Oil application has a potential to improve weight gain and cause less weight loss in first 7 d in low birth weight neonates.

Addition of topical EMLA application or vapocoolant spray to breastfeeding during wDPT vaccination does not reduce duration of cry in infants up to 3 months of age. However, they are able to show reduction in pain score and further studies are warranted to assess their efficacy as pain relief measures in infants and children.

Point of care testing, is the term commonly applied to the bedside tests performed in sick patients. Common clinical conditions encountered in pediatric emergency rooms are respiratory, gastro-intestinal, infections and cardiac. Emergencies at most of the places, especially developing countries are overburdened. Availability of tests like arterial blood gas, lactate, electrolytes and procalcitonin, bedside tests or point of care tests can help identify sick patients quickly. Abnormalities like acid-base disturbances and dyselectrolytemias can be dealt with instantly, thus improving the overall prognosis. Lactate levels in emergency give the earliest clue to cardiovascular compromise and poor tissue perfusion. Procalcitonin has recently gained significant importance as an acute phase reactant for early identification of sepsis. Decisions for initiating or withholding antibiotic therapy can also be taken based on procalcitonin levels in emergency. Bedside estimation of serum electrolytes, blood gas analysis and procalcitonin thus facilitate the clinical evaluation and management of critical patients. An extensive literature review of current status of these investigations as point of care tests is appraised here.

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Globally more than one-third of the irrigated area is under waterlogging which limits our wheat production and out of which northern Indo-Gangetic plains of India alone had 2.5 million ha affected by irregular waterlogging. So, to meet out the food demand of ever-growing population we have to find some alternates to harness the potential of the waterlogged area. With this point of view this investigation was conducted to study the changes in growth and biochemical behavior of wheat due to waterlogging at ear emergence stage in sodic soil and also to assess the traits conferring higher yield at experimental site of department of crop physiology, Narendra Deva University of Agriculture & Technology, Kumarganj, Faizabad (U.P.), India. The results showed that the genotypic variability exists for waterlogging tolerance in wheat varieties evaluated under investigation. HD-2009 which is susceptible to waterlogging gave poor performance in terms of growth parameters, biochemical behavior and traits conferring higher yield under waterlogging conditions at ear head emergence stage in sodic soil as compared to HD-2851, KRL-3-4 and KRL-99 wheat varieties. KRL-99 (1.80g yield plant -1 ) gave best results followed KRL-3-4 (1.37g yield plant -1 ) by under waterlogged conditions at ear head emergence stage in sodic soil.

U.P.) throughout Rabi, 2011-12, on sixty four genotypes with four checks varieties (Vardan, Ashirwad, Kranti, and Maya) in Augmented Block Design. Information obtained by this method helps in direct and indirect selection for genetic improvement of yield. Results revealed that the seed yield plant -1 showed extremely vital and positive correlational statistics with length of main flower cluster, secondary branches plant -1 , primary branches plant -1 , plant height and siliquae on main flower cluster whereas non-significant positive correlation with remaining characters. Path analysis disclosed that characters viz., seed yield exhibited the highest positive direct impact on length of main flower cluster followed by primary branches plant -1 , secondary branches plant -1 and plant height. Considering each, the correlation co-efficients and path co-efficients along, length of main flower cluster, number of primary & secondary branches plant -1 and plant height emerged as vital elements of seed yield which should be given due importance during indirect selection criteria.

A Contracted socket is a complication of an Anophthalmic socket which results in the inability to support prosthesis. Contracted socket defines absence of functional eyeball from orbit. In most of cases, its presence take a lot on person's confidence and make oneself very difficult to come out of psychological trauma and stress associated with it. Rehabilitation of these patients is of utmost importance to provide positivity and self confidence in these scenarios. Artificial Eye (Customized Ocular Prosthesis) acceptance is dependent on individual persona and multiple sitting approaches to satisfy the individual need. There are occasions to modify the socket by surgical intervention to fit the artificial prosthesis. This article was written to create basic understanding of artificial eye and its various steps of manufacturing and dispensing.

The progression of innovation and technology and ease of inter-connectivity among networks has allowed us to evolve towards one of the promising areas, the Internet of Vehicles. Nowadays, modern vehicles are connected to a range of networks, including intra-vehicle networks and external networks. However, a primary challenge in the automotive industry is to make the vehicle safe and reliable; particularly with the loopholes in the existing traditional protocols, cyberattacks on the vehicle network are rising drastically. Practically every vehicle uses the universal Controller Area Network (CAN) bus protocol for the communication between electronic control units to transmit key vehicle functionality and messages related to driver safety. The CAN bus system, although its critical significance, lacks the key feature of any protocol authentication and authorization. Resulting in compromises of CAN bus security leads to serious issues to both car and driver safety. This paper discusses the security issues of the CAN bus protocol and proposes an Intrusion Detection System (IDS) that detects known attacks on in-vehicle networks. Multiple Artificial Intelligence (AI) algorithms are employed to provide recognition of known potential cyber-attacks based on messages, timestamps, and data packets traveling through the CAN. The main objective of this paper is to accurately detect cyberattacks by considering time-series features and attack frequency. The majority of the evaluated AI algorithms, when considering attack frequency, correctly identify known attacks with remarkable accuracy of more than 99%. However, these models achieve approximately 92% to 97% accuracy when timestamps are not taken into account. Long Short Term Memory (LSTM), Xgboost, and SVC have proved to the well-performing classifiers.