A Language for Verification and Manipulation of Web Documents: (Extended Abstract)

In this paper we develop the language theory underpinning the logical framework PLF. This language features lambda abstraction with patterns and application via pattern-matching. Reductions are allowed in patterns. The framework is particularly suited as a metalanguage for encoding rewriting logics and logical systems where proof terms have a special syntactic constraints, as in term rewriting systems, and rule-based languages. PLF is a conservative extension of the well-known Edinburgh Logical Framework LF. Because of sophisticated pattern matching facilities PLF is suitable for verification and manipulation of HXML documents.     

Color tunable nanocrystalline SrGd2Al2O7:Tb3+ phosphor for solid state lighting

Color tunable Tb³⁺ doped SrGd₂Al₂O₇ nanophosphor is synthesized employing a facile and economic urea assisted solution combustion approach. XRD studies confirm the crystallization of single phased SrGd_2(1-x)Tb_2xAl₂O₇ nanophosphor in tetragonal lattice with I4/mmm (139) space group. Rietveld refinement is performed over SrGd_1.9Tb_0.1Al₂O₇ sample to execute qualitative as well as quantitative phase analysis. TEM analysis confirms the more or less spherical shaped phosphors in nano domain with average particle size ranging 45–80?nm. Photoluminescent investigation reveals that this nanophosphor can be successfully excited by ultraviolet light yielding significant luminescent properties arising due to radiative transitions from ⁵D_3,4 levels to ⁷F_j levels. Dipole-dipole interactions are solely responsible for the energy transfer causing concentration quenching. Concentration controlled luminescent tendency can be employed to induce chromaticity from blue to green region. Findings of the study proclaim the application of this nanophosphor as one of the green component of tricolor based ultraviolet excited white LEDs.     

Incidence and Molecular Typing of Vibrio parahaemolyticus from Tiger Shrimp Culture Environments along the Southwest Coast of India

Vibrio parahaemolyticus is one of the most prevalent food-borne pathogens along the southwest coast of India, where marine foods are frequently consumed. Shrimp (Penaeus monodon) and environmental samples were collected from aquaculture farms located in and around Cochin. Confirmation of the biochemically identified strains with species-specific toxR gene and detection of virulent genes viz., tdh and trh was performed by polymerase chain reaction (PCR). The phenotypic markers for the presence of tdh and trh genes were assayed by Kanagawa phenomenon and urease activity, respectively. Protease activity was examined to identify other potential virulence factors. After phenotypic characterization of bacterial strains fingerprinting of genomic DNA was carried by various typing methods, viz., random amplified polymorphic DNA (RAPD), enterobacterial repetitive intergenic consensus sequence (ERIC), repetitive extragenic palindromic sequence (REP), and ribosomal gene spacer sequence (RS) PCR methods to assess the genetic diversity within the isolates. Eighteen percent of the samples were found positive for the incidence of V. parahaemolyticus by biochemical protocols and toxR (368 bp) targeted PCR. PCR analyses revealed 1% of the samples positive for tdh (269 bp) and trh (500 bp) gene. RAPD analysis revealed clustering of toxigenic strains into a single group. Cluster analysis revealed the conglomeration of isolates into two, five, and seven major groups using RS, ERIC, and REP PCR methods, respectively. RS PCR generated fewer amplified bands compared to REP and ERIC PCR methods, thus giving scope for higher discrimination. Moreover, RS PCR patterns were more discernible visually from other patterns, suggesting RS PCR as a considerably practical method for routine use.     

Exergy and energy analysis of a wavy fin radiator with variously shaped nanofluids as coolants

The present study deals with the energy and exergy analysis of a wavy fin radiator deploying various shapes of Al₂O ₃‐water as nanocoolant. The effects of radiator effectiveness, pumping power, heat transfer rate, and performance index with variously shaped nanoparticles, mainly spherical, brick, and platelet, on coolant flow rates and air velocities have been investigated. Also, the impacts of entropy, second law efficiency, entropy generation number, and irreversibility on radiator performance analysis have been considered with steady‐state assumptions. Theoretical analysis revealed that the spherical particle–based nanocoolant showed 21.9%, and 18.2% higher effectiveness than platelet and brick nanocoolants. However, minimization in the entropy generation is observed in the platelet shape of the nanoparticle. The second law efficiency is 13% higher for the spherical nanocoolant compared with the brick nanocoolant. An optimum entropy generation number is found at a coolant flow rate of 13 l/min and then gradually decreases with an increase in the coolant flow rate. For all the considered operating parameters, the spherical nanoparticle showed a better performance than brick and platelet nanofluids as a radiator coolant. Due to the enhanced overall performance for the spherical nanofluid, it may be considered as a potential candidate for a radiator coolant.     

