Influence of journals indexed from a country on its research output: An empirical investigation

Scientific journals are currently the primary medium used by researchers to report their research findings. The transformation of print journals into e-journals has simplified the process of submissions to journals and also their access has become wider. Journals are usually published by commercial publishers, learned societies as well as Universities. There are different number of journals published from different countries. This paper attempts to explore whether the number of journals published from a country influences its research output. Scopus master journal list is analysed to identify journals published from 50 selected countries with significant volume of research output. The following relationship are analysed: (a) number of journals from a country and its research output, (b) growth rate of journals and research output for different countries, (c) global share of journals and research output for different countries, and (d) subject area-wise number of journals and research output in that subject area for different countries. Factors like journal packing density are also analysed. The results obtained show that for majority of the countries, the number of journals is positively correlated to their research output volume, though some other factors also play a role in growth of research output. The study at the end presents a discussion of the analytical outcomes and provides useful suggestions on policy perspectives for different countries.Comment: 6 figures and 4 table

Heterosis study in Okra [Abelmoschus esculentus (L.) Moench] genotypes for pod yield attributes

A study was conducted at Vegetable Research Farm, Department of Horticulture, Institute of Agriculture Sciences, Banaras Hindu University, Varanasi during Spring-Summer and Rainy season of 2012 and 2013 using 12 diverse parental lines of okra and their 66 F1 hybrids (through diallel cross-excluding reciprocals) with the objective to measure the extent of heterosis over better parent and standard commercial check varieties for the purpose of judging the extent up to which heterosis can be exploited in commercial okra breeding. The extent of heterosis for five best crosses over better parent and check (48.32 % to 82.42 % and 7.13 % to 35.66 %, respectively) for yield per hectare suggested the great scope of realizing higher yield in okra through heterosis breeding. Other economic traits also recorded moderate to high level of heterosis over the better parents. The cross combination IC -282280×EC – 329380showed high heterosis over better parent and standard check for pod yield (82.42 % and 35.66 %), number of pods per plant (62.82 % and 48.54 %) and respectively. This particular cross combination eventually resulted the height magnitude of heterobeltiosis and standard heterosis for the most of the desirable growth parameters as well as yield attributing characters which may be taken for further breeding programme

India's rank and global share in scientific research -- how publication counting method and subject selection can vary the outcomes

During the last two decades, India has emerged as a major knowledge producer in the world, however different reports put it at different ranks, varying from 3rd to 9th places. The recent commissioned study reports of Department of Science and Technology (DST) done by Elsevier and Clarivate Analytics, rank India at 5thand 9th places, respectively. On the other hand, an independent report by National Science Foundation (NSF) of United States (US), ranks India at 3rd place on research output in Science and Engineering area. Interestingly, both, the Elsevier and the NSF reports use Scopus data, and yet surprisingly their outcomes are different. This article, therefore, attempts to investigate as to how the use of same database can still produce different outcomes, due to differences in methodological approaches. The publication counting method used and the subject selection approach are the two main exogenous factors identified to cause these variations. The implications of the analytical outcomes are discussed with special focus on policy perspectives

Laparoscopic Cholecystectomy Conversion Rates Two Decades Later

Male patients greater than 50 years of age and cases performed by low-volume surgeons were found to have a higher rate of conversion to open procedures

Congenital atrichia with papular lesions

Congenital atrichia with papular lesions is a rare, autosomal recessive and irreversible form of total alopecia of the body hair characterized by hair loss soon after birth and the development of keratinfilled cysts or horny papules over extensive areas of the body. The condition is associated with a mutation of the human hairless gene on chromosome region 8p12. We report a 1-year-old boy presenting with the absence of scalp and body hair since birth. On examination, he had complete absence of hair on the scalp, eyebrows, and eyelashes. Multiple, discrete, pearly-to-skin-colored papules of 1-3mm in size were present over the scalp. The skin biopsy from a scalp papule revealed normal overlying epidermis with multiple keratin cysts and hypoplastic hair follicles in the upper dermis

Speaker verification using Mel Frequency Cepstral Coefficient and Artificial Neural Network

Speaker recognition is defined as to make sure that if the person is the same person he claims to be or not. This technique is one of the biometric recognition techniques useful in all most all areas where security is a concern. Speaker recognition can be divided into speaker identification and speaker verification. Speaker identification decides if a speaker is a specific person or is from a group. In speaker verification, a person makes an identity claim (e.g., by entering a pin number with the debit/credit card at ATM). There are two main stages in this technique, feature extraction and feature matching. Feature extraction is the process in which we extract some useful data which can later to be used to represent the speaker. Feature matching involves identification of the unknown speaker by comparing the feature extracted from the voice with the enrolled voices of known speakers. In this project we have extracted the MFCCs of the speech signal, which involve recording of the speech signal, windowing, framing, thresholding, STDFT (short time discrete fourier transform) calculation and then passing through mel frequency filter. Extracted features are then matched with the stored templates. Algorithms used in feature extraction are calculation of real cepstral coefficient calculation and mel frequency cepstral coefficient calculation. For feature matching we used multi-layer perceptron method in artificial neural network