Author: Anuradha Batabyal
A Novel Behavioral Display in Lymnaea Induced by Quercetin and Hypoxia
Publisher: The Biological Bulletin, 2023
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The pond snail Lymnaea stagnalis employs aerial respiration under hypoxia and can be operantly conditioned to reduce this behavior. When applied individually, a heat shock (30 °C for 1 h) and the flavonoid quercetin enhance long-term memory formation for the operant conditioning of aerial respiration. However, when snails are exposed to quercetin before the heat shock, long-term memory is no longer enhanced. This is because quercetin prevents the heat-induced upregulation of heat-shock proteins 70 and 40. When we tested the memory outcome of operant conditioning due to the simultaneous exposure to quercetin and 30 °C, we found that Lymnaea entered a quiescent survival state. The same behavioral response occurred when snails were simultaneously exposed to quercetin and pond water made hypoxic by bubbling nitrogen through it. Thus, in this study, we performed six experiments to propose a physiological explanation for that curious behavioral response. Our results suggest that bubbling nitrogen in pond water, heating pond water to 30 °C, and bubbling nitrogen in 30 °C pond water create a hypoxic environment, to which organisms may respond by upregulating the heat-shock protein system. On the other hand, when snails experience quercetin together with these hypoxic conditions, they can no longer express the physiological stress response evoked by heat or hypoxia. Thus, the quiescent survival state could be an emergency response to survive the hypoxic condition when the heat-shock proteins cannot be activated.
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Author: Anuradha Batabyal
LPS-Induced Garcia Effect and Its Pharmacological Regulation Mediated by Acetylsalicylic Acid: Behavioral and Transcriptional Evidence
Publisher: Biology, 2023
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Lymnaea stagnalis learns and remembers to avoid certain foods when their ingestion is followed by sickness. This rapid, taste-specific, and long-lasting aversion—known as the Garcia effect—can be formed by exposing snails to a novel taste and 1 h later injecting them with lipopolysaccharide (LPS). However, the exposure of snails to acetylsalicylic acid (ASA) for 1 h before the LPS injection, prevents both the LPS-induced sickness state and the Garcia effect. Here, we investigated novel aspects of this unique form of conditioned taste aversion and its pharmacological regulation. We first explored the transcriptional effects in the snails’ central nervous system induced by the injection with LPS (25 mg), the exposure to ASA (900 nM), as well as their combined presentation in untrained snails. Then, we investigated the behavioral and molecular mechanisms underlying the LPS-induced Garcia effect and its pharmacological regulation by ASA. LPS injection, both alone and during the Garcia effect procedure, upregulated the expression levels of immune- and stress-related targets. This upregulation was prevented by pre-exposure to ASA. While LPS alone did not affect the expression levels of neuroplasticity genes, its combination with the conditioning procedure resulted in their significant upregulation and memory formation for the Garcia effect.
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Author: Aamod Sane, Renu Dhadwal and Jayaraman Valadi
Interpretation of Drop Size Predictions from a Random Forest Model Using Local Interpretable Model-Agnostic Explanations (LIME) in a Rotating Disc Contactor
Publisher: Industrial & Engineering Chemistry Research, 2023
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Drop size is a crucial parameter for the efficient design and operation of the rotating disc contactor (RDC) in liquid–liquid extraction. The current work focuses on providing local and global explanations for the prediction of the drop size in a rotating disc contactor (RDC). The Random Forest (RF) regression model is a robust machine learning algorithm that can accurately capture complex relationships in the data. However, the interpretability of the model is limited. In order to address the issue of interpretability of the developed RF model, in the current work, we employed Local Interpretable Model-Agnostic Explanations (LIME) of the predictions of the RF model. This provides both local and global views of the model and thereby helps one to gain insights into the factors influencing predictions. We have provided local explanations depicting the impact of different attributes on the prediction of the output for any given input example. We have also obtained global feature importance, providing the top subset of informative attributes. We have also developed local surrogate models incorporating second order attribute interactions. This has provided important information about the effect of interactions on the drop size prediction. By augmenting the random forest model with LIME, it is possible to develop a more accurate and interpretable model for estimating the drop size in RDCs, ultimately leading to improved performance and efficiency.
