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Investigation of research support services (RSS) in academic libraries of India
No full textResearch is crucial not only for the growth of a country but also for society as a whole, especially in a knowledge-based society. At each stage of research, scientists and researchers require support from various research stakeholders in the form of information resources and pertinent assistance. Consequently, academic libraries, as one of the most important stakeholders in research and the backbone of knowledge acquisition, storage, and dissemination processes, offer a variety of services to support research endeavors in their parent institutions. The current study classifies these services into eight major categories, viz. “Research Guides, Research Consultancy, Research Impact Measurement, Open Access, Research Tools Recommendation, Research Data Management (RDM), Scholarly Publishing, and Archiving and Preservation of Research Output (Article, Data, etc.).” The purpose of this study is to investigate the implementation status of these Research Support Services (RSS) in academic libraries of India (which include a total of 212 institutions, counting all of India’s “Central Universities (CUs)” (56) and “Institutes of National Importance (INIs)” (156) by referring to the related information provided on their respective library websites. The findings show that Indian academic libraries lack significant adoption and cognizance of research support services, and their implementation is in its infancy. The study reveals that very few academic libraries offer RDM services, whereas the vast majority of academic libraries provide recommendations for research tools. Indian academic libraries need to actively explore various RSS and make them a part of their core offerings. Additionally, they should look into novel ways to support researchers at different phases of their studies
Jack bean urease inhibition by different root fractions of Cleome gynandra L – Kinetic mechanism and computational molecular modelling
No full textNatural products with urease inhibiting potentialities would be valuable for enhancing nitrogen fertilizer formulations and developing new therapeutics against infectious diseases. Main focus of this research was to assess the inhibitory impact of various parts of Cleome gynandra (Cleomaceae) on jack bean urease activity, identify the responsible compounds, and ascertain their mode of enzyme inhibition and interactions with urease enzyme. Urease inhibitory potentiality of different plant parts of C. gynandra was determined using the phenol-hypochlorite method and mode of enzyme inhibition by Lineweaver-Burk kinetic analysis. LC-HRMS was carried out to identify the compounds of the active fractions. Molecular docking and simulations were executed to find out the binding affinity and interaction pattern of the isolated compounds at the active site of urease enzyme and to verify stability of protein-inhibitor complexes. The root of C. gynandra exhibited highest urease inhibitory potentiality with IC50 value of 1.529 mg/ml compared with leaf and stem. Among the different root fractions, water fraction revealed maximum anti-urease activity with IC50 values of 1.477 mg/ml followed by methanol (1.655 mg/ml) and acetone fractions (1.955 mg/ml). Inhibition kinetics indicated that these fractions were strong inhibitors of urease and exhibited a non-competitive mode of inhibition with Ki values of 184.911 µg/ml, 147.34 µg/ml, and 233.75 µg/ml respectively at 1000 mg/L concentration. LC-HRMS analysis confirmed the occurrence of glucocapparin, fluticasone propionate and lauryl hydrogen sulfate etc. in water fraction. Molecular modelling and simulation study suggested strong and stable interactions between the specified compounds of water fraction and active site of urease. Hence, the water fraction of C. gynandra roots represent a valuable source of natural urease inhibitors, for possible therapeutic applications and sustainable agricultural practices
Knowledge Guided Transformer Network for Compositional Zero-Shot Learning
No full textCompositional Zero-shot Learning (CZSL) attempts to recognise images of new compositions of states and objects when images of only a subset of state-object compositions are available as training data. An example of CZSL is to recognise images of peeled apple by a model when it is trained using images of peeled orange, ripe apple and ripe orange. There are two major challenges in solving CZSL. First, the visual features of a state vary depending on the context of a state-object composition. For example state like ripe produces distinct visual properties in the compositions ripe orange and ripe banana. Hence, understanding the context dependency of state features is a necessary requirement to solve CZSL. Second, the extent of association between the features of a state and an object varies significantly in different images of same composition. For example, in different images of peeled