Developing a Scale to Measure the Trend in Millet Farming and Attitude of Farmers towards Millet Cultivation

In the recent years concern for millets has been on the rise. Sources had shown that there is an existence of valid linkage between millets and poverty reduction. A study was designed to develop a scale to measure the current trend in millet farming and changing attitude of farmers towards millet cultivation. The study was conducted in Tiruvannamalai and Vellore Districts of Tamil Nadu. Twenty statements reflecting the changing trends towards millet farming were generated. Likert’s method was employed in the scale construction and the final scale comprising 10 statements was standardized

SEARCHING ANTIVIRAL DRUGS FOR EBOLA VIRUS FROM PHYTO-CONSTITUENTS OF AZADIRACHTA INDICA: APPLICATION OF MOLECULAR MODELING STUDIES

 ABSTRACTThe current objective of the study is to identify some naturally occurring product from Azadirachta indica and evaluate its binding activity against VP24 protein as Ebola virus target through in silico docking studies. Reported phytoconstituents of Azadirachta indica were prepared for docking evaluation using Brincidofovir as the standard. In silico docking studies were carried out using GLIDE (Grid-based Ligand Docking with Energetics) is a ligand binding program provided by Schrödinger. These results showed that all the selected phytoconstituents showed binding energy ranging between -7.95 kcal/mol to -1.54 kcal/mol when compared with that of the standard (-6.06 kcal/mol). Naturally occurring products Catechin, Epicatechin, Gallic acid and Nimbolide are potential than the standard brincidofovir but Azadirachtin, Margolonone, Mahmoodin, Isomargolonone, Gedunin, Margolone, Nimbidin and Nimbin have low binding affinity towards target when compared with the standard. These molecular docking analyses of phytoconstituents of Azadirachta indica could lead to the further development to identify the potent drugs for the treatment of Ebola virus. KEYWORDS: Azadirachta indica, VP42 protein, Ebola virus, in silico docking.  Â

Neuroenhancement: Enhancing brain and mind in health and in disease

AbstractHumans have long used cognitive enhancement methods to expand the proficiency and range of the various mental activities that they engage in, including writing to store and retrieve information, and computers that allow them to perform myriad activities that are now commonplace in the internet age. Neuroenhancement describes the use of neuroscience-based techniques for enhancing cognitive function by acting directly on the human brain and nervous system, altering its properties to increase performance. Cognitive neuroscience has now reached the point where it may begin to put theory derived from years of experimentation into practice. This special issue includes 16 articles that employ or examine a variety of neuroenhancement methods currently being developed to increase cognition in healthy people and in patients with neurological or psychiatric illness. This includes transcranial electromagnetic stimulation methods, such as transcranial direct current stimulation (tDCS) and transcranial magnetic stimulation (TMS), along with deep brain stimulation, neurofeedback, behavioral training techniques, and these and other techniques in conjunction with neuroimaging. These methods can be used to improve attention, perception, memory and other forms of cognition in healthy individuals, leading to better performance in many aspects of everyday life. They may also reduce the cost, duration and overall impact of brain and mental illness in patients with neurological and psychiatric illness. Potential disadvantages of these techniques are also discussed. Given that the benefits of neuroenhancement outweigh the potential costs, these methods could potentially reduce suffering and improve quality of life for everyone, while further increasing our knowledge about the mechanisms of human cognition

Healthcare professional’s guide to cardiopulmonary exercise testing

Cardiopulmonary exercise testing (CPEX) is a valuable clinical tool that has proven indications within the fields of cardiovascular, respiratory and pre-operative medical care. Validated uses include investigation of the underlying mechanism in patients with breathlessness, monitoring functional status in patients with known cardiovascular disease and pre-operative functional state assessment. An understanding of the underlying physiology of exercise, and the perturbations associated with pathological states, is essential for healthcare professionals to provide optimal patient care. Healthcare professionals may find performing CPEX to be daunting, yet this is often due to a lack of local expertise and guidance with testing. We outline the indications for CPEX within the clinical setting, present a typical protocol that is easy to implement, explain the key underlying physiological changes assessed by CPEX, and review the evidence behind its use in routine clinical practice. There is mounting evidence for the use of CPEX clinically, and an ever-growing utilisation of the test within research fields; a sound knowledge of CPEX is essential for healthcare professionals involved in routine patient care

Design, Synthesis, Characterization And Biological Evaluation Of Novel Flavone Derivatives: Molecular Docking Studies

