A Survey on Reading Habit of Library Users during COVID-19 Lockdown

E-Libraries has become more relevant in present situation of COVID-19 pandemic as it has caused an international lockdown in the world and India. Causing majority of the citizens to stay at home. The survey was conducted to study the reading habits of various library users (volunteers) during this situation. Besides the reading habit, the survey also collected the data for the various activities carried out by users at home. Main finding of the survey is that the users had taken keen interest to switch over to reading eBooks and 70% of student users and 53% of faculty users are reading more e-content especially books/magazines/research papers. Besides the extensive reading habit, the survey also discloses the greater involvement of users for learning/leisure/hobby activities at home. Student users have also reported spending more quality life with family members at home. Above all, the survey disclosed the reading of books as the main activity of the users during lockdown. This finding will inspire the organizations for establishing scalable and secure elibrary Infrastructure and for focusing on acquiring more eBooks for the eLibrary and provide better services to their users during situations like that of COVID-19

DEVELOPMENT OF AN ACCURATE SEIZURE DETECTION SYSTEM USING RANDOM FOREST CLASSIFIER WITH ICA BASED ARTIFACT REMOVAL ON EEG DATA

Abstract The creation of a reliable artifact removal and precise epileptic seizure identification system using Seina Scalp EEG data and cutting-edge machine learning techniques is presented in this paper. Random Forest classifier used for seizure classification, and independent component analysis (ICA) is used for artifact removal. Various artifacts, such as eye blinks, muscular activity, and environmental noise, are successfully recognized and removed from the EEG signals using ICA-based artifact removal, increasing the accuracy of the analysis that comes after. A precise distinction between seizure and non-seizure segments is made possible by the Random Forest Classifier, which was created expressly to capture the spatial and temporal patterns associated with epileptic seizures. Experimental evaluation of the Seina Scalp EEG Data demonstrates the excellent accuracy of our approach, achieving a 96% seizure identification rate A potential strategy for improving the accuracy and clinical utility of EEG-based epilepsy diagnosis is the merging of modern signal processing methods and deep learning algorithms

FRAND Licensing and Standards-Essential Patents: Concocting for Impending Technologies

Engineering of innumerable advancement in telecommunications placed India at a plinth of one of the largest telecommunication markets. In essence, most of these ingenuities pivot around a strong information, communication technology (“ITC”) platform; therefore, at the juncture of business and innovation Intellectual Property Rights (“IPR”) has a perilous role to play. Specifically, the success of India’s national development aspirations will depend on a court system and the competition Commission of India (“CCI”) to set enforcement standards and guidelines across the Intellectual Property Rights (“IPR”) regime associated with those initiatives. In this section we review decisions by Indian courts to explore emergence of any trends or standards of review.  Specifically, this paper explores how Indian courts have approached the Fair Reasonable and Non-Discriminatory (“FRAND”) terms to adjudicate disputes arising from standard-essential patents (“SEPs”). Further, the paper compares and contrasts court decisions on disputes arising from SEP licensing under FRAND terms across various international jurisdictions to set a benchmark for considerations by Indian legal experts. The work outlines the multidimensional nature of IPR in relation to licensing SEPs which presents not only legal issues but also business, technology and associated government policy issues

Network Intrusion Detection System: Classification, Techniques and Datasets to Implement

The Network Intrusion Detection System (NIDS) is a useful security utility that helps to prevent unauthorized and unwanted access to network resources by observing the network traffic and identify the records as either normal or abnormal. In this paper, compare three algorithms for network intrusion detection SVM, KNN and Decision Tree over Dos, Normal, R2L and U2R attacks. The features of SVM dataset are the decline for each type of attacks using correlation-based selection feature method. Then with the reduced feature set, discriminant analysis has done for the classification of different records. Comparison with other techniques shows that modified approach provides good classification rate for Normal, Dos, R2L (Remote-to-Local) and U2R (User-to-Root) attacks. A NIDS can be a software or piece of hardware. Many NIDS tools will store event or log of the event at a later date or will combine events with other data to make decisions about damage control or regarding policies. This paper shows the comparison of the different types of attacks that can be detected in a simulated core network environment. The different types of attacks are normal, DoS, Probe attacks, R2L and U2R attacks. The proposed method is implemented by the Python (Anaconda Navigator) and R programming software and tested on NSL-KDD dataset

Evaluation of masticatory efficiency using Bite Force Measurement in treated mandibular fractures with miniplates.

