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Copyright of European Journal of Development Research is the property of Palgrave Macmillan Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Cryptocurrency is a form of digital currency using cryptographic techniques in a decentralized system for secure peer-to-peer transactions. It is gaining much popularity over traditional methods of payment because it facilitates very fast, easy, and secure transactions. Social media is a significant influence, but it is also very volatile and subject to a variety of other factors. Thus, with over four billion active users on social media, we need to understand its influence on the crypto market and how it can lead to fluctuations in the values of these cryptocurrencies. In our work, we analyze the influence of activities on Twitter, in particular the sentiments of the tweets posted regarding cryptocurrencies and how they influence their prices. In addition, we also collect metadata related to tweets and users. We try to leverage these features to predict the price of cryptocurrency, for which we use some regression-based models and an LSTM-based model. [ABSTRACT FROM AUTHOR]

Background: A new strain of coronavirus responsible for pneumonia of unknown origin was detected in early January 2020, named as 2019-novel coronavirus. Even though COVID-19 has affected all regions of the world, there are great variations in the prevalence of the disease and mortality rates in different countries, the reasons for which are poorly understood. In this study, we analysed the clinical manifestation, laboratory profile and final outcome in COVID-19 patients in our Medical College & Hospital providing tertiary care with the purpose of adding information to the already existing data. Material and Methods: Inclusion Criteria: All positive and confirmed cases of COVID-19 disease, admitted in COVID wards, HDU, ICU of our Medical College & Hospital, irrespective of age & gender. Results: Majority of study subjects (61%) were above 40 years of age. The commonest presenting complaint was cough with less than one-fifth having fever. Sputum was present in 27% of cases and more common in live subjects. Breathlessness was present in 56% of cases and more common in expired subjects. Oxygen support was required in 59% of cases. Treatment with Remdesivir was needed in more than 80% of non-survivors of Covid-19 disease while less than 30% survivors needed Remdesivir therapy. Plasma treatment therapy was given in 6% and Mechanical ventilation in 34% of cases. Conclusion: Majority of the patients were asymptomatic but potential spreaders of the disease. Fever, cough, and breathlessness were the major presenting symptoms. Advanced age, high TLC with high N/L ratio, high CRP level, high serum ferritin level, high D-dimer value and low vitamin D levels correlated positively with severity of disease responsible for high mortality rate. [ABSTRACT FROM AUTHOR]

Background: A large proportion of amputations of lower extremity secondary to aPAD is the major cause of significant disability and hence economic burden on individual and as well as the healthcare system in developing countries like India. LEAD is characterized by a spectrum ranging from no symptoms, intermittent claudicating, pain at rest to finally non-healing wounds & gangrene. ABPI is a not only a sensitive but cost-effective screening tool for LEAD. Pulse oximetry (PO) which is a simple, noninvasive, readily available & inexpensive tool for measurement of oxygen saturation in peripheral blood (SpO2). This study was conducted to comapre (ABPI) plus Pulse oximetry with Duplex Ultrasound in detecting LEAD in Diabetes Mellitus. Material and Methods: Inclusion Criteria: Adults more than 40 years with known diagnosis of Diabetes Mellitus. Exclusion Criteria: Patient having lower limb amputation, fracture, or gangrenous limb, Patient with pedal oedema or ulcer, Previous history of hypercoagulable states, congestive heart failure, suspected arteritis, or collagen vascular diseases, Patients with coarctation of aorta & Patients with pre-existing diagnosis of lower extremity arterial disease (LEAD). Results: This study was carried out at TMMC & RC (Moradabad, UP). It was a prospective hospital based observational study. Out of 55 participant 30 (54.5%) are smoker and 25 (45.5%) are non-smoker. Among 30 smoker 29 (96.7%) are pulse oximeter positive and 1 (3.33%) are pulse oximeter negative. In our study, Right limb analysis suggestive of 75% of sensitivity, 39.1% of specificity, 63.2% of PPV and 52.9% of NPV. Right ABPI has 60% of accuracy. Left limb analysis suggestive of 65.5% sensitivity, 42.3% specificity, 55.9% PPV and 52.4% NPV. Left limb ABPI has 54.5% of accuracy. Left limb pulse oximeter method analysis suggestive of 93.1% sensitivity, 23.1% specificity, 57.4% PPV and 75% NPV. Left limb pulse oximetry method has 60% of accuracy. Average pulse oximeter analysis: 91.8% sensitivity, 22.4% specificity, 60% PPV and 68.7% NPV. Average ABPI had an accuracy of 60.9%. Conclusion: A combination of ABPI & PO is most sensitive with highest negative predictive value. These methods are simple, cost effective, quick, non-invasive and easily available tools. Hence, detection of LEAD should be a part of regular work-up of DM patients. [ABSTRACT FROM AUTHOR]

Human Identification has been widely implemented to enhance the efficiency of surveillance systems, however, systems based on common CCTV (closed-circuit television) cameras are mostly incompatible with the advanced identification algorithms which aim to extract the facial features or speech of an individual for identification. Gait (i.e., an individual's unique walking pattern/style) is a leading exponent when compared to first-generation biometric modalities as it is unobtrusive (i.e., it requires no contact with the individual), hence proving gait to be an optimal solution to human identification at a distance. This paper proposes an automatic identification system that analyzes gait to identify humans at a distance and predicts the strength of the match (i.e., probability of the match being positive) between two gait profiles. This is achieved by incorporating computer vision, digital image processing, vectorization, artificial intelligence, and multi-threading. The proposed model extracts gait profiles (from low-resolution camera feeds) by breaking down the complete gait cycle into four quarter-cycles using the variations in the width of the region-of-interest and then saves the gait profile in the form of four distinct projections (i.e., vectors) of length 20 units each, thus, summing up to 80 features for each individual's gait profile. The focus of this study revolved around the speed-accuracy tradeoff of the proposed model where, with a limited dataset and training, the model runs at a speed of 30Hz and yields 85% accurate results on average. A Receiver Operating Characteristic Curve (ROC) is obtained for comparison of the proposed model with other machine learning models to better understand the efficiency of the system. [ABSTRACT FROM AUTHOR]