oranges, the oranges may be peeled to different extents. As a consequence, the visual features of images of the class peeled orange may vary. Hence, there exists a significant amount of intra-class variability among the visual features of different images of a composition. Existing approaches merely look for the existence or absence of features of particular state or object in a composition. Our approach not only looks for the existence of a particular state features or object features but also the extent of association of state features and object features to better tackle the intra-class variability in visual features of compositional images. The proposed architecture is constructed using a novel Knowledge Guided Transformer. The transformer-based framework is utilised for processing larger context dependency between the state and object. Extensive experiments on C-GQA, MIT-States and UT-Zappos50k datasets demonstrate the superiority of the proposed approach in comparison with the state-of-the-art in both open-world and closed-world CZSL settings
K-theory of noncommutative Bernoulli shifts
No full textFor a large class of C∗-algebras A, we calculate the K-theory of reduced crossed products A⊗G⋊rG of Bernoulli shifts by groups satisfying the Baum–Connes conjecture. In particular, we give explicit formulas for finite-dimensional C∗-algebras, UHF-algebras, rotation algebras, and several other examples. As an application, we obtain a formula for the K-theory of reduced C∗-algebras of wreath products H≀G for large classes of groups H and G. Our methods use a generalization of techniques developed by the second named author together with Joachim Cuntz and Xin Li, and a trivialization theorem for finite group actions on UHF algebras developed in a companion paper by the third and fourth named authors
Locally unidentifiable subset of quantum states and its resourcefulness in secret password distribution
No full textWe introduce a stronger form of quantum nonlocality, termed local subset unidentifiability, that arises from the limitation of spatially separated parties to perfectly identify a subset of mutually orthogonal multipartite quantum states, randomly chosen from a larger known set, using local operations and classical communication (LOCC). We show that this nonlocality is stronger than other existing forms of quantum nonlocality, such as local indistinguishability and local unmarkability. If more than one multipartite states from a locally indistinguishable set are distributed between spatially separated parties in a sequentially ordered fashion, then they may or may not mark which state is which using LOCC. However, we show that even when the parties cannot mark the states, they may still locally identify the particular states given to them, though not their order - i.e., they can identify the elements of the given subset of states. Then we prove the existence of such subsets that are not even locally identifiable, thereby manifesting a stronger nonlocality. We also present the genuine version of this nonlocality - genuine subset unidentifiability - where the provided subset remains unidentifiable unless all the parties come together in a common location and perform global measurements. We anticipate potential applications of this nonlocality for future quantum technologies. We discuss one such application in a certain secret password distribution protocol, where this nonlocality outperforms its predecessors as a resource
Minimum detection efficiencies for loophole-free genuine nonlocality tests
No full textThe certification of quantum nonlocality, which has immense significance in designing device-independent technologies, confronts severe experimental challenges. Detection loopholes, originating from the unavailability of perfect detectors, are one of the major issues among them. In the present study we focus on the minimum detection efficiency (MDE) required to detect various forms of genuine nonlocality, originating from the type of causal constraints imposed on the involved parties. In this context, we demonstrate that the MDE needed to manifest the recently suggested T2-type nonlocality deviates significantly from perfection. Additionally, we have computed the MDE necessary to manifest Svetlichny\u27s nonlocality, with the state-independent approach markedly reducing the previously established bound. Finally, considering the inevitable existence of noise we demonstrate the robustness of the imperfect detectors to certify T2-type nonlocality
Moduli dynamics in effective nested warped geometry in four dimensions and some cosmological implications
