utilizing Fuzzy C Means strategy with an upgraded noise filtering calculation. A novel technique is proposed to enhance the execution of cerebrum tumor discovery. A new calculation for noise filtering is adapted to extract the correct area of tumor, where execution is enhanced by upgrading the threshold task in wavelet filtering strategy as a preprocessing step. Trial results demonstrate that by utilizing proposed calculation, the filtering procedure gives better execution when contrasted with the current methods. The average value of Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) for Gaussian noise is improved by 40% and 41.06% and for Rician noise, which is 13.73% and 25.39% higher than the state-of-art methods. After filtering, segmentation is done to point out the tumor region. For segmentation, Otsu and FCM methods are adapted here and a comparison is made between these two methods. Experimental results show that Jaccard and Dice coefficient of Fuzzy C Means (FCM) with enhanced filtering is increased by 3.6% and 1.3% compared to the methods available in the literature. [ABSTRACT FROM AUTHOR]

In the present investigation, eighteen finger millet genotypes were raised in randomized block design to study about the genetic variability for quantitative traits. Phenotypic coefficient of variation was relatively high as compared to that of genotypic coefficient of variation for all the traits studied. The traits namely grain yield / plant and straw yield / plant depicts higher value for phenotypic and genotypic coefficient of variation which indicates the occurrence of broader variability for these characters. All the characters exhibited higher heritability except finger width which showed their genetic capability to transmit genes from parents to their offspring with least impact of environment. High heritability along with high genetic advance as percent of mean was recorded for number of fingers/ ear, finger length, ear head length, number of productive tillers, grain yield and straw yield showed that the additive gene action was predominant for these characters and favours effective selection. The present study revealed that there was significant variability is available in the experimental material and this might be effectively utilized for future crop improvement either through selection or via hybridization. [ABSTRACT FROM AUTHOR]

This paper proposes a fuzzy economic order quantity and fuzzy optimum total cost for the suggested supply model. Carrying cost and Setup cost are considered in Decagonal fuzzy number. The objective of this study is to select a suitable defuzzification method to obtain the optimum ordering size and effective entire expenditure. [ABSTRACT FROM AUTHOR]

In this work we have studied an backlog model for damaged products with logarthimic stipulation rate for the optimal stock of commodities which may be either constant or vary with time. This paradigmatic is developed to find the fuzzy total cost of the inventory system so as to get the lower expenditure. Time dependent deterioration of time is considered. For defuzzification the proposed model is dealt with heptagonal fuzzy numbers. Numeric illustration is dispensed to exhibit the evaluation of suggested layout. [ABSTRACT FROM AUTHOR]

A case study of erythema annulare centrifugum (EAC) induced by azole antifungals in a patient with extensive tinea, focusing on its clinical manifestation and challenges in diagnosis. It underscores the importance of recognizing drug-induced EAC, emphasizing the need for a high clinical suspicion and careful management, including the cessation of causative medications for effective resolution.

The present study aimed to estimate the nature and magnitude of genetic divergence in 60 horse gram genotypes for ten characters using Mahalanobis D2 analysis. The genotypes were grouped into thirteen clusters. Concerning intracluster distance, the genotypes falling within cluster III (31.51) has maximum divergence. Maximum inter-cluster distance was observed between cluster VIII and XIII (184.05), followed by cluster XI and XIII (170.83). Cluster VIII exhibited a higher mean for hundred seed weight, grain yield per plot and Bhusa yld/plot and cluster VI contained genotypes with the higher mean value for pod length and the number of seeds per pod. Among the yield contributing characters, the traits viz.,grain yield per plot (28.30%) followed by the number of pods per plant (26.21 %) and the number of branches per plant (18.36%) contributes to major genetic divergence. The results indicated that from cluster IV the genotype HA 871-5-67/2 was selected for plant height, from cluster II the genotype Morappur-1 was chosen for the number of branches per plant, from cluster XII the accession HG 102 was selected for the trait number of pods per plant, from cluster VI the genotype T 45 was chosen for pod length and the number of seeds per pod. From cluster VIII the genotypes 12EB and IC 9606 were nominated for hundred seed weight, grain yield per plot and Bhusa yield per plot(g). [ABSTRACT FROM AUTHOR]

