Biocontrol of biomass bulking caused by Haliscomenobacter hydrossis using a newly isolated lytic bacteriophage

This research demonstrates the first ever application of lytic bacteriophage (virus) mediated biocontrol of biomass bulking in the activated sludge process using Haliscomenobacter hydrossis as a model filamentous bacterium. Bacteriophages are viruses that specifically infect bacteria only. The lytic phage specifically infecting H. hydrossis was isolated from the mixed liquor of a local wastewater treatment plant. The isolated bacteriophage belongs to the Myoviridae family with a contractile tail (length-126 nm; diameter-18 nm) and icosahedral head (diameter-81 nm). Titer of the isolated phage with H. hydrossis was calculated to be 5.2 ± 0.3 × 10⁵ PFU/mL and burst size was found to be 105 ± 7 PFU/infected cell. The phage was considerably stable after exposure to high temperature (42 °C) and pH between 5 and 8, emphasizing that it can withstand the seasonal/operational fluctuations under real-time applications. Phage to host (bacteria) ratio for the optimal infection was found to be 1:1000 with ∼54% host death. The isolated phage showed no cross infectivity with other bacteria most commonly found in activated sludge systems, thus validating its suitability for biocontrol of filamentous bulking caused by H. hydrossis. Following the phage application, successful reduction in sludge volume index (SVI) from 155 to 105 was achieved, indicating improved biomass settling. The application of phage did not affect nutrient removal efficiency of the biomass, suggesting no collateral damage. Similar to phage therapy in medical applications, phage-mediated biocontrol holds a great potentiality for large-scale applications as economic agent in the mitigation of several water, wastewater and environmental problems. Present study in this direction is a novel effort.     

Multiple Functional Ingredient Approach in Formulating Dietary Supplement for Management of Diabetes: A Review

Food and nutrition science has moved from identifying and correcting nutritional deficiencies to designing foods that promote optimal health and reduce the risk of disease. Diabetes is rapidly emerging as a pandemic. It is also accompanied by several health implications viz. cardiovascular diseases, obesity, hypertension, cancer, depression, and eating disorders. International Diabetes Federation estimates that in 2010, India is home to 50.8 million diabetics and the number is expected to go up to a whopping 87 million by 2030. The primary goal of medical nutrition therapy was to design special dietary products for patients with hyperglycemia, intended in controlling postprandial plasma glucose fluctuations and hypercholesterolemic tendencies. However, an effective way to minimize these health risks could be through modifications in the diet by inclusion of multiple functional ingredients, aimed for their concerted role in management of individuals suffering with diabetes.     

Experimental investigation on natural fibre composite for thermal insulation performance enhancement

ABSTRACT

This experimental investigations deals with the natural fibre composites such as abaca and kenaf with carbon for thermal insulation performance enhancement. The square matrix is used for this analysis. Volume fractions, ratio of thermal conductivity lumen were the most important considerations for this investigation with respect to the thermal conductivity of the corresponding composites. The experimental and theoretical results were compared for the performance identifications.     

Estimation of Thermal Properties and Heat Transfer Study during Continuous Processing of Rice in Milk

Cooking rice and milk simultaneously is the basis of some popular cereal-based dairy products (e.g., rice-pudding, kheer). A conceptual design for continuous processing of rice in milk is being developed and is a helical coil heat exchanger to cook the rice-milk mixture, which is otherwise prepared as a batch process. The present study investigates the thermo-physical properties of the rice-milk mixture as functions of temperature and composition. In addition, a fundamentals-based heat transfer model is presented that includes the effects of milk fouling to estimate the drop in temperature of the product at the outlet, the degree of fouling, and fouling thickness that would build up with time and length of the helical coil. Fouling thickness increases towards the outlet and the rate of increase in fouling thickness decreases with time. At the outlet, a significant drop in temperature is observed (11°C) as an adverse effect of milk fouling.     

Retinoic acid receptor-gamma in human epidermis preferentially traps all-trans retinoic acid as its ligand rather than 9-cis retinoic acid

Brain injury in the premature infant is an extremely important problem, in part because of the large absolute number of infants affected yearly. The 2 principal brain lesions that underlie the neurological manifestations subsequently observed in premature infants are periventricular hemorrhagic infarction and periventricular leukomalacia. The emphases of this article are the neuropathological features, pathogenesis, and potential means of prevention of these 2 lesions. Recent work suggests that the ultimate goal, prevention of the lesions, is potentially achievable. Periventricular hemorrhagic infarction may be avoidable by prevention of germinal matrix-intraventricular hemorrhage, and periventricular leukomalacia by detection of impaired cerebrovascular autoregulation, prevention of impaired cerebral blood flow, and interruption of the cascade to oligodendroglial cell death by such agents as free radical scavengers.     

Shape extraction: A comparative study between neural network-based and conventional techniques

Extraction of the skeletal shape of an elongated object is often required in object recognition and classification problems. Various techniques have so far been developed for this purpose. A comprehensive comparative study is carried out here between neural network-based and conventional techniques. The main problems with the conventional methods are noise sensitivity and rotation dependency. Most of the existing algorithms are sensitive to boundary noise and interior noise. Also, they are mostly rotation dependent, particularly if the angle of rotation is not a multiple of 90°. On the other hand, the neural network based technique discussed here is found to be highly robust in terms of boundary noise as well as interior noise. The neural method produces satisfactory results even for a very low (close to 1) Signal to Noise Ratio (SNR). The algorithm is also found to be efficient in terms of invariance under arbitrary rotations and data reduction. Moreover, unlike the conventional algorithms, it is grid independent. Finally, the neural technique is easily extendible to dot patterns and grey-level patterns also.