In the past 60 years, antibiotics have been critical in the fight against infectious disease caused by bacteria and other microbes. However, disease-causing microbes that have become resistant to antibiotic drug therapy are an increasing public health problem. Another part of the problem is due to increasing use, and misuse, of existing antibiotics in human and veterinary medicine and in agriculture. Antimicrobial resistance is not a new problem but one that is becoming more dangerous; urgent and consolidated efforts are needed to avoid regressing to the pre-antibiotic era. Drug resistance is becoming more severe and many infections are no longer easily cured, leading to prolonged and expensive treatment and greater risk of death. Microbial development of resistance, as well as economic incentives, has resulted in research and development in the search for new antibiotics in order to maintain a pool of effective drugs at all times. While the development of resistant strains is inevitable, the slack ways that we administer and use antibiotics has greatly exacerbated the process (78). Among the various factors that have contributed to the current resurgence of malaria, growing resistance to anti-malarial drugs is perhaps the most important. The rising all-cause mortality rate among African children is attributable directly to malaria and specifically to the rapidly increasing resistance to anti-malarial drugs. Drug resistance is also emerging as a serious problem in the Indian subcontinent. The number of effective drugs available to treat malaria is small and the rate at which resistance is growing is outpacing the development of new anti-malarials. Nearly all the anti-malarials that are in use today were developed almost 30 years ago and, in general, the pharmaceutical companies, particularly the multinationals, have little interest in developing new cure despite the enormous need. Flavones have attracted continuing interest because of their varied biological activities namely anti-bacterial, anti-fungal, anti-Malarial, anti-viral, anti-oxidant, hepatoprotective, anti-inflammatory, anti-cancer, cardiovascular, anti-osteoporotic effects, anti-allergic, Anti-Alzheimer and anti-thrombotic activity

Why Are People's Decisions Sometimes Worse with Computer Support?

In many applications of computerised decision support, a recognised source of undesired outcomes is operators' apparent over-reliance on automation. For instance, an operator may fail to react to a potentially dangerous situation because a computer fails to generate an alarm. However, the very use of terms like "over-reliance" betrays possible misunderstandings of these phenomena and their causes, which may lead to ineffective corrective action (e.g. training or procedures that do not counteract all the causes of the apparently "over-reliant" behaviour). We review relevant literature in the area of "automation bias" and describe the diverse mechanisms that may be involved in human errors when using computer support. We discuss these mechanisms, with reference to errors of omission when using "alerting systems", with the help of examples of novel counterintuitive findings we obtained from a case study in a health care application, as well as other examples from the literature

Evaluation of Oxidative Stress and Antioxidant Status in Patients with Cardiovascular Disease in Rural Populations of the Nilgiris, South India

Objective. The objective of this work was to study the risk factors of ischaemic heart disease (IHD) in rural populations of the Nilgiris, south India, with stress on the various social habits and oxidant stress. Methods. A total of 72 patients with cardiovascular disease (CVD) and 12 healthy volunteers were screened. Forty-seven patients with CVD (intervention group) and 10 healthy volunteers (control group) were randomly selected for the study. Written informed consent was obtained from all the participants, and their demographic details were collected. A 6 mL blood sample was collected from each of the participants, and the serum was separated in the samples. The levels of enzymic (superoxide dismutase, catalase) and nonenzymic antioxidants (ascorbic acid) in the plasma were determined biochemically. The level of thiobarbituric acid species (TBARS), which is a predictor of lipid peroxidation, was measured. Results. The participants of the study were stratified as according to demographic and social variables. The values of all the antioxidants and TBARS were statistically compared. Significantly reduced antioxidant levels and increased TBARS levels were found in the intervention group compared with the control group. The results suggest that the lowered antioxidant level may be a result of the oxidant stress of the disease. Statistically significant differences were not found in the antioxidant and TBARS levels when comparing smokers versus nonsmokers, alcoholics versus nonalcoholics, and vegetarians versus nonvegetarians. Conclusion. The major causes of CVD amongst the rural populations of the Nilgiris, south India, are preventable causes such as smoking and high fat intake, all of which cause oxidative stress, as seen in our study through various serum markers

Current Concepts and Trends in Human-Automation Interaction

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.The purpose of this panel was to provide a general overview and discussion of some of the most current and controversial concepts and trends in human-automation interaction. The panel was composed of eight researchers and practitioners. The panelists are well-known experts in the area and offered differing views on a variety of different human-automation topics. The range of concepts and trends discussed in this panel include: general taxonomies regarding stages and levels of automation and function allocation, individualized adaptive automation, automation-induced complacency, economic rationality and the use of automation, the potential utility of false alarms, the influence of different types of false alarms on trust and reliance, and a system-wide theory of trust in multiple automated aids

3D Deep Learning on Medical Images: A Review

The rapid advancements in machine learning, graphics processing technologies and availability of medical imaging data has led to a rapid increase in use of deep learning models in the medical domain. This was exacerbated by the rapid advancements in convolutional neural network (CNN) based architectures, which were adopted by the medical imaging community to assist clinicians in disease diagnosis. Since the grand success of AlexNet in 2012, CNNs have been increasingly used in medical image analysis to improve the efficiency of human clinicians. In recent years, three-dimensional (3D) CNNs have been employed for analysis of medical images. In this paper, we trace the history of how the 3D CNN was developed from its machine learning roots, give a brief mathematical description of 3D CNN and the preprocessing steps required for medical images before feeding them to 3D CNNs. We review the significant research in the field of 3D medical imaging analysis using 3D CNNs (and its variants) in different medical areas such as classification, segmentation, detection, and localization. We conclude by discussing the challenges associated with the use of 3D CNNs in the medical imaging domain (and the use of deep learning models, in general) and possible future trends in the field.Comment: 13 pages, 4 figures, 2 table