Management of IT services is rapidly adapting to the cloud computing environment due to optimized service delivery models. Geo distributed cloud data centers act as a backbone for providing fundamental infrastructure for cloud services delivery. Conversely, their high growing energy consumption rate is the major problem to be addressed. Cloud providers are in a hunger to identify different solutions to tackle energy management and carbon emission. In this work, a multi-cloud environment is modeled as geographically distributed data centers with varying solar power generation corresponding to its location, electricity price, carbon emission, and carbon tax. The energy management of the workload allocation algorithm is strongly dependent on the nature of the application considered. The task deadline and brownout information is used to bring in variation in task types. The renewable energy-aware workload allocation algorithm adaptive to task nature is proposed with migration policy to explore its impact on carbon emission, total energy cost, brown and renewable power consumption. [ABSTRACT FROM AUTHOR]

The widespread adoption of cloud computing by several companies across diverse verticals of different sizes has led to an exponential growth of Cloud Service Providers (CSP). Multiple CSPs offer homogeneous services with a vast array of options and different pricing policies, making the suitable service selection process complex. Our proposed model simplifies the IaaS selection process that can be used by all users including clients from the non-IT background. In the first phase, requirements are gathered using a simple questionnaire and are mapped with the compute services among different alternatives.In the second phase, we have implemented the Sugeno Fuzzy inference system to rank the service providers based on the QoS attributes to ascertain the appropriate selection. In the third phase, we have applied the cost model to identify the optimal CSP. This framework is validated by applying it for a gaming application use case and it has outperformed the online tools thus making it an exemplary model. [ABSTRACT FROM AUTHOR]

Principal component analysis was carried out with experimental material comprising of 30 sorghum land races and observations were recorded on eleven biometrical traits viz., days to 50 per cent flowering, days to maturity, plant height, the number of tillers per plant, inflorescence length, inflorescence width stem thickness, hundred seed weight, grain yield per plant, fodder yield per plant (wet) and fodder yield per plant (dry). The results of the principal component analysis indicated that four out of eleven principal components with eigenvalues >1 were obtained. Principal components 1, 2, 3 and 4 contributed 31.82, 18.41, 13.16 and 10.3 per cent towards the variation observed among accessions, respectively. Regarding the comparison of the first four principal components, variation proportional to the first component was positive for days to 50 per cent flowering, days to maturity and inflorescence length. The second principal component was negatively associated with fodder yield per plant (wet) and fodder yield per plant (dry). The third principal component was a positive influence on stem thickness whereas, other traits viz., the number of tillers per plant, hundred seed weight, grain yield per plant had contributed negatively. The fourth principal component was associated with plant height, inflorescence width negatively. [ABSTRACT FROM AUTHOR]

The present study was aimed to carry out correlation and path analysis in Dolichos Bean (Lablab Purpureus L.) Genotypes . The field experiment was carried out using twenty-six genotypes of field bean in Randomized Block Design with three replications. Biometrical observations were recorded on days to fifty percent flowering, days to maturity, plant height, number of branches/plant, number of pod/plant, grain yield (g) and green pod yield (g). Among the various polygenic characters, yield is a complex character and it depends on several yield attributing characters. Hence, the knowledge of association between yield and its component traits is needed, which forms the basis for selection. Partitioning of total correlation into direct and indirect effects by path coefficient analysis helps gain information on the relative status of the plant characters, making the selection more effective. At both phenotypic and genotypic levels, green pod yield recorded moderately significant and positive correlation with plant height and number of branches/plant and the traits viz., number of pod/plant and grain yield (g) exhibited an extremely significant and positive correlation with green pod yield. Days to maturity showed the first maximum positive direct effect (3.986) on green pod yield, followed by number of pod/plant (2.241) and number of branches/plant (0.143). Whereas the other characters viz., days to fifty percent flowering, plant height and grain yield recorded direct negative effect on green pod yield. The results indicated that the characters viz., days to maturity, number of branches/plant, number of pod/plant and green pod yield were the most desirable yield contributing characters. Their contribution to grain yield and green pod yield is in positive direction via direct effect. Hence, selection based on these characters would be rewarding for improving grain yield and green pod yield in Dolichos bean. [ABSTRACT FROM AUTHOR]