Maxillofacial injuries are routinely encountered in our practice and can lead to severe disfigurement and alter one\u27s facial form. Facial injuries can also result as a serious blow to one’s self esteem and psychosocial functioning, as there is a great emphasis on one’s appearance in the society.As a result, maxillofacial injuries require prompt and expert therapy to return to their normal shape and function. Road traffic accidents (RTA) are the most frequent cause of maxillofacial injuries in developing nations like India, followed by interpersonal disputes, unintentional falls, sports injuries, and industrial accidents.

Incidence And Factors Associated With Caesarean Section In Primigravida Women: A Retrospective Cohort Study

Aim: Current study was conducted to determine the incidence and factors associated with caesarean sections in primigravida.Methods: This retrospective study was conducted in the Department of Obstetrics and Gynaecology at a tertiary care govt hospital from June 2021 to May 2022. A total of 2345 primigravida patients visited the hospital for delivery. Out of these, 361 underwent Caesarean Section (CS) deliveries after 28 weeks of gestation. This study focused specifically on the 361 primigravida patients who underwent either emergency or elective primary CS. Clinical data of the patients were collected from the medical records. Results: Total number of primigravida CS were 361 (15.39%) of which emergency CS accounted for 92.0% (332 cases). Majority (79.2%) of the patients were between 21 and 30 years old. The analysis of body mass index (BMI) and period of gestation (POG) in relation to the type of CS revealed no statistically significant difference. Non-progress of labor (NPOL) was commonest indication of CS at 24.1% (87 cases) followed by Foetal distress 21,7% (78 cases), malpresentation15.8% (57 cases) and failed induction at 13.3% (48 cases). Significant obstetric risk factors in our study were GDM, hypothyroidism and obesity. GDM was more common in our population (24.3%). The analysis showed no significant association of GDM, Hypertension, Hypothyroidism , Covid 19 infection, IUGR, Thick MSL and Twin pregnancy with emergency LSCS. Anaemia, PPROM and Preeclampsia showed a high propensity for Emergency LSCS (Large OR). Breech presentation and post-IVF pregnancies were found to be significantly associated with elective LSCS, while other obstetric risk factors did not show statistically significant associations. Conclusion: Caesarean sections are absolutely critical and can be lifesaving in certain situations where vaginal deliveries would pose hazard and reduce both maternal and neonatal mortality and morbidity, so health care infrastructure should must ensure timely access to those who need them. Contrarily, needless caesarean sections run the risk of endangering the lives and health of expectant mothers and their children. As majority of these (92℅ of these) were only performed as part of emergency protocol, it reflects that if strict clinical and ethical guidelines are adhered to, the rate of caesarean section could be well controlled and optimal.Improving prenatal screening programs, educating patients on healthy lifestyle as well the benefits and low risk factors for normal vaginal delivery can reduce the rising caesarean section rates and in turn enhance the maternal and neonatal outcomes as well as alleviate the financial burden on healthcare system

A Study on Google Classroom for Mobile Edification at University level by Using AHP Model for Initial Perceptions – A Case Study of Sankalchand Patel University

