Search

India being the largest democracy of the world and being one of the fastest growing economy in the world is facing the problem of unemployment from a long period of time. The problem was worst during the post-independence era and after independence various schemes and necessary provisions are taken by the government to tackle this.The government has launched various self-employment as well as credit linked schemes to assist people in starting their own business. This paper attempts to examine the status of unemployment its causes, steps taken by the government regarding this along with suggesting measures to overcome this problem.

Oral and maxillofacial surgery (OMFS) is a specialty of dentistry dealing with the surgical aspects of head and neck. It is considered to be a bridge between medical and dental specialties. However, little is known regarding this field among the medical practitioners. Method: A survey was conducted among 200 health care professionals in KANPUR to check for awareness regarding the field of OMFS, and its scope in the medical field. Result: Most of the dental professionals were found to be more aware of range of work done in Oral and Maxillofacial Surgery, in contrast to medical professionals. The difference in perceived knowledge was not significant for nose fractures, cleft lip and/or palate, removal of wisdom tooth and temporomandibular joint problems. Most of the respondents referred cases to OMFS for mandibular, maxillary and zygoma fractures. OMFS was also preferred for dento-alveolar trauma, maxillary cysts, benign mandibular tumors, removal of wisdom tooth, orthognathic surgeries, TMJ problems and maxillofacial infections. There was a difference of opinion for others. Dental professionals preferred OMFS for biopsy of oral lesions, lump in the mouth, mandibular reconstruction and bone graft in mandible, while medical professionals referred less number of cases for these conditions. There were more referrals to OMFS from medical professionals’ side for dental implants, as compared to dental professionals. There were overall less number of referrals to OMFS for cancer of the mouth, removal of salivary glands, cleft lip and/or palate, and problems with facial appearance. Conclusion: The knowledge of health care professionals regarding specialty referrals in oro-facial conditions is average. Many health care professionals still associate our specialty mostly with intraoral conditions and tooth removal only. Health care professionals still lack information regarding the advances and new procedures being done in Oral and Maxillofacial Surgery, Dental Practitioners were more aware about the range of work done and referrals to OMFS than Medical Practitioners of all specialties

Recent research on the SARS-CoV-2 pandemic has exploded around the furin-cleavable polybasic insert PRRAR↓S, found within the spike protein. The insert and the receptor-binding domain, (RBD), are vital clues in the Sherlock Holmes-like investigation into the origin of the virus and in its zoonotic crossover. Based on comparative analysis of the whole genome and the sequence features of the insert and the RBD domain, the bat and the pangolin have been proposed as very likely intermediary hosts. In this study, using the various databases, in-house developed tools, sequence comparisons, structure-guided docking, and molecular dynamics simulations, we cautiously present a fresh, theoretical perspective on the SARS-CoV-2 virus activation and its intermediary host. They are a) the SARS-CoV-2 has not yet acquired a fully optimal furin binding site or this seemingly less optimal sequence, PRRARS, has been selected for survival; b) in structural models of furin complexed with peptides, PRRAR↓S binds less well and with distinct differences as compared to the all basic RRKRR↓S; c) these differences may be exploited for the design of virus-specific inhibitors; d) the novel polybasic insert of SARS-CoV-2 may be promiscuous enough to be cleaved by multiple enzymes of the human airway epithelium and tissues which may explain its unexpected broad tropism; e) the RBD domain of the feline coronavirus spike protein carries residues that are responsible for high-affinity binding of the SARS-CoV-2 to the ACE 2 receptor; f) en route zoonotic transfer, the virus may have passed through the domestic cat whose very human-like ACE2 receptor and furin may have played some role in optimizing the traits required for zoonotic transfer., Highlights • Polybasic insert of the SARS-CoV-2 spike protein is rare among several hundred proteins with a motif ‘RRARS’. • SARS CoV-2 shares furin-like site and RBD interface residues including hotspot sites, with some of the lethal form of Feline coronavirus spike protein and those from the healthy cats. • Polybasic sequence PRRARS binds less well to furin in structural models. • SARS-CoV-2 may have passed through the domestic cat during zoonotic transfer.