The agricultural land mass is more than just being a feeding sourcing in today's world. Agriculture productivity defines the economy of India in a great manner. So, in plants, disease detection plays a vital role in agriculture field. Automatic disease detection approaches are used for detecting plant diseases during the initial stages. To identify the agricultural diseases using digital image based on various features like color, textures and shape. Research firm currently doing a research to detect and diagnosis agricultural diseases based on digital image. This survey provides a better understanding of the soft computing techniques and image processing used for researcher and farmers to identify the agricultural diseases. This survey highlights several diseases of agricultural plants like rice, apple, cucumber, graphs, banana, cherry, wheat and sugarcane. And also this analysis work provides the comparison analysis of different research techniques in terms of their merits and demerits along with numerical analysis. [ABSTRACT FROM AUTHOR]

Bulk metallic glasses (BMGs) with new chemical compositions (ZrCoAgAlNi) were fabricated and the effects of Ag minor addition on the glass forming ability (GFA) and crystallization kinetics were studied. The x-ray diffraction (XRD) test was applied to identify the amorphousness of BMGs or possible crystalline phases. Using differential scanning calorimeter (DSC), the thermal stability and crystallization kinetics under a non-isothermal condition at the different heating rates were studied. Considering the heating rate dependency of glass transition and crystallization kinetics, the activation energy was evaluated and measured for the mentioned processes. It was revealed that the rise in Ag content led to the decrease in activation energy for glass transition, while the activation energy for crystallization increased. The thermal stability and GFA were also studied and it was found that the Ag addition strongly affected the inherent features of BMGs. With the increase in Ag content, the atomic mobility and structural rearrangement changed in the material and consequently, the GFA and thermal stability were significantly improved. [ABSTRACT FROM AUTHOR]

Hypoglycemic drugs in the dipeptidyl peptidase-4 (DPP-4) inhibitor class are used as a second-line treatment for type 2 diabetes mellitus. With DPP-4 inhibitors, there have been a few reports of cutaneous side effects such as bullous response, fixed drug eruption, and photosensitivity. There is no definitive pathophysiology for the above mentioned allergic reactions. Sitagliptin phosphate belongs to the DPP-4 inhibitor class. This is a case report of a sitagliptin-induced bullous drug reaction manifesting three weeks after starting therapy. He had bullous pemphigoid-like eruptions all over the body. The patient showed improvement once sitagliptin was discontinued alon with oral and topical steroid treatment. [ABSTRACT FROM AUTHOR]

Pathogenesis of diabetes mellitus involves scores of different factors, out of which Glucagon like factor-1 (GLP-1) plays a foremost role. GLP-1 is a peptide-hormone of the incretin system. It exhibits glucagonostatic as well as glucose dependent insulinotropic action. GLP-1 augments regeneration of β-cell, boost secretion of insulin and trim down weight gain in type-2 diabetes. GLP-1 discharge from the L cells of intestine is mediated by neural and hormonal factors which are stimulated by the occurrence of nutrients in the gastrointestinal tract. Conversely, GLP-1 is instantaneously shattered by enzyme dipeptidyl peptidase-IV. GLP-1 is also cleared by renal clearance. Diminished GLP-1 leads to attenuated insulin release leading to type-2 diabetes. Substitution of GLP-1 regularizes the insulin release and prevents type-2 diabetes. However, GLP-1 holding infinitesimal plasma half life limits its therapeutic effects. To surmount the limitations of indigenous GLP-1, several GLP-1 receptor agonist like Exenatide are been developed. Modifications in pharmaceutical formulation are also been made to meet the patients adherence to the medication of GLP-1 agonist. [ABSTRACT FROM AUTHOR]