We construct viscous fluid flow sourced by a force dipole embedded in a cylindrical fluid membrane, coupled to external embedding fluids. We find analytic expressions for the flow in the limit of infinitely long and thin tubular membranes. We utilize this solution to formulate the in-plane dynamics of a pair of pusher-type dipoles along the cylinder surface. We find that a mutually perpendicular dipole pair generically moves together along helical geodesics. Since the cylindrical geometry breaks the in-plane rotational symmetry of the membrane, there is a difference in flows along the axial ( z ̂ ) and transverse ( θ ̂ ) directions of the cylinder. This in turn leads to anisotropic hydrodynamic interaction between the dipoles and is remarkably different from flat and spherical fluid membranes. In particular, the flow along the compact θ ̂ direction of the cylinder has a local rigid rotation term (independent of the angular coordinate but decays along the axis of the cylinder). Due to this feature of the flow, we observe that the interacting dipole pair initially situated along the axial direction z ̂ exhibits an overall "drift" along the compact angular direction θ ̂ of the tubular fluid membrane. We find that the drift for the dipole pair increases linearly with time. Our results are relevant for non-equilibrium dynamics of motor proteins in tubular membranes arising in nature, as well as in vitro experiments. [ABSTRACT FROM AUTHOR]

The objectives of this work are to investigate the status of implementation of quality initiatives by manufacturing firms in Madhya Pradesh, India, and to compare large and small-medium scale industries. Very few researchers have attempted to compare large scale and small-medium scale firms in order to know the extent of implementation of quality initiatives for a state like Madhya Pradesh. In this study, the survey questionnaire method was used for the collection of data. Nine quality initiatives were selected for the study. The obtained data are grouped into two groups: 1) large scale firms, and 2) small-medium scale firms. Descriptive and inferential statistics are used for analysis and the results are presented. Hypothesis testing was used to investigate for any significant difference between the two groups of firms in implementing each quality initiative. Results from inferential statistics reveal that there is a significant difference in the implementation of quality initiatives in large and small-medium scale industries. The findings of the present work will guide firms to identify areas where improvement is required at each quality initiative level. The study will help small-medium scale firms in the Madhya Pradesh state of India to conduct training programs in the areas of relevant quality initiatives for improving their quality of products. [ABSTRACT FROM AUTHOR]

Social cognition concerns the various psychological processes that enable individuals to take advantage of being part of a social group. Of major importance to social cognition are the various social signals that enable us to learn about the world. Such signals include facial expressions, such as fear and disgust, which warn us of danger, and eye gaze direction, which indicate where interesting things can be found. Such signals are particularly important in infant development. Social referencing, for example, refers to the phenomenon in which infants refer to their mothers’ facial expressions to determine whether or not to approach a novel object. We can learn a great deal simply by observing others. Much of this signalling seems to happen automatically and unconsciously on the part of both the sender and the receiver. We can learn to fear a stimulus by observing the response of another, in the absence of awareness of that stimulus. By contrast, learning by instruction, rather than observation, does seem to depend upon awareness of the stimulus, since such learning does not generalize to situations where the stimulus is presented subliminally. Learning by instruction depends upon a meta-cognitive process through which both the sender and the receiver recognize that signals are intended to be signals. An example would be the ‘ostensive’ signals that indicate that what follows are intentional communications. Infants learn more from signals that they recognize to be instructive. I speculate that it is this ability to recognize and learn from instructions rather than mere observation which permitted that advanced ability to benefit from cultural learning that seems to be unique to the human race. [ABSTRACT FROM AUTHOR]

Feature selection is a critical research problem in data science. The need for feature selection has become more critical with the advent of high-dimensional data sets especially related to text, image and micro-array data. In this paper, a graph-theoretic approach with step-by-step visualization is proposed in the context of supervised feature selection. Mutual information criterion is used to evaluate the relevance of the features with respect to the class. A graph-based representation of the input data set, named as feature information map (FIM) is created, highlighting the vertices representing the less informative features. Amongst the more informative features, the inter-feature similarity is measured to draw edges between features having high similarity. At the end, minimal vertex cover is applied on the connected vertices to identify a subset of features potentially having less similarity among each other. Results of the experiments conducted with standard data sets show that the proposed method gives better results than the competing algorithms for most of the data sets. The proposed algorithm also has a novel contribution of rendering a visualization of features in terms of relevance and redundancy. [ABSTRACT FROM AUTHOR]

Dr. Kübler-Ross also weaves in many real-life transcripts from her interviews with patients with life-limiting illness. REFERENCES 1 Bansal A, Monk A, Norman M, Fingas S. Improving medical students' confidence in end-of-life consultations. We welcome the study by Bansal I et al i .1 that is looking into ways to stimulate awareness, engagement and confidence in end-of-life discussions for medical students. [Extracted from the article]