Nutritional Status And Its Association With Diabetes Mellitus In School Children, India

Background: Poor health and nutrition may impair both the growth and intellectual development of school children. Incidence of malnutrition related childhood diabetes mellitus has increased and continues to be on the rise.Objectives: To assess the nutritional status by anthropometry and to screen for diabetes by capillary blood examination of school children. Design: Longitudinal study Setting: The study was carried out at Sri R.L.Jalappa Central School, Kolar from August 2008 to December 2009. Methods: All the school children were interviewed with pre-designed and pre-tested proforma. Height, Weight was measured by standard procedures. The nutritional status was analysed by Body Mass Index (BMI) for age. The school children were also screened for diabetes mellitus by Finger stick capillary random plasma glucose testing. The children were followed up for any major medical problems during the study period.Participants: All the students studying in the school during study period.Results: Mean height and weight of children were found comparable to the ICMR pooled data. However, compared to NCHS standards and affluent Indian children the mean height and weight were found to be much inferior at all ages. According to BMI for age as per NCHS most of the children were undernourished (79.2%) and 3 children (0.6%) were overweight. Out of 495 children screened for diabetes 14 children had hyperglycaemia (>160mg/dl). These 14 children were further tested by oral glucose tolerance test and found to have normal blood sugars levels. During the follow up two undernourished children developed diabetes mellitus. Conclusion: The magnitude of malnutrition among school going children was found to be 79%. During the follow up two undernourished children developed diabetes mellitus, hence under nutrition was associated with diabetes mellitus

A Game Theoretic Software Test-bed for Cyber Security Analysis of Critical Infrastructure

National critical infrastructures are vital to the functioning of modern societies and economies. The dependence on these infrastructures is so succinct that their incapacitation or destruction has a debilitating and cascading effect on national security. Critical infrastructure sectors ranging from financial services to power and transportation to communications and health care, all depend on massive information communication technology networks. Cyberspace is composed of numerous interconnected computers, servers and databases that hold critical data and allow critical infrastructures to function. Securing critical data in a cyberspace that holds against growing and evolving cyber threats is an important focus area for most countries across the world. A novel approach is proposed to assess the vulnerabilities of own networks against adversarial attackers, where the adversary’s perception of strengths and vulnerabilities are modelled using game theoretic techniques. The proposed game theoretic framework models the uncertainties of information with the players (attackers and defenders) in terms of their information sets and their behaviour is modelled and assessed using a probability and belief function framework. The attack-defence scenarios are exercised on a virtual cyber warfare test-bed to assess and evaluate vulnerability of cyber systems. Optimal strategies for attack and defence are computed for the players which are validated using simulation experiments on the cyber war-games testbed, the results of which are used for security analyses

Tree-Structured Nonlinear Adaptive Signal Processing

In communication systems, nonlinear adaptive filtering has become increasingly popular in a variety of applications such as channel equalization, echo cancellation and speech coding. However, existing nonlinear adaptive filters such as polynomial (truncated Volterra series) filters and multilayer perceptrons suffer from a number of problems. First, although high Order polynomials can approximate complex nonlinearities, they also train very slowly. Second, there is no systematic and efficient way to select their structure. As for multilayer perceptrons, they have a very complicated structure and train extremely slowly Motivated by the success of classification and regression trees on difficult nonlinear and nonparametfic problems, we propose the idea of a tree-structured piecewise linear adaptive filter. In the proposed method each node in a tree is associated with a linear filter restricted to a polygonal domain, and this is done in such a way that each pruned subtree is associated with a piecewise linear filter. A training sequence is used to adaptively update the filter coefficients and domains at each node, and to select the best pruned subtree and the corresponding piecewise linear filter. The tree structured approach offers several advantages. First, it makes use of standard linear adaptive filtering techniques at each node to find the corresponding Conditional linear filter. Second, it allows for efficient selection of the subtree and the corresponding piecewise linear filter of appropriate complexity. Overall, the approach is computationally efficient and conceptually simple. The tree-structured piecewise linear adaptive filter bears some similarity to classification and regression trees. But it is actually quite different from a classification and regression tree. Here the terminal nodes are not just assigned a region and a class label or a regression value, but rather represent: a linear filter with restricted domain, It is also different in that classification and regression trees are determined in a batch mode offline, whereas the tree-structured adaptive filter is determined recursively in real-time. We first develop the specific structure of a tree-structured piecewise linear adaptive filter and derive a stochastic gradient-based training algorithm. We then carry out a rigorous convergence analysis of the proposed training algorithm for the tree-structured filter. Here we show the mean-square convergence of the adaptively trained tree-structured piecewise linear filter to the optimal tree-structured piecewise linear filter. Same new techniques are developed for analyzing stochastic gradient algorithms with fixed gains and (nonstandard) dependent data. Finally, numerical experiments are performed to show the computational and performance advantages of the tree-structured piecewise linear filter over linear and polynomial filters for equalization of high frequency channels with severe intersymbol interference, echo cancellation in telephone networks and predictive coding of speech signals