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Author: Ajith Abraham
An Improved Boykov’s Graph Cut-based Segmentation Technique for the Efficient Detection of Cervical Cancer
Publisher: IEEE Access, 2023
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The accurate and reliable derivation of the pap smear cell, which contains cytoplasm and nucleus regions, depends on the segmentation process employed in the cervical cancer detection mechanism. In this paper, an Improved Boykov’s Graph Cut-based Conditional Random Fields and Superpixel imposed Semantic Segmentation Technique (IBGC-CRF-SPSST) is proposed for efficient cervical cancer detection. This proposed IBGC-CRF-SPSST embeds the complete benefits of constraint association among pixels and superpixel edge data for accurate determination of the nuclei and cytoplasmic boundaries so as to ensure efficient differentiation of the healthy and unhealthy cancer cells. Finally, the pixel-level forecasting potential of Conditional Random Fields is included for enhancing the degree of semantic-based segmentation accuracy to a predominant level. The experimental evaluated results of the proposed IBGC-CRF-SPSST aim to produce an accuracy of 99.78%, a mean processing time of 2.18sec, a precision of 96%, a sensitivity of 98.92%, and a specificity of 99.32% value which is determined to be excellent and on par with the existing detection techniques used for investigating cervical cancer.
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Author: Lily Kelting
Sorry Not Sorry: Monster Truck’s Postcolonial Anti-Authenticity Spectacular!
Publisher: TDR: The Drama Review, 2023
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Monster Truck’s performances reproduce power dynamics that are at once painful and hurtful. By staging the representational process of dehumanizing black bodies, Monster Truck applies a different strategy than other Freie Szene groups: shining a bright light on dark discourse, selling the audience’s own willing consumption of neocolonial power relationships back to them as art.
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Author: Sunil Rajpal
Progress on Sustainable Development Goal indicators in 707 districts of India: a quantitative mid-line assessment using the National Family Health Surveys, 2016 and 2021
Publisher: The Lancet Regional Health – Southeast Asia, 2023
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"India has committed itself to accomplishing the Sustainable Development Goals (SDGs) by 2030. Meeting these goals would require prioritizing and targeting specific areas within India. We provide a mid-line assessment of the progress across 707 districts of India for 33 SDG indicators related to health and social determinants of health.
Methods
We used data collected on children and adults from two rounds of the National Family Health Survey (NFHS) conducted in 2016 and 2021. We identified 33 indicators that cover 9 of the 17 official SDGs. We used the goals and targets outlined by the Global Indicator Framework, Government of India and World Health Organization (WHO) to determine SDG targets to be met by 2030. Using precision-weighted multilevel models, we estimated district mean for 2016 and 2021, and using these values, computed the Annual Absolute Change (AAC) for each indicator. Using the AAC and targets, we classified India and each district as: Achieved-I, Achieved-II, On-Target and Off-Target. Further, when a district was Off-Target on a given indicator, we further identified the calendar year in which the target will be met post-2030.
Findings
India is not On-Target for 19 of the 33 SDGs indicators. The critical Off-Target indicators include Access to Basic Services, Wasting and Overweight Children, Anaemia, Child Marriage, Partner Violence, Tobacco Use, and Modern Contraceptive Use. For these indicators, more than 75% of the districts were Off-Target. Because of a worsening trend observed between 2016 and 2021, and assuming no course correction occurs, many districts will never meet the targets on the SDGs even well after 2030. These Off-Target districts are concentrated in the states of Madhya Pradesh, Chhattisgarh, Jharkhand, Bihar, and Odisha. Finally, it does not appear that Aspirational Districts, on average, are performing better in meeting the SDG targets than other districts on majority of the indicators.
Interpretation
A mid-line assessment of districts' progress on SDGs suggests an urgent need to increase the pace and momentum on four SDG goals: No Poverty (SDG 1), Zero Hunger (SDG 2), Good Health and Well-Being (SDG 3) and Gender Equality (SDG 5). Developing a strategic roadmap at this time will help India ensure success with regards to meeting the SDGs. India's emergence and sustenance as a leading economic power depends on meeting some of the more basic health and social determinants of health-related SDGs in an immediate and equitable manner."
