Millets (including sorghum) are known to be highly nutritious besides having a low carbon footprint and the ability to survive in high temperatures with minimal water. Millets are widely recognised as having a low Glycaemic Index (GI) helping to manage diabetes. This systematic review and meta-analyzes across the different types of millets and different forms of processing/cooking collated all evidences. Of the 65 studies that were collected globally, 39 studies with 111 observations were used to analyze GI outcomes and 56 studies were used to analyze fasting, post-prandial glucose level, insulin index and HbA1c outcomes in a meta-analysis. It is evident from the descriptive statistics that the mean GI of millets is 52.7 ± 10.3, which is about 36% lower than in typical staples of milled rice (71.7 ± 14.4) and refined wheat (74.2 ± 14.9). The descriptive, meta and regression analyses revealed that Job's tears, fonio, foxtail, barnyard, and teff were the millets with low mean GI (<55) that are more effective (35–79%) in reducing dietary GI than the control samples. Millets with intermediate GI (55–69) are pearl millet, finger millet, kodo millet, little millet, and sorghum which have a 13–35% lower GI than the control with high GI (>69). A meta-analysis also showed that all millets had significantly (p < 0.01) lower GI than white rice, refined wheat, standard glucose or white wheat bread except little millet which had inconsistent data. Long term millet consumption lowered fasting and post-prandial blood glucose levels significantly (p < 0.01) by 12 and 15%, respectively, in diabetic subjects. There was a significant reduction in HbA1c level (from 6.65 ± 0.4 to 5.67 ± 0.4%) among pre-diabetic individuals (p < 0.01) who consumed millets for a long period. Minimally processed millets were 30% more effective in lowering GI of a meal compared to milled rice and refined wheat. In conclusion, millets can be beneficial in managing and reducing the risk of developing diabetes and could therefore be used to design appropriate meals for diabetic and pre-diabetic subjects as well as for non-diabetic people for a preventive approach.

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The author reports the results of an empirical study on Occupational Stress and Psychological Wellbeing on the Faculty of Higher Education, and its effect on Virtual Teaching and performance. The data gathered using google forms from the Engineering and Management faculty in and around Hyderabad Higher educational institutes. The research instrument,  a structured questionnaire, completed by 400 faculty members of the Engineering and Management faculty of Higher Educational Institutes in and around Hyderabad. The data was gathered using a 5-point Likert Type scale to measure the faculty performance, occupational stress, and virtual teaching factors, whereas the psychological well-being of the faculty is measured using a 7-point scale. The response from the 7-point psychological well-being scale was converted into a 5-point Likert-type scale using linear transformations. The research instrument maintained its reliability and internal consistency as assessed by Cronbach Alpha (0.83). The logistic regression analysis indicated autonomy, the purpose of life the psychological well-being factors, and work load, remote working, role conflict are statistically significant and influencing the faculty performance and virtual teaching.

The authors of this article attempted combining the two methodologies of gamification and resource pooling with a view to derive the maximum productivity from the organization drawing certain significant commonalities. Another biggest motive behind the authors for combining these two techniques is the fact that eCommerce is a business vertical or a market place where people from all walks of life participate in online purchases. eCommerce is not a market place where it is restricted to one particular community, region, age, colour etc., So to interact, involve and conduct the business operations with an inclusive mindset, the authors thought that it would be appropriate to gamify and pooling the resources such that there would be a perfect blend of resources with utmost motivation to serve all the stakeholders, irrespective of their age, gender, community, region, economic status, in ecommerce. It turned out to be a practical solution as it proved to be promoting an atmosphere that fosters friendship and loyalty, and these close-knit relationships motivate employees; align them to work much harder, cooperate and be supportive to each other. This is possible because every individual possesses diverse talents, weaknesses, communication skills, strengths, habits, and hence it is optimally balanced out. Gamification is a method to enhance employee engagement, behavioral change and motivation. Application of gamification is not limited to eCommerce business models, but can be applied to various other business models in the sectors like education, research, healthcare etc. So also, the human resource pooling is building and grouping of human resources for best use to improve the operational efficiency and reduce the costs. The human resource pooling can happen during fine tuning of a cultural fit, organization mergers, change in organization structure, technological changes and on acquiring new technology. In this study we have considered a group of 120 employees who were further divided to 6 functional groups, having 20 employees in each functional

In this empirical research we are reporting the results of a survey carried out in Healthcare Industry in the Metro city of Hyderabad, whether the performance appraisal management system is effected by the independent factors performance management, improved employee performance and impact of performance appraisal system on employee performance. The authors surveyed 750 staff working in various healthcare centres including hospitals, training centres consisting of 435 men and 315 women employees, to evaluate the how the said factors effect the performance management system in healthcare industry. The reliability statistics Cronbach Alpha, Kaiser-Meyer-Olkin Measure of Sampling Adequacy and Bartlett's tests of sample adequacy, principal component analysis and multiple linear regression analysis carried out. The Cronbach alpha measured at for performance management 0.870 factors for improvement of employee performance 0.776 and factors for Impact of performance appraisal system on organization is 0.742. The KMO-Bartlett tests reveal a strong relationship among the study variables and Bartlett's test of Sphericity is significant (P<0.001) for all the three factors indicating the correlation matrix is not an identify matrix. The multiple regression analysis reveals the three factors significantly influencing the performance management system in healthcare industry in the Metro of Hyderabad.

Technology-based teaching and learning are always an innovative technique that absorbs many researchers’ attention throughout the words. Considering the vital role of online learning, this study aimed to examine the effects of e-learning on Iranian EFL learners’ reading comprehension and reading motivation. To this end, the OQPT was given to 101 Iranian EFL learners, and 60 of them who were at the intermediate level were selected as the participants of the study. Then, they were randomly divided into two groups: one experimental group (EG) (n = 30) and one control group (CG) (n = 30). After that, a reading comprehension test and a reading motivation questionnaire were administered to both groups as the pretests of the study. After pretesting, the participants of the EG received the treatment through e-learning. Eight lessons of Connect Book 4 were taught to the experimental participants online. On the other side, the participants of the CG were taught traditionally, through a face-to-face fashion. In the last session, a reading comprehension test and a reading motivation questionnaire were again given to both groups. The independent-samples t-test revealed that the EG outflanked the CG on the posttests. The e-learning instruction aided Iranian EFL learners in enhancing their reading comprehension and reading motivation. Regarding the findings of this study, some implications are mentioned for learners, teachers, and curriculum designers.

Anomaly-based network intrusion detection plays a vital role in protecting networks against malicious activities. In recent years, data mining techniques have gained importance in addressing security issues in network. Intrusion detection systems (IDS) aim to identify intrusions with a low false alarm rate and a high detection rate. Although classification-based data mining techniques are popular, they are not effective to detect unknown attacks. Unsupervised learning methods have been given a closer look for network IDS, which are insignificant to detect dynamic intrusion activities. The recent contributions in literature focus on machine learning techniques to build anomaly-based intrusion detection systems, which extract the knowledge from training phase. Though existing intrusion detection techniques address the latest types of attacks like DoS, Probe, U2R, and R2L, reducing false alarm rate is a challenging issue. Most network IDS depend on the deployed environment. Hence, developing a system which is independent of the deployed environment with fast and appropriate feature selection method is a challenging issue. The exponential growth of zero-day attacks emphasizing the need of security mechanisms which can accurately detect previously unknown attacks is another challenging task. In this work, an attempt is made to develop generic meta-heuristic scale for both known and unknown attacks with a high detection rate and low false alarm rate by adopting efficient feature optimization techniques.