Summary: Radio frequency identification device (RFID) has emerged as one of the most potential building blocks for future IoT‐enabled technologies. Various applications like logistic monitoring use the RFID system to deal with the tagged objects. RFID‐based tracking approach is extremely solicited for appropriate logistic distribution because of the frequent tagged‐objects rearrangements. Nevertheless, with an RFID system, one of the most significant issues is resolving collisions between tags as they transfer data to the reader at the same time. This work investigates the core issue of locating all lost tags in RFID systems. The most significant factor in missing tag recognition is to reduce the time required for execution. A problem needs to be formulated to differentiate the tagged objects' motion state, that is, static or dynamic, to handle this issue. It tracks the moving objects with various existing localization approaches. Finally, a tag detection known as constructive Steiner graph matching (CSGM) detection is proposed to achieve time efficiency by utilizing RFID collision signals. Specifically, the physical‐layer features are considered for differentiating the positions. Experimental outcomes demonstrate that the anticipated model can attain better prediction accuracy by reducing inventory time compared to other approaches. Simulation findings show that the suggested approach performs exceptionally well in giving a significant performance boost in an RFID system. It minimizes the complexity of tracking the objects. The simulation outcomes illustrate that the algorithm's identification speed is substantially enhanced and ensuring high system efficiency. The simulation results of the proposed algorithm have been improved in terms of system efficiency (9.5%), success rate (6.3%), and identification speed (4%) compared to the conventional algorithm. The suggested CSGM technique's average waiting time is decreased by more than 45.372%, and its detection speed is increased by at least 38.219% compared to other existing algorithms. [ABSTRACT FROM AUTHOR]

The unprecedented growth in personal, business and research data motivates users to lease storage from multiple cloud storage providers like Amazon, Azure, etc. Selection of cost-effective cloud storage service by considering different pricing policies along with their performance characteristics is a challenging task. This research proposes a model named as OUTFIT (Optimal sUgeno Type Fuzzy Inference sysTem) an optimal data storage hosting model by suggesting an appropriate storage type based on user demands. In the first phase, we have surveyed Amazon, Google Cloud, Azure and Rackspace cloud storage providers and consolidated the different cloud storage types supported by them. In the second phase the cloud service providers are ranked by using Sugeno fuzzy inference system based on the user preference. The third phase designates the appropriate service that incurs minimal estimated storage usage cost. The proposed approach is able to categorize various cloud service providers with an optimal grading process by including multiple decision criteria for fine-grained storage type selection. The observed results prove it to be a more favourable selection tool in comparison with its counterpart tools like Cloudorado, RightCloudz in terms of cost. [ABSTRACT FROM AUTHOR]

Aim: This study was aimed to investigate antimicrobial and cytotoxicity effect of nano ZnO in in vitro for the application of livestock feed supplement. Materials and Methods: Nano ZnO was synthesized by wet chemical precipitation method using zinc acetate as a precursor and sodium hydroxide was used for reducing the precursor salt. The properties of synthesized powder were characterized using ultraviolet (UV)-visible spectroscopy, Fourier transform infrared (FTIR), scanning electron microscopy (SEM), and X-ray diffraction (XRD), respectively. In vitro antimicrobial activities were analyzed against the pathogenic bacteria in poultry Escherichia coli, Staphylococcus aureus, Klebsiella pneumoniae, and Streptococcus aeruginosa. 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay was conducted to analyze the cytotoxicity effect of nano ZnO. Results: SEM showed a spherical ZnO particle in the range of 70-100 nm. The size of the particle and purity of the sample were confirmed by XRD. The nano-sized ZnO particles exhibited the UV absorption peak at 335 nm. In FTIR spectroscopy, pure ZnO nanoparticles showed stretching vibrations at 4000-5000 cm-1. ZnO nanoparticles exhibited remarkable antibacterial activity against E. coli, S. aureus, K. pneumoniae, and S. aeruginosa bacterial strains. Cell viability was significantly reduced in a dose-dependent manner in the cytotoxicity study. Conclusion: From the broad-spectrum antibacterial activity and the lower cytotoxicity observed at the prescribed dose, it is concluded that nano ZnO powder is a potential alternate zinc supplement for livestock. [ABSTRACT FROM AUTHOR]