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Author: Barun Kumar Thakur
Interrelationship between Share of Women in Parliament and Gender and Development: A Critical Analysis
Publisher: Administrative Sciences, 2023
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Gender and development are among the two most important components of any economy to sustain its perpetual and sustainable economic growth in both the long as well as short run. The role of women in parliament and the interrelationship between gender and development is critically analysed. Women’s representation in parliament is the dependent variable and the predictor variables considered are gender development index, female access to assets, female labour force, and country GDP per capita. Data were collected from the UNDP human development report for the period 2015 to 2021–2022 and World Bank for 188 countries of which finally 159 were considered to develop the model based on data availability. We have used the theoretical lens of social stratification theory and gender role theory to frame the hypothesis. A random effects model-based panel regression analysis of the data indicated a strong positive relationship between gender development index and the dependent variable, but no relationship between female labour force, and access to assets. The study addresses a critical gap in policy and development of the literature on gender, politics, and development using a global data set, establishing the importance of indicators such as gender development index, and laying down the path for future research on the subject.
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Author: Shweta Rana
Recent Advances and Perspectives of Nanomaterials in Agricultural Management and Associated Environmental Risk: A Review
Publisher: Nanomaterials, 2023
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The advancement in nanotechnology has enabled a significant expansion in agricultural production. Agri-nanotechnology is an emerging discipline where nanotechnological methods provide diverse nanomaterials (NMs) such as nanopesticides, nanoherbicides, nanofertilizers and different nanoforms of agrochemicals for agricultural management. Applications of nanofabricated products can potentially improve the shelf life, stability, bioavailability, safety and environmental sustainability of active ingredients for sustained release. Nanoscale modification of bulk or surface properties bears tremendous potential for effective enhancement of agricultural productivity. As NMs improve the tolerance mechanisms of the plants under stressful conditions, they are considered as effective and promising tools to overcome the constraints in sustainable agricultural production. For their exceptional qualities and usages, nano-enabled products are developed and enforced, along with agriculture, in diverse sectors. The rampant usage of NMs increases their release into the environment. Once incorporated into the environment, NMs may threaten the stability and function of biological systems. Nanotechnology is a newly emerging technology, so the evaluation of the associated environmental risk is pivotal. This review emphasizes the current approach to NMs synthesis, their application in agriculture, interaction with plant-soil microbes and environmental challenges to address future applications in maintaining a sustainable environment.
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Author: Gayatri Kotbagi
Analyse des causes psychologiques des premières consommations de substances psychoactives chez les adolescents en contexte scolaire et universitaire
Publisher: La Revue de l'Infirmiere, 2023
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Experimentation with psychoactive substances (PAS), such as alcohol, tobacco or cannabis, is common in adolescence, and continues to pose a public health issue that can lead to failure at school and university. Most of the work on these issues focuses on addiction-related aspects, and little on the underlying causes of addiction. This article sheds psycho-social theoretical light on the causes of first-time use of APS, and cannabis in particular. It is particularly aimed at school nurses and university preventive medicine nurses.
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Author: Yugank Goyal
A theory of legal apparitions: regulation and escape in Indian divorces
Publisher: International Journal of Law in Context, 2023
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When people do not approach a formal court of law to settle their disputes, and cannot enter into out-of-court settlements either, what do they do? I find that people install court-like processes which mimetically follow the court procedures, executing the settlement as if the decision were rendered officially. By examining such practices in the case of divorce-related disputes in India, I advance a theory of legal apparitions, a phenomenon in which cosmetic mimicry of legal processes creates a new form of extra-legal resolution. This is likely to prevail in societies where access to justice is hindered due to socio-institutional factors and customary forms of adjudication are not possible (sometimes because of state law’s design). This idea can be used to explain a range of practices observed in South Asian societies, where people’s imagination of, and interaction with, legal apparatuses creates new forms of institutions.
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Author: Sasikiran, R.M.
The PhD Odyssey: Retrospective Reflections on the Notion of “Care”
Publisher: Journal of Autoethnography, 2023
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"[Neoliberalism] has pervasive effects on ways of thought to the point where it has become incorporated into the common-sense way many of us interpret, live in, and understand the world.1
My critical autoethnographic account reflects on the lived experience of being a PhD scholar inhabiting a neoliberal public education space. It is written from a position of caste and class privilege, mindful of the trials and tribulations of less privileged fellow research scholars, who face unimaginable obstacles in the pursuit of their doctoral degrees. The attempt is not just to highlight the inconvenience caused to me but to reflect on the structures erected by neoliberalism that make pursuing a PhD a traumatic experience prone with vulnerabilities. I reflect on the precarity of doing a PhD in a public university in India after the normative age, the resulting anxiety, and notions of care.
When I discussed my plans of pursuing..."