No full textWe analyze the effective four-dimensional dynamics of the extra-dimensional moduli fields in curved braneworlds having nested warping, with particular emphasis on the doubly warped model which is interesting in the light of current collider constraints on the mass of the Kaluza-Klein graviton. The presence of a non-zero brane cosmological constant (Ω) naturally induces an effective moduli potential in the four-dimensional action, which shows distinct features in dS (Ω \u3e 0) and AdS (Ω \u3c 0) branches. For the observationally interesting case of dS 4-branes, a metastable minimum in the potential arises along the first modulus, with no minima along the higher moduli. The underlying nested geometry also leads to interesting separable forms of the non-canonical kinetic terms in the Einstein frame, where the brane curvature directly impacts the kinetic properties of only the first modulus. The non-canonicity of the scenario has been illustrated via an explicit computation of the field space curvature. We subsequently explore the ability of curved multiply warped geometries to drive inflation with an in-built exit mechanism, by considering predominant slow roll along each modular direction on a case-by-case basis. We find slow roll on top of the metastable plateau along the first modular direction to be the most viable scenario, with the higher-dimensional moduli parametrically tuning the height of the potential without significant impact on the inflationary observables. On the other hand, while slow roll along the higher moduli can successfully inflate the background and eventually lead to an exit, consistency with observations seemingly requires unphysical hierarchies among the extra-dimensional radii, thus disfavouring such scenarios
Multi-scale analysis of rural and urban areas: a case study of Indian districts
No full textAbstract: It is well known that the urban systems, in particular cities, display scaling behaviour regarding socio-economic, infrastructural and individual basic services indicators. However, understanding urbanisation and the links between rural and urban areas is fundamental to making the most of the global transformations happening around the world. In this context, it is important to study the scaling laws based on both the urban and rural regions, going beyond cities. This paper explores the extension of the idea of allometric urban scaling law to study the scaling behaviour of Indian districts, with both the urban and rural population. To proceed, we have chosen districts (both rural and urban) of India, a relatively larger local administrative units, which are more or less independently functional within a country. This interdisciplinary work focus on the scaling analysis of various socio-economic indicators (SEIs) corresponding to the size (population) of four distinct urbanisation classes, namely rural, semi-rural, semi-urban and urban districts. The scaling exponents (β) were estimated for each classes for the years 2001 and 2011 along with their goodness-of-fit measured by the R2 values. Our rigorous statistical analysis indicates that the scaling laws indeed exist even at the district level for most of the SEIs considered, related to education, employment, housing, health, etc.; the R2 values obtained for these SEIs are very high (often greater than 0.8 or 0.9) in both the years. Moreover, linearity of the scaling factors have been statistically tested and it has been found, at 95% level of confidence, that not all the SEIs behave linearly (β= 1); some of them are characterised by super-linear (β\u3e 1) behaviour and some behave sub-linearly (β\u3c 1). Statistical hypothesis tests have also been performed to test the equality of two scaling factors corresponding to two distinct classes and two different years to understand the differences in scaling relationships amongst increasing urbanisation classes and their changes over time. Graphical Abstract: [Figure not available: see fulltext.]
Neighbourhood and the Perception of the Quality of Medical Treatment
No full textNumerous studies have explored the role of the economic characteristics of a neighbourhood on the health status of its residents. We contribute to this work by examining the effects of the change in concentration of affluence on the perception of the quality of medical treatment received by the poor. We consider different neighbourhoods characterised by their level of prosperity. Based on the Asset Index, a particular primary sampling unit is identified as poor, middle or rich neighbourhoods to capture regional differences in the level of poverty. In each of these regions, we measure how the percentage of poor who claim that they were treated nicely varies with the change in the percentage of rich. The results reveal that, after a point, the probability of the perception of receiving superior treatment initially increases with an increase in the percentage of rich people and then starts declining. The principal component analysis is used to create weights in the asset index. The estimation is based on the nationally representative India Human Development Survey-2 (IHDS-2) household data collected in 2011–2012. We employ an ordered logit model for the analysis, as the perception of the quality of treatment, the dependent variable, is ordered in nature. Furthermore, we use Heckman’s two-step correction method to control for the plausibility of ‘self-selection’