Interpreting BOLD: towards a dialogue between cognitive and cellular neuroscience

Cognitive neuroscience depends on the use of blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) to probe brain function. Although commonly used as a surrogate measure of neuronal activity, BOLD signals actually reflect changes in brain blood oxygenation. Understanding the mechanisms linking neuronal activity to vascular perfusion is, therefore, critical in interpreting BOLD. Advances in cellular neuroscience demonstrating differences in this neurovascular relationship in different brain regions, conditions or pathologies are often not accounted for when interpreting BOLD. Meanwhile, within cognitive neuroscience, increasing use of high magnetic field strengths and the development of model-based tasks and analyses have broadened the capability of BOLD signals to inform us about the underlying neuronal activity, but these methods are less well understood by cellular neuroscientists. In 2016, a Royal Society Theo Murphy Meeting brought scientists from the two communities together to discuss these issues. Here we consolidate the main conclusions arising from that meeting. We discuss areas of consensus about what BOLD fMRI can tell us about underlying neuronal activity, and how advanced modelling techniques have improved our ability to use and interpret BOLD. We also highlight areas of controversy in understanding BOLD and suggest research directions required to resolve these issues

The Problems and Prospects of Women Entrepreneurs

Women are one of the most relevant untapped resources if you talk about entrepreneurship. Femaleentrepreneurship is gaining attention and importance in light of the evidence of the importance of new businesscreation for economic growth and development. Entrepreneurship refers to the act of setting up a new businessso as to take advantages from new opportunities. Entrepreneurs are responsible for shaping the economy andthey help in creation of new wealth and new jobs by inventing new products, process and services. We allunderstand that economic development of the today’s woman is crucial for economic development of any countryspecially a country like India. The women today have emerged as a key player in economic development of thenations. However this transformation of society is far from over and the women entrepreneurs not only facedifficulties while starting up an enterprise but also during the running phase. Globally, they have become a keyplayer in sustaining both social development and economic growth. There are a number of socio-economichurdles faced by the women while they attempt to venture into setting up and running their own enterprises. Inthis paper, an attempt has been made to study the opportunities and challenges related with entrepreneurship thatthe woman of our country faces in the present times.&nbsp

Socio-Economic Profile of Women Entrepreneurs

Pandit Jawaharlal Lal Nehru has remarked “When women move forward, the family moves, thevillage moves and then ultimately the Nation moves forward.” Women are one of the most relevant untappedresources if you talk about entrepreneurship. Female entrepreneurship is gaining attention and importance inlight of the evidence of the importance of new business creation for economic growth and development.Entrepreneurship refers to the act of setting up a new business so as to take advantages from new opportunitiesEntrepreneurs are responsible for shaping the economy and they help in creation of new wealth and new jobs byinventing new products, process and services. We all understand that economic development of the today’swoman is crucial for economic development of any country specially a country like India. The dependency onservice sector has created many entrepreneurial opportunities for women that they can utilize to enhance theirsocial standing and reputation. In this paper, an attempt has been made to study the socio – economic profilecharacteristics related with entrepreneurship that the woman of our country in the present times. Muchknowledge is not found about the economic relevance of women in entrepreneurship programs and the effect ofthese programs on society and economy

Plant Disease Detection using Deep Convolution Network

The global rise in population has led to a shortage of raw materials and food supplies. The agricultural sector has become the primary and most vital source to overcome this particular constraint. However, the industry itself is facing the challenge of pests and various crop diseases. Battling this has been the significant focus of the sector for decades. Still, due to  the technology gap that existed earlier, there existed a constraint on identifying the diseased crops on a massive scale. Nevertheless, today, with the improvement of technologies such as drones, IoT devices, and higher processing speeds combined with data analysis and machine learning, the problem of identification can be resolved quickly. This paper aims to provide a brief description of existing solutions that have been published and focuses on the more efficient machine learning model based on conventional neural networks (CNN) that we have developed. This machinelearning model can be deployed on IoT devices, mobile phones, and drones and cameras that farmers can utilize to identify the diseased crops on a massive scale and take the necessary precautions not to let the disease spread and affect the supply produced

Effectiveness of 0.125% Bupivacaine versus 0.125% Ropivacaine in Epidural Labour Analgesia- A Randomised Clinical Study