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Author: Sreeparna Chattopadhyay
Making research ethics work for global health: towards a more agile and collaborative approach
Publisher: BMJ Global Health, 2023
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In this reflective essay, we seek to engage in a constructive dialogue with scholars across medicine, public health and anthropology on research ethics practices. Drawing on anthropological research and ethical dilemmas that our colleagues and we encountered as medical anthropologists, we reflect on presumed and institutionalised ‘best’ practices such as mandatory written informed consent, and problematise how they are implemented in interdisciplinary global health research projects. We demonstrate that mandatory, individualised, written, informed consent may be unsuitable in many contexts and also identify reasons why tensions between professionals in interdisciplinary teams may arise when decisions about ethics procedures are taken. We propose alternatives to written informed consent that acknowledge research governance requirements and contextual realities and leave more room for ethnographic approaches. Beyond informed consent, we also explore the situatedness of ethical practices when working in contexts where decision-making around health is clearly a shared concern. We use vignettes based on our own and colleagues’ experiences to illustrate our arguments, using the collective ‘we’ instead of ‘I’ in our vignettes to protect our research participants, partners and interlocutors. We propose a decolonial, plural and vernacular approach to informed consent specifically, and research ethics more broadly. We contend that ethics procedures and frameworks need to become more agile, decolonial, pluralised and vernacularised to enable achieving congruence between communities’ ideas of social justice and institutional ethics. We argue that global health research can benefit from anthropology’s engagement with situated ethics and consent that is relational, negotiated and processual; and accountability that is not only bureaucratic but also constructive. In doing so, we hope to broaden ethical praxis so that the best outcomes that are also just, fair and equitable can be achieved for all stakeholders.
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Author: Sunil Rajpal
Socioeconomic and geographic variation in coverage of health insurance across India
Publisher: Frontiers in Public Health, 2023
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"In India, regular monitoring of health insurance at district levels (the most essential administrative unit) is important for its effective uptake to contain the high out of pocket health expenditures. Given that the last individual data on health insurance coverage at district levels in India was in 2016, we update the evidence using the latest round of the National Family Health Survey conducted in 2019-2021.
Methods: We use the unit records of households from the latest round (2021) of the nationally representative National Family Health Survey to calculate the weighted percentage (and 95% CI) of households with at least one member covered by any form of health insurance and its types across socio-economic characteristics and geographies of India. Further, we used a random intercept logistic regression to measure the variation in coverage across communities, district and state. Such household level study of coverage is helpful as it represents awareness and outreach for at least one member, which can percolate easily to the entire household with further interventions.
Results: We found that only 2/5th of households in India had insurance coverage for at least one of its members, with vast geographic variation emphasizing need for aggressive expansion. About 15.5% were covered by national schemes, 47.1% by state health scheme, 13.2% by employer provided health insurance, 3.3% had purchased health insurance privately and 25.6% were covered by other health insurance schemes (not covered above). About 30.5% of the total variation in coverage was attributable to state, 2.7% to districts and 9.5% to clusters. Household size, gender, marital status and education of household head show weak gradient for coverage under “any” insurance.
Discussion: Despite substantial increase in population eligible for state sponsored health insurance and rise in private health insurance companies, nearly 60% of families do not have a single person covered under any health insurance scheme. Further, the existing coverage is fragmented, with significant rural/urban and geographic variation within districts. It is essential to consider these disparities and adopt rigorous place-based interventions for improving health insurance coverage."
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Author: Anuradha Batabyal
Investigating the interactions between multiple memory stores in the pond snail Lymnaea stagnalis
Publisher: Journal of Comparative Physiology A, 2023
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The pond snail Lymnaea stagnalis exhibits various forms of associative learning including (1) operant conditioning of aerial respiration where snails are trained not to open their pneumostome in a hypoxic pond water environment using a weak tactile stimulus to their pneumostome as they attempt to open it; and (2) a 24 h-lasting taste-specific learned avoidance known as the Garcia effect utilizing a lipopolysaccharide (LPS) injection just after snails eat a novel food substance (carrot). Typically, lab-inbred snails require two 0.5 h training sessions to form long-term memory (LTM) for operant conditioning of aerial respiration. However, some stressors (e.g., heat shock or predator scent) act as memory enhancers and thus a single 0.5 h training session is sufficient to enhance LTM formation lasting at least 24 h. Here, we found that snails forming a food-aversion LTM following Garcia-effect training exhibited enhanced LTM following operant condition of aerial respiration if trained in the presence of the food substance (carrot) they became averse to. Control experiments led us to conclude that carrot becomes a ‘sickness’ risk signal and acts as a stressor, sufficient to enhance LTM formation for another conditioning procedure.