The scientific workflows in the field of science like biology and astronomy are essential in facilitating and automating the scientific data of high volumes and their processing especially in a computing structure that is large. Owing to the large need for resources, a public heterogeneous cloud tends to play a major role in the completion of tasks. The traditional researches falling into the scheduling workflows in cloud applications were focusing on the problems that have a quality of service that is not sufficient for the competitive environment that exists today. There are scientific workflows that consist of several granular tasks which are intensive in terms of data. For a computational granularity that is efficient, the task clustering has a major role to play in reducing the length of the schedule and the utilization of resources. The workflow scheduling is a prominent issue in cloud computing, and this makes an attempt to map workflow tasks to VMs on the basis of various functional needs. The very popular approaches to this are either the static or the dynamic scheduling algorithms that have been based on various heuristics like the Opportunistic Load Balancing (OLB). But, in the case of workflow scheduling, this becomes a non-deterministic polynomial-hard optimization and is a challenge to achieve within an optimal schedule. The proposed work is a vertical node partition that makes use the vertical node partition that make use of a heuristic and novel shuffled frog leaping algorithm (SFLA) technique of clustering for optimal scheduling of scientific workflow. The results of the technique have shown that the SFLA proposed along with the method of clustering has achieved better performance (in terms of makespan and utilization of resources) compared to the SFLA and the OLB without clustering. [ABSTRACT FROM AUTHOR]

Big Data has been a term used in datasets which are complex and large in such a way there are some traditional technologies of data processing which are not adequate. Big Data can revolutionize most aspects in society such as collection or management of data from Big Data which is challenging and also very complex. The Hadoop has been designed for processing a large amount of unstructured and complex data. It has provided with a large amount of storage for data along with the ability to be able to tackle unlimited and concurrent tasks or jobs. The selection of features is an extremely powerful technique in the reduction of dimensionality and is also the most important step in machine learning applications. In recent decades, data is getting larger in a progressive manner in terms of instances and numbers making it very hard to deal with the problem of feature selection. In order to cope with such an epoch of Big Data, there are some more new techniques that are required to address the problem in a more efficient manner. At the same time, the suitability of the algorithms currently used may not be applicable especially when the size of data is above hundreds of gigabytes. For the purpose of this work, the correlation-based feature selection along with mutual information-based methods of feature selection was used for improving the performance. The AdaBoost and the support vector machine based classifiers have been used for improving their accuracy. The results of the experiment prove that the method proposed was able to achieve better performance compared to that of the other methods. [ABSTRACT FROM AUTHOR]

Dengue fever is a viral infection transmitted to humans by mosquitoes that live in tropical and subtropical climates and carry the virus. Blood testing detects the dengue virus or antibodies produced in response to dengue infection. Nowadays, the doctors need to know the set of predicted features on dengue virus in order to classify the infected patients and suspected patients, where the suspected patients can be treated in advance by predicting the similar features from the infected patients. This works applies data mining techniques on the real-time clinical data. The data consists of the infected patient records from their admitted date to death date. The sources of data are collected from Rajapalayam Hospital which is a crucial region of Tamilnadu where Dengue death rate is raised. Each dataset consists of nearly 200 attributes. To achieve the knowledge discovery task, this work concentrates on Hierarchical clustering as a data mining technique. The proposed work includes 3 processes to validate the Dengue virus. The first process Preprocessing involves filtering the risk factors for developing dengue hemorrhagic fever. The second concentrates on eliminating trivial factors of disease from the infected persons. The third process involves the final stage in validating the virus from the calculated IgG(Immunoglobulin G) and IgM(Immunoglobulin M) values from the clinical dataset with initial results(attributes regarding blood) from the laboratory test and resulted dendrogram shows the age factor and infected feature. The high IGM is the critical stage of dengue patients that some patients face the fatal condition. Therefore, the experts can utilize the method to predict the virus based on the symptoms intense. [ABSTRACT FROM AUTHOR]