Introduction: Epidurally administered local anaesthetics provide most effective analgesia during labour process. Among the available local anaesthetics, bupivacaine and ropivacaine are the most commonly used drugs in concentrations ranging from 0.0625% to 0.125% and 0.08% to 0.125%, respectively. Both these drugs are weak bases, highly protein-bound, highly lipid soluble, and have a pKa of 8.1, low unionised fraction, thus, having a slightly longer time for onset of action but with a longer duration of action and have less transfer across the placenta. Hence, they are ideal drugs for use in labour analgesia. Aim: To compare the effectiveness of programmed intermittent bolus of 0.125% bupivacaine vs 0.125% ropivacaine in low volumes in full term primigravidas for epidural labour analgesia. Materials and Methods: This randomised clinical study was conducetd at PES Institute of Medical Sciences and Research, Kuppam, Andhra Pradesh, India, between June 2020 and December 2021 among 80 full-term primi parturients requiring normal vaginal delivery. They were randomly divided into two groups of 40 each. Group B received 10 mL of 0.125% bupivacaine and group R received 10 mL of 0.125% ropivacaine as initial bolus dose. Repeat doses of 5 mL was given every 60 minutes or when the patient had Visual Analogue Score (VAS) score >4 with a maximum dose of 10 mL/hr with a 20 minute interval between two doses. Parameters assessed were onset, duration, level and quality of analgesia, motor blockade, number of epidural top ups, total volume of drug consumed, mode of delivery, duration of labour, APGAR score, haemodynamics, patient satisfaction and complications. Data was entered in Microsoft Excel 2010 version and analysed using Statistical Package for Social Sciences (SPSS) version 20.0. Results: Both drugs were equally effective in terms of analgesia, maternal and foetal outcomes. Bupivacaine had a faster onset of action (7.075±0.916 min) compared to ropivacaine (8.225±0.891 min) (p-value=0.001). Ropivacaine had a shorter duration of action (43.1±2.30 min vs 47.9±4.16 min in group B) (p-value=0.0001), requiring more top-up doses (5.2±0.46 vs 4.77±0.61 in group B) (p-value=0.0007), and more total volume of drug (38.5±3.08 mL vs 35.5±4 mL in group B) (p-value=0.002). It also caused lesser motor blockade (Bromage score of 1 in 1 parturient vs 8 parturients in group B) (p-value=0.0129) and better overall maternal satisfaction score (excellent) in 30 parturients vs 25 parturients in group B. APGAR scores at 1 minute and 5 minutes were comparable between the two groups. Mean heart rates, mean blood pressures were also comparable between the two groups. There were no significant adverse effects in either groups. Conclusion: By providing minimal motor blockade and adequate analgesia 0.125% ropivacaine allows parturients to go through the labour process with excellent maternal satisfaction and minimal adverse effects compared to 0.125% bupivacaine

Global, regional, and national prevalence of adult overweight and obesity, 1990–2021, with forecasts to 2050: a forecasting study for the Global Burden of Disease Study 2021

Background: Overweight and obesity is a global epidemic. Forecasting future trajectories of the epidemic is crucial for providing an evidence base for policy change. In this study, we examine the historical trends of the global, regional, and national prevalence of adult overweight and obesity from 1990 to 2021 and forecast the future trajectories to 2050. Methods: Leveraging established methodology from the Global Burden of Diseases, Injuries, and Risk Factors Study, we estimated the prevalence of overweight and obesity among individuals aged 25 years and older by age and sex for 204 countries and territories from 1990 to 2050. Retrospective and current prevalence trends were derived based on both self-reported and measured anthropometric data extracted from 1350 unique sources, which include survey microdata and reports, as well as published literature. Specific adjustment was applied to correct for self-report bias. Spatiotemporal Gaussian process regression models were used to synthesise data, leveraging both spatial and temporal correlation in epidemiological trends, to optimise the comparability of results across time and geographies. To generate forecast estimates, we used forecasts of the Socio-demographic Index and temporal correlation patterns presented as annualised rate of change to inform future trajectories. We considered a reference scenario assuming the continuation of historical trends. Findings: Rates of overweight and obesity increased at the global and regional levels, and in all nations, between 1990 and 2021. In 2021, an estimated 1·00 billion (95% uncertainty interval [UI] 0·989–1·01) adult males and 1·11 billion (1·10–1·12) adult females had overweight and obesity. China had the largest population of adults with overweight and obesity (402 million [397–407] individuals), followed by India (180 million [167–194]) and the USA (172 million [169–174]). The highest age-standardised prevalence of overweight and obesity was observed in countries in Oceania and north Africa and the Middle East, with many of these countries reporting prevalence of more than 80% in adults. Compared with 1990, the global prevalence of obesity had increased by 155·1% (149·8–160·3) in males and 104·9% (95% UI 100·9–108·8) in females. The most rapid rise in obesity prevalence was observed in the north Africa and the Middle East super-region, where age-standardised prevalence rates in males more than tripled and in females more than doubled. Assuming the continuation of historical trends, by 2050, we forecast that the total number of adults living with overweight and obesity will reach 3·80 billion (95% UI 3·39–4·04), over half of the likely global adult population at that time. While China, India, and the USA will continue to constitute a large proportion of the global population with overweight and obesity, the number in the sub-Saharan Africa super-region is forecasted to increase by 254·8% (234·4–269·5). In Nigeria specifically, the number of adults with overweight and obesity is forecasted to rise to 141 million (121–162) by 2050, making it the country with the fourth-largest population with overweight and obesity. Interpretation: No country to date has successfully curbed the rising rates of adult overweight and obesity. Without immediate and effective intervention, overweight and obesity will continue to increase globally. Particularly in Asia and Africa, driven by growing populations, the number of individuals with overweight and obesity is forecast to rise substantially. These regions will face a considerable increase in obesity-related disease burden. Merely acknowledging obesity as a global health issue would be negligent on the part of global health and public health practitioners; more aggressive and targeted measures are required to address this crisis, as obesity is one of the foremost avertible risks to health now and in the future and poses an unparalleled threat of premature disease and death at local, national, and global levels. Funding: Bill & Melinda Gates Foundation

Time Series Data Analysis using Machine Learning-(ML) Approach

Healthcare benefits related to continuous monitoring of human movement and physical activity can potentially reduce the risk of accidents associated with elderly living alone at home. Based on the literature review, it is found that many studies focus on human activity recognition and are still active towards achieving practical solutions to support the elderly care system. The proposed system has introduced a joint approach of machine learning and signal processing technology for the recognition of human\u27s physical movements using signal data generated by accelerometer sensors. The framework adopts the concept of DSP to select very descriptive feature sets and uses ML-based supervised learning techniques for effective classification. The simulation result demonstrates the efficiency of the proposed system regarding the prediction of human movement based on sensor signals