In India, many online teaching platforms are being used in universities, colleges, and schools at all levels in the context of COVID-19. This research provides an online teaching platform evaluation system in order to systematically investigate the elements that influence the selection of online teaching platforms. Following a review of a series of factors that have significant influences on the selection of online teaching platforms, eight major factors are identified. Based on the Analytic Hierarchy Process, a hierarchical structure model for online teaching platform selection is constructed. Based on the questionnaire, the rank was the same with both methods for the most preferred question and the least important question, which were derived from Performance Expectancy (PE) and Use Behaviour, respectively (UB). These findings revealed that both techniques produced the same rank for the five likert scale alternatives, with "Agree" being the most important and "Strongly disagree" being the least important. In specifically, the weights of the indicators are calculated and evaluated for each layer in order to achieve the overall ranking and, as a result, the optimal scheme. The following is the order of priority for assessment indicators of online teaching platforms, according to the findings: Google Classroom is useful in this course since it is simple to use and has all of the materials that are required to participate in Google Classroom (internet, Smartphone, laptop, etc.)

Linking the UN SDGs and African Agenda 2063: Global goals and local priorities for Africa

The UN 2030 Agenda is a global agenda which brings nations together to address global challenges for sustainable development. It is increasingly expected for bilateral and multilateral development projects and programmes in sub-Saharan Africa to address the Sustainable Development Goals (SDGs). However, Africa's agency in steering sustainable development priorities, notably by proposing its own development agenda and achievements’ visions such as those contained in the African Agenda 2063 (AA2063), must be better recognised. This paper aims to establish converging links between the SDGs and AA2063. The authors used a structured process to identify and ‘map’ commonalities between all SDG and AA2063 targets. This process involved reviewing 32,617 possible connections between the 169 SDG Targets and 193 Agenda 2063 Targets. Key results identified 4,434 (14%) connections and three approaches for selecting overlapping areas of action: based on strength of connections, number of connections, and a combination of both. By comparing and establishing areas of overlap between the two agendas a discussion around converging and diverging priorities is held, which can in turn inform project design and monitoring and allow development initiatives to consider how they connect with both agendas. The findings could facilitate funders, policy makers and practitioners to leverage multiple benefits through a targeted approach to address both Agendas effectively

Cost-effectiveness of public-health policy options in the presence of pretreatment NNRTI drug resistance in sub-Saharan Africa: a modelling study

BACKGROUND: There is concern over increasing prevalence of non-nucleoside reverse-transcriptase inhibitor (NNRTI) resistance in people initiating antiretroviral therapy (ART) in low-income and middle-income countries. We assessed the effectiveness and cost-effectiveness of alternative public health responses in countries in sub-Saharan Africa where the prevalence of pretreatment drug resistance to NNRTIs is high. METHODS: The HIV Synthesis Model is an individual-based simulation model of sexual HIV transmission, progression, and the effect of ART in adults, which is based on extensive published data sources and considers specific drugs and resistance mutations. We used this model to generate multiple setting scenarios mimicking those in sub-Saharan Africa and considered the prevalence of pretreatment NNRTI drug resistance in 2017. We then compared effectiveness and cost-effectiveness of alternative policy options. We took a 20 year time horizon, used a cost effectiveness threshold of US$500 per DALY averted, and discounted DALYs and costs at 3% per year. FINDINGS: A transition to use of a dolutegravir as a first-line regimen in all new ART initiators is the option predicted to produce the most health benefits, resulting in a reduction of about 1 death per year per 100 people on ART over the next 20 years in a situation in which more than 10% of ART initiators have NNRTI resistance. The negative effect on population health of postponing the transition to dolutegravir increases substantially with higher prevalence of HIV drug resistance to NNRTI in ART initiators. Because of the reduced risk of resistance acquisition with dolutegravir-based regimens and reduced use of expensive second-line boosted protease inhibitor regimens, this policy option is also predicted to lead to a reduction of overall programme cost. INTERPRETATION: A future transition from first-line regimens containing efavirenz to regimens containing dolutegravir formulations in adult ART initiators is predicted to be effective and cost-effective in low-income settings in sub-Saharan Africa at any prevalence of pre-ART NNRTI resistance. The urgency of the transition will depend largely on the country-specific prevalence of NNRTI resistance. FUNDING: Bill & Melinda Gates Foundation, World Health Organization