In recent decades, the Internet of Things (IoT)-enabled Wireless Sensor Network (IWSN) facilitates to development of numerous real-time applications. IWSN has become significant expertise in acquiring a better quality of service, long-term consistency, and low-cost management. Nevertheless, the sensor nodes of IWSN typically have restricted battery energy and are vulnerable to several intrusion attacks. To address the constraints of IWSN, an energy-efficient clustering and rapid intrusion detection system have been proposed. A novel MapDiminution-based Training-Discovering Optimization method is employed in the proposed framework to obtain optimal cluster routing path from each cluster to sink. Once the route is determined, the MapDiminution model invokes the task scheduling process in which each cluster member is managed with the queuing framework. This optimum path and scheduling process reduces the energy consumption in IWSN. Afterward, the Hybrid classifier can be formulated by integrating Artificial Neural Network (ANN) with Simulated Annealing (SA). The weights of ANN are optimized through the SA where the different types of intrusion attacks are then classified based on received information from the cluster nodes. The simulation results expose that the proposed framework achieves a lesser energy intake of 0.01 J and a higher detection accuracy of 97.57% as compared to the existing methods. [ABSTRACT FROM AUTHOR]

Magnetic susceptibilities of spin–1/2 systems of orthorhombic and higher crystal symmetries have been numerically investigated while taking possible anisotropy in the coupling constants along different crystal axes into account. The work relies on the magnon-based theory of ferromagnetic (FM) and antiferromagnetic (AFM) crystal systems of types FFF, AFF, AAF, and AAA [J. Chem. Phys. 111, 9009 (1999)]. The AAF crystal, in particular, shows interesting changes in the temperature dependence of magnetic susceptibility when the ferromagnetic exchange coupling constant is varied. We especially show that the susceptibility anomalies of molecular crystals fit naturally within the framework of the extended magnon-theoretical formalism, and do not necessarily imply a FM→AFM or a reverse phase transition. A real system, molecular crystal of 2,4,6-triphenylverdazyl (2,4,6-TPV), has been investigated here. It was previously interpreted as an AAF system from observed susceptibility data [Tomiyoshi et al., Phys. Rev. B 49, 16031 (1994)]. The trend of the temperature dependence of magnetic susceptibility studied in the present work also indicates that the crystal belongs to the AAF category with a less prominent FM exchange coupling constant. To reinforce our conclusions, we have adopted a two-pronged strategy. First, the geometry of the 2,4,6-TPV monomer has been optimized here by ab initio unrestricted Hartree–Fock (UHF) calculations using the STO-3G basis set. The optimized geometry is almost planar. A subsequent calculation has been carried out with the phenyl rings twisted out of the plane of the nitrogen atoms. The STO-3G optimized geometry, and the same geometry except for the twisted phenyl rings, have been used to perform ab initio coupled-cluster (UCCSD-T) calculations with the same basis, and UHF as well as density-functional (UB3LYP) calculations using the 6-31G basis set. The calculated data can easily rationalize the twists while the species remains in crystal. The magnetic category of the crystal has been unambiguously confirmed as AFA from ab initio UHF and UB3LYP calculations of the total energy in different spin states of dimers and trimers along the crystal axes. The computed energy values, however, fail to yield accurate estimates of the exchange coupling constants J[sub a], J[sub b], and J[sub c], because the latter are on the order of 1k[sub B]K corresponding to energy differences on the order of 10[sup -6] hartree between different spin states. In the second approach, the observed features of the susceptibility minimum and maximum have been used to determine the best values of the exchange coupling constants from the theoretical formulas for an anisotropic AFA crystal. The AFM (J[sub a] and J[sub c]) and FM (J[sub b]) exchange coupling constants and the Néel temperature (T[sub N]) found from this analysis correspond to J[sub a]+J[sub c]=-1.05 k[sub B]K, J[sub b]=1.35 k[sub B]K, and T[sub N]=1.75 K. The calculated J values significantly differ from those estimated from a linear Heisenberg chain model, but generate a susceptibility versus temperature graph that mimics the experimental plot. © 2004 American Institute of Physics. [ABSTRACT FROM AUTHOR]