Deep Neural Artificial Intelligence for IoT Based Tele Health Data Analytics

Tele health utilizes information and communication mechanisms to convey medical information for providing clinical and educational assistances. It makes an effort to get the better of issues of health service delivery involving time factor, space and laborious terrains, validating cost-efficiency and finer ingress in both developed and developing countries. Tele health has been categorized into either real-time electronic communication, or store-and-forward communication. In recent years, a third-class has been perceived as remote healthcare monitoring or tele health, presuming data obtained via Internet of Things (IOT). Although, tele health data analytics and machine learning have been researched in great depth, there is a dearth of studies that entirely concentrate on the progress of ML-based techniques for tele health data analytics in the IoT healthcare sector. Motivated by this fact, in this work a method called, Weighted Bayesian and Polynomial Taylor Deep Network (WB-PTDN) is proposed to improve health prediction in a computationally efficient and accurate manner. First, the Independent Component Data Arrangement model is designed with the objective of normalizing the data obtained from the Physionet dataset. Next, with the normalized data as input, Weighted Bayesian Feature Extraction is applied to minimize the dimensionality involved and therefore extracting the relevant features for further health risk analysis. Finally, to obtain reliable predictions concerning tele health data analytics, First Order Polynomial Taylor DNN-based Feature Homogenization is proposed that with the aid of First Order Polynomial Taylor function updates the new results based on the result analysis of old values and therefore provides increased transparency in decision making. The comparison of proposed and existing methods indicates that the WB-PTDN method achieves higher accuracy, true positive rate and lesser response time for IoT based tele health data analytics than the traditional methods.

     

Weaning foods: a review of the Indian experience

Although breastmilk is adequate to meet the energy and nutrient requirements of an infant up to four to six months of age, thereafter it is insufficient to sustain normal growth and needs to be supplemented with other foods, such as weaning foods. However, the capacity of a weaning diet to meet the protein and energy requirements of infants depends on its nutritional quality as well as its dietary bulk. This review highlights varieties of weaning foods, blend formulations, nutrient requirements, process characteristics, physicochemical parameters, quality evaluation, and other important aspects of developing a weaning food that satisfies all the requirements of the infant during the vulnerable transitional stage. Traditional weaning foods of India are briefly summarized.     

Deep-fat fried noodle-like products from model individual blends of corn starch with casein,soy protein or their hydrolysates

The present work reports on the oil content of fried noodle-like products prepared from model individual blends of corn starch with casein, soy protein or their hydrolysates in ratios ranging from 80:20 to 20:80 of protein/hydrolysate:starch. In general, the oil content increased for all blends with an increase in the content of the protein/protein hydrolysate. However, there was a pronounced increase in oil uptake with an increase in the content of protein hydrolysates in the model blends. The Results are interpreted with respect to possible differences in surface tension and hydrophobicity, which are known to influence oil content in fried foods. © 1999 Society of Chemical Industry     

Screening of hydrocolloids for reduction in oil uptake of a model deep fat fried product

Reduction of oil content in deep fat fried foods would be welcome by both the food manufacturers and the consumers. Among the many approaches that have been evaluated for this purpose, use of hydrocolloid additives is believed to be most promising. Work in this area is restricted mostly to cellulose derivatives. The mechanism of action of these derivatives is attributed to formation of an oil resistant barrier film, an alteration in surface hydrophobicity of the product being fried, and the thermal gelation. However, most hydrocolloids would alter the surface hydrophobicity, and many of them have the ability to form films. Furthermore, the presence of other food constituents can alter all these properties. Hence, hydrocolloids at 0.25— 2.00 % (on the basis of chickpea flour) were screened for their ability to reduce oil uptake in sev, a model deep fat fried product prepared from chickpea flour. Results obtained indicate that the ability to reduce oil uptake in this product decreases in the following order: gum arabic > carrageenan > gum karaya > guar gum > carboxymethylcellulose > hydroxypropylmethyl cellulose. Hydrocolloids such as xanthan, gum ghatti, gum tragacanth, and locust bean gum were found to be ineffective (<10 % reduction in the oil content) for this purpose.