A Research and Strategy of Remote Sensing Image Denoising Algorithms

Most raw data download from satellites are useless, resulting in transmission waste, one solution is to process data directly on satellites, then only transmit the processed results to the ground. Image processing is the main data processing on satellites, in this paper, we focus on image denoising which is the basic image processing. There are many high-performance denoising approaches at present, however, most of them rely on advanced computing resources or rich images on the ground. Considering the limited computing resources of satellites and the characteristics of remote sensing images, we do some research on these high-performance ground image denoising approaches and compare them in simulation experiments to analyze whether they are suitable for satellites. According to the analysis results, we propose two feasible image denoising strategies for satellites based on satellite TianZhi-1.Comment: 9 pages, 4 figures, ICNC-FSKD 201

PRELIMINARY ANALYTICAL STUDY OF SAINDHAVADYA GHRUTA

Ghruta is considered best among the Snehas. Its usage is being highlighted by our Acharyas in the disorders of brain like Unmada, Apasmara etc. This study focuses on one such preparation Saindhayadya ghruta mentioned in Yogaratnaka Apasmara chikitsa. Literary review done through various sources like books, journals and internet revealed that, no studies have been carried out on this formulation yet. Hence an attempt was made to study Saindhayadya ghruta through qualitative and quantitative analysis of Physico-chemical parameters and to develop fingerprints of High-Performance Thin Layer chromatography study (HPTLC). HPTLC densitometric scan of chloroform extract of unsaponifiable matter of Saindhvadhya Ghruta showed 9 and 6 spots at 254nm and 366nm respectively. To interpret the results, there are no previous standard markers established for Saindhavadya ghruta. This analytical profile may help in the identification of Saindhavadya ghruta in future and to maintain the standard quality of the formulation

A Deep Cascade of Convolutional Neural Networks for MR Image Reconstruction

The acquisition of Magnetic Resonance Imaging (MRI) is inherently slow. Inspired by recent advances in deep learning, we propose a framework for reconstructing MR images from undersampled data using a deep cascade of convolutional neural networks to accelerate the data acquisition process. We show that for Cartesian undersampling of 2D cardiac MR images, the proposed method outperforms the state-of-the-art compressed sensing approaches, such as dictionary learning-based MRI (DLMRI) reconstruction, in terms of reconstruction error, perceptual quality and reconstruction speed for both 3-fold and 6-fold undersampling. Compared to DLMRI, the error produced by the method proposed is approximately twice as small, allowing to preserve anatomical structures more faithfully. Using our method, each image can be reconstructed in 23 ms, which is fast enough to enable real-time applications

Prevalence of Traumatic Dental Injuries to Anterior Teeth of 12-Year-Old School Children in Kashmir, India

Background: Traumatic dental injuries to anterior teeth are a significant public health problem, not only because their prevalence is relatively high, but also because they have considerable impact on children’s daily lives. Traumatic dental injuries (TDIs) cause physical and psychological discomfort, pain and other negative impacts, such as tendency to avoid laughing or smiling, which can affect social relationships. Objectives: This study aimed to assess the prevalence of traumatic dental injuries to anterior teeth among 12-year-old school children in Kashmir, India. Patients and Methods: A cross-sectional study was conducted in private and government schools of India among 1600 schoolchildren aged 12 years. In addition to recording of the type of trauma (using Ellis and Davey classification of fractures, 1970), over jet, Angle’s molar relation and lip competence were also recorded. The socioeconomic status and academic performance of the study subjects were registered. The data obtained were compiled systematically and then statistically analyzed. The statistical significance for the association between the traumatic injury and the variables was analyzed using the chi-square test. Logistic regression was used to identify potential risk predictors of TDIs. Results: The overall prevalence of TDI to anterior teeth was found to be 9.3%. The TDI to anterior teeth in male was more than female, but the difference was statistically nonsignificant (P < 0.01). Falls and sports were the most common causes of trauma in the present study. The highest potential risk factor for the occurrence of trauma was over jet. Academic performance was found to be significantly associated to TDI to anterior teeth, when analyzed in a multiple regression model. Conclusions: It was concluded that the prevalence of traumatic dental injuries was 9.3%. Traumatic dental injuries among children exhibit complex interaction between the victims’ oral conditions and their behavior. Therefore, prevention should consider a number of characteristics such as oral predisposing factors, environmental determinants and human behavior. It is recommended that specific and proper public places for leisure and sports activities, with impact-absorbing surfaces around the items on which children are most likely to fall, should be provided