Due to lack of a central bureaucrat in mobile ad hoc networks, the security of the network becomes serious issue. During malicious attacks, according to the motivation of intruder the severity of the threat varies. It may lead to loss of data, energy or throughput. This paper proposes a lightweight Intruder Node Detection and Isolation Action mechanism (INDIA) using feature extraction, feature optimization and classification techniques. The indirect and direct trust features are extracted from each node and the total trust feature is computed by combining them. The trust features are extracted from each node of MANET and these features are optimized using Particle Swarm Optimization (PSO) algorithm as feature optimization technique. These optimized feature sets are then classified using Neural Networks (NN) classifier which identifies the intruder node. The performance of the proposed methodology is studied in terms of various parameters such as success rate in packet delivery, delay in communication and the amount of energy consumption for identifying and isolating the intruder. [ABSTRACT FROM AUTHOR]

An enhanced nonvolatile magnetic flip-flop is introduced in this paper. Spin torque transfer magnetic tunnel junction (MTJ) with the breakdown concept is used to design FDSOI circuit, which is implemented with 45 nm. The proposed flip-flop structure named enhanced nonvolatile magnetic flip-flop which uses the power retention technique in order to control the leakage power Large Scale Cluster based Engineering Application. The proposed design requires less design effort and offers greater power reduction up to 75 % and smaller area cost than the existing method. [ABSTRACT FROM AUTHOR]

The most natural source of problems in semigroup theory is the study of semigroup of transformations. It is well known that Green's relations play an important role in the theory of semigroups. The definition of Cayley graphs of groups was introduced by Arthur Cayley in 1878 and Cayley graphs of semigroups are general- izations of Cayley graphs of groups. In this paper, we study the Cayley graphs of Symmetric inverse semigroup relative to Green's equivalence R-Class. [ABSTRACT FROM AUTHOR]

The present study reports the preparation and evaluation of a water soluble octenyl succinylated cassava starch‐curcumin nanoformulation with enhanced bioavailability and anticancer potential. The major drawback of curcumin as a bioactive compound is its poor aqueous solubility and the resultant low bioavailability. In this study, curcumin has been incorporated in octenyl succinate cassava starch by a wet grinding method and the product is characterized by Fourier transform infra red spectroscopy (FTIR), scanning electron microscopy (SEM), transmission electron microscopy (TEM), dynamic light scattering (DLS), atomic force microscopy (AFM), and X‐ray diffraction (XRD) analyses. The OSA starch loaded nanocurcumin is found to be non‐toxic to L929 cells, but shows anti‐cancer potential to HeLa cells. A significant enhancement in cellular uptake also can be achieved for the OSA starch loaded nanocurcumin as revealed by fluorescence microscopy. The in vitro release of curcumin from the nanostarch matrix is more controlled at simulated intestinal pH than that at gastric pH. Pharmacokinetic study shows that bioavailability of nanocurcumin is increased by about 71.27%. [ABSTRACT FROM AUTHOR]

Diterpenoid lactones and flavonoids are major bio‐active compounds of therapeutically important medicinal herb Andrographis paniculata (Burm.F.) Nees. The lack of a validated protocol for quality assurance of raw herbs is a significant issue for its wider use. A validated LC‐ESI‐MS/MS method developed using MRM mode for simultaneous determination of five diterpenoid lactones (andrographolide, neoandrographolide, andrograpanin, 14‐deoxy‐11,12‐didehydroandrographolide and andrographiside) along with two flavonoids (7‐O‐methylwogonin and apigenin). Chromatographic separation of seven analytes was achieved within 14 minutes in Alltima column (100×4.6 mm, 3 μm) using gradient elution. The developed method was accurate (97.77 to 101.17 %; recovery), precise (intra‐day and inter‐day %RSD of 0.22–2.19 and 1.01–3.68, respectively) and linear (R2 >0.99). To meet the regulatory obligation, uncertainty associated with the measurement was also evaluated by using different validation parameters. Developed method was successfully employed in analysing the analytes quality in different solvent extracts. Total diterpenoid lactones and flavonoids (DTLF) content was recorded highest in methanol extract (45.47 μg g−1) followed by ethanol (39.23 μg g−1) and lowermost content found in petroleum ether extract (0.38 μg g−1) in triplicate samples. Since the method is simple, rapid, sensitive, and accurate, it has potential role for quality evaluation of A. paniculata and its derived formulation. [ABSTRACT FROM AUTHOR]