The stylization of pitch contour is a primary task in the speech prosody for the development of a linguistic model. The stylization of pitch contour is performed either by statistical learning or statistical analysis. The recent statistical learning models require a large amount of data for training purposes and rely on complex machine learning algorithms. Whereas, the statistical analysis methods perform stylization based on the shape of the contour and require further processing to capture the voice intonations of the speaker. The objective of this paper is to devise a low-complexity transcription algorithm for the stylization of pitch contour based on the voice intonation of a speaker. For this, we propose to use of pitch marks as a subset of points for the stylization of the pitch contour. The pitch marks are the instance of glottal closure in a speech waveform that captures characteristics of speech uttered by a speaker. The selected subset can interpolate the shape of the pitch contour and acts as a template to capture the intonation of a speaker’s voice, which can be used for designing applications in speech synthesis and speech morphing. The algorithm balances the quality of the stylized curve and its cost in terms of the number of data points used. We evaluate the performance of the proposed algorithm using the mean square error and the number of lines used for fitting the pitch contour. Furthermore, we perform a comparison with other existing stylization algorithms using the LibriSpeech ASR corpus.

The target of this inspection is exploring the influence of Medical Course training on satisfaction, loyalty, and Word-Of-Mouth (WOM) in Indian Medical Colleges context. A twenty-five items Questionnaire (CEQ) was distributed in Medical Colleges in Delhi. Demographic variables were gender, age, education level, preferred Source of Study, Hostel Inhabitant, Family income, Class Attendance, Personality Type and the distance between College and residence. Linear regression analysis was performed for this research. Responses were collected both through online and offline means. Results suggest that improving course experience of education influences its outcomes for the institute.

The nutritive quality of legumes is poor due to deficiency of certain amino acids, low protein and starch digestibility and presence of certain anti-nutritional factor. As a result, processing techniques are adopted to overcome these problems and increases the palatability of legumes. Malting is one of the simple and inexpensive traditional processing techniques that are widely accepted for achieving desirable changes in the composition of legumes. In view of the above aspects the aim of present work was to investigate the effect of malting on nutritional profile of alfalfa seeds and development of value added fermented products. The nutritional profile (moisture, ash, protein, fat, fibre, carbohydrate, calcium and iron content) of unmalted and malted alfalfa flours were analysed with standard protocols. Fermented products viz; Dhokla and Appe were developed by incorporating malted alfalfa flour (MAF) at 10%, 15% and 20% level and organoleptic evaluated by 5-point composite Score and 9-point hedonic scale. The study data revealed that malted alfalfa flour contain significantly increased content of protein (19.6%), fibre (29.1%), iron (39.9%) and calcium (93.9%) when compared to unmalted alfalfa flour at P≥0.05 level. Sensory evaluation showed that fermented products developed at 10% level of incorporation of malted alfalfa flour were highly acceptable and registered insignificant difference at P≤ 0.05 level when compared with their respective standard products. Thus, it can be concluded that the malted alfalfa seeds contain appreciable amount of nutrients that may be used in the formulation of fermented food products and advantageous in human health.

Counting the number of speakers in an audio sample can lead to innovative applications, such as a real-time ranking system. Researchers have studied advanced machine learning approaches for solving the speaker count problem. However, these solutions are not efficient in real-time environments, as it requires pre-processing of a finite set of data samples. Another approach for solving the problem is via unsupervised learning or by using audio processing techniques. The research in this category is limited and does not consider the large-scale open set environment. In this paper, we propose a distributed clustering approach to address the speaker count problem. The separability of the speaker is computed using statistical pitch parameters. The proposed solution uses multiple microphones available in smartphones in a large geographical area to capture and extract statistical pitch features from the audio samples. These features are shared between the nodes to estimate the number of speakers in the neighborhood. One of the major challenges is to reduce the error count that arises due to the proximity of the users and multiple microphones. We evaluate the algorithm’s performance using real smartphones in a multi-group arrangement by capturing parallel conversations between the users in both indoor and outdoor scenarios. The average error count distance is 1.667 in a multi-group scenario. The average error count distances in indoor environments are 16% which is better than in the outdoor environment.