Studying alumina boundary migration using combined microscopy techniques

Thermal grooving and migration of grain boundaries in alumina have been investigated using a variety of microscopy techniques. Using two different methods, polycrystalline alumina was used to investigate wet, (implying the presence of a glassy phase), and dry grain boundaries. In the first, single-crystal Al2O3 was hot-pressed via liquid phase sintering (LPS) to polycrystalline alumina with an anorthite glass film at the interface. Pulsed laser deposition was used to deposit approximately 100-nm thick glass films. Specimens were annealed in air at 1650°C for 20 h to induce boundary migration. Boundary characterization was carried out using visible light (VLM) and scanning electron (SEM) microscopies. Effects on migration due to surface orientation of grains were investigated using electron backscatter diffraction (EBSD). The second method dealt with heat treating dry boundaries in polycrystalline alumina to monitor boundary migration behavior via remnant thermal grooves. Heat treatments were conducted at 1650°C for 30 min. The same region of the sample was mapped using VLM and atomic force microscopy (AFM) and followed over a series of 30 min heat treatments. Boundary migration through a pore trapped inside the grain matrix was of particular interest

Influence of Charge Transport Layers on Open Circuit Voltage and Hysteresis in Perovskite Solar Cells

Perovskite materials have experienced an impressive improvement in photovoltaic performance due to their unique combination of optoelectronic properties. Their remarkable progression, facilitated by the use of different device architectures, compositional engineering, and processing methodologies, contrasts with the lack of understanding of the materials properties and interface phenomena. Here we directly target the interplay between the charge-transporting layers (CTLs) and open-circuit potential (VOC) in the operation mechanism of the state-of-the-art CH3NH3PbI3 solar cells. Our results suggest that the VOC is controlled by the splitting of quasi-Fermi levels and recombination inside the perovskite, rather than being governed by any internal electric field established by the difference in the CTL work functions. In addition, we provide novel insights into the hysteretic origin in perovskite solar cells, identifying the nature of the contacts as a critical factor in defining the charge accumulation at its interface, leading to either ionic, electronic, or mixed ionic-electronic accumulation

Breeding tomatoes suitable for processing with triple disease resistance to tomato leaf curl disease, bacterial wilt and early blight

India is the second largest producer of tomato with 11 per cent global share and cultivated on an estimated area of 0.76 million hectares with productivity of 24 tonnes per hectare. Less than 1% of the produce is processed when compared to 26% in other major producing countries. Of the estimated more than 41 million tonnes of tomato processed globally, only 130,000 tonnes were processed in India and domestic demand for processed tomato products is expanding at an estimated 30% annually. At present traditional fresh market tomato cultivars are being processed though such cultivars are unsuitable for processing. Processors in India are looking for high yielding tomato cultivars with high total soluble solids (5-6 º Brix), acidity not less than 0.4%, pH less than 4.5 and uniform red colour with a/b colour value of at least 2. In addition, firm fruited tomato cultivars with joint less pedicel (j2) which facilitate mechanical harvesting or rapid hand picking. ICAR-Indian Institute of Horticultural Research has recently developed two high yielding F1 hybrids in tomato viz: Arka Apeksha and Arka Vishesh suitable for processing. On evaluation for three years, both the hybrids recorded good level of total soluble solids (4.5-5º Brix) and colour value of 2. Further, both the hybrids had high yield potential (80-90 tonnes / hectare) with triple disease resistance to tomato leaf curl disease, bacterial wilt and early blight. Arka Apeksha and Arka Vishesh were also bred with jointless pedicel making them suitable for mechanical harvesting. Our experimental studies on vine storability revealed that all the fruits were intact on plants even 110 days after transplanting in the main field facilitating once over harvest