Rice, a vital staple for millions globally, plays a pivotal role in food security and livelihoods. There is a steady increase in the export of non-basmati rice to other countries in recent years due to migration from India and changing dietary pattern. The quality of rice exported from India is compromised by millers to achieve market need. This study focuses on finding quality traits preferred by different markets and identifying varieties suitable for export. For this purpose, Representative export rice samples were collected and compared with the TNAU released rice varieties. Quality traits of 34 rice genotypes, comprising both TNAU rice varieties and rice samples collected from traders were evaluated. Key quality parameters namely kernel length, cooking characteristics, physicochemical attributes, and organoleptic traits were evaluated. Samples collected from traders fall into three categories, RNR 15048 type and BPT 5204 type for premium price and CO 51 type for low premium price. Varieties ADT 43 and TKM 15 can be recommended as alternates for CO 51 type, CO 55 for RNR 15048 type and TKM 13, CO 52 and CO 43 for BPT 5204 type. The genetics of various quality traits were studied which revealed high genetic advance and high heritability for kernel breadth, kernel breadth after cooking, length breadth ratio, gel consistency and gelatinization temperature. The Principal Component Analysis (PCA) offered insights into the inherent variation within the genotypes and classified them into four group. This study aided in identifying varieties with export potential which will fetch high price in international market. [ABSTRACT FROM AUTHOR]

Background: Nano-technology is currently an emerging field and giving promising results with cost economics in the poultry nutrition sector. A study was conducted to investigate the effects of nano Zn supplementation on production performance, immune response and carcass characteristicsin Japanese quail broiler. Methods: Synthesis of zinc oxide nano-particles was carried out by chemical method and characterized by standard techniques. Day old Japanese quail chicks (n=240) were randomly allotted in four treatment groups for feeding trial and fed with basal diet and source of zinc viz. for T1 inorganic zinc oxide, for T2, T3 and T4 nano zinc oxide was used at 75%, 50% and 25% levels of BIS recommendation for Zinc. Production parameters, immune response, carcass characteristics and cost economics were studied. Result: Based on the data analysed T3 and T4 showed significantly (P<0.05) improved performance in production parameters like body weight gainand cumulative feed conversion ratio than T1 and T4. HI, titer value and carcass characteristics data also showed similar trend. [ABSTRACT FROM AUTHOR]

To evaluate the effect of optic nerve sheath fenestration (ONSF) on the rate of visual function improvement in patients with pseudotumor cerebri syndrome (PTCS). Retrospective chart review of patients with PTCS who underwent ONSF between 1998 and 2017. Visual function was evaluated by evaluating visual field (VF), mean deviation (MD), retinal nerve fiber layer (RNFL) thickness, papilledema grade, and visual acuity (VA) prior to and after ONSF. Seventeen female patients aged 17 to 36 years underwent unilateral ONSF. Follow-up averaged 40.1 months. VF MD improved steadily in both eyes up to 12 months. Average RNFL thickness improved in the operated eye from 347 ± 166 mm to 92 ± 27 mm (p <.001) and the non-operated eyes from 306 ± 165 mm to 109 ± 46 mm (p <.001). The grade of papilledema improved in the operated eye from 3.3 ± 1.3 to 0.3 ± 0.7 and the non-operated eye from 3.0 ± 1.6 to 0.18 ± 0.4. There was an exponential rate of improvement in papilledema and RNFL thickness, with the greatest improvement occurring within the first 30 days. Average visual acuity remained intact in both eyes before and after surgery. ONSF in appropriately selected patients leads to rapid improvement in papilledema and a steady recovery in VF. [ABSTRACT FROM AUTHOR]

Let G be the dihedral group Dn and Cay(G, S) is the Cayley graph of G with respect to S, and let CG(x) is the centralizer of an element x in G and x is the orbit of x in G. In this paper, we prove that if G act on G by conjugation, the vertex induced subgraph with vertex set CG(x) of the Cayley graph Cay(G, x) is either Hamiltonian or it contain Hamiltonian decompositions. But if n is prime, it is always Hamiltonian. [ABSTRACT FROM AUTHOR]