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Author: Anuradha Batabyal
The extent of rapid colour change in male agamid lizards is unrelated to overall sexual dichromatism
Publisher: Ecology and Evolution, 2023
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Dynamic colour change is widespread in ectothermic animals, but has primarily been studied in the context of background matching. For most species, we lack quantitative data on the extent of colour change across different contexts. It is also unclear whether and how colour change varies across body regions, and how overall sexual dichromatism relates to the extent of individual colour change. In this study, we obtained reflectance measures in response to different stimuli for males and females of six species of agamid lizards (Agamidae, sister family to Chameleonidae) comprising three closely related species pairs. We computed the colour volume in a lizard-vision colour space occupied by males and females of each species and estimated overall sexual dichromatism based on the area of non-overlapping male and female colour volumes. As expected, males had larger colour volumes than females, but the extent of colour change in males differed between species and between body regions. Notably, species that were most sexually dichromatic were not necessarily those in which males showed the greatest individual colour change. Our results indicate that the extent of colour change is independent of the degree of sexual dichromatism and demonstrate that colour change on different body regions can vary substantially even between pairs of closely related species.
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Author: Debendrakumar Jain
Macro-financial risk in the South Pacific: analysing balance sheet effects for Fiji economy
Publisher: International Journal of Trade and Global Markets, 2023
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The general failure of highly sophisticated models of financial risk management (based on flow variables) prompted international financial institutions, researchers, and academics to look for options beyond the traditional macroeconomic indicators. This paper contributes to the gap in the literature related to the qualitative analysis of macro-financial risks of small island developing economies. The qualitative analysis based on the aggregate balance sheet of the Fiji economy is aimed at identifying sector-specific weaknesses and their developmental paths (sources of weaknesses). It analyses various financial risks across key economic sectors (government sector, central bank, other depository corporations (ODC), other financial corporations (OFC), other non-financial corporations (NFC), other resident and non-resident) and their linkages and spill-over effects from one sector to another sector within the aggregate economy. The findings are indicative and exploratory of sector-specific weaknesses and invite further research interest in applying the framework to other similar economies in the region.
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Author: Anuradha Batabyal
Five-minute exposure to a novel appetitive food substance is sufficient time for a microRNA-dependent long-term memory to form
Publisher: Journal of Comparative Physiology A, 2023
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The Garcia effect is a unique form of conditioned taste aversion which requires that a novel food stimulus be followed sometime later by a sickness state associated with the novel food stimulus. The long-lasting associative memory resulting from the Garcia effect ensures that organisms avoid toxic foods in their environment. Considering its ecological relevance, we sought to investigate whether a brief encounter (5 min) with a novel, appetitive food stimulus can cause a persisting long-term memory (LTM) to form that would in turn block the Garcia effect in Lymnaea stagnalis. Furthermore, we wanted to explore whether that persisting LTM could be modified by the alteration of microRNAs via an injection of poly-L-lysine (PLL), an inhibitor of Dicer-mediated microRNA biogenesis. The Garcia effect procedure involved two observations of feeding behavior in carrot separated by a heat stress (30 °C for 1 h). Exposing snails to carrot for 5 min caused a LTM to form and persist for 1 week, effectively preventing the Garcia effect in snails. In contrast, PLL injection following the 5-min carrot exposure impaired LTM formation, allowing the Garcia effect to occur. These results provide more insight into LTM formation and the Garcia effect, an important survival mechanism.
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Author: Ajith Abraham
Remaining Useful-Life Prediction of the Milling Cutting Tool Using Time–Frequency-Based Features and Deep Learning Models
Publisher: Sensors, 2023
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The milling machine serves an important role in manufacturing because of its versatility in machining. The cutting tool is a critical component of machining because it is responsible for machining accuracy and surface finishing, impacting industrial productivity. Monitoring the cutting tool’s life is essential to avoid machining downtime caused due to tool wear. To prevent the unplanned downtime of the machine and to utilize the maximum life of the cutting tool, the accurate prediction of the remaining useful life (RUL) cutting tool is essential. Different artificial intelligence (AI) techniques estimate the RUL of cutting tools in milling operations with improved prediction accuracy. The IEEE NUAA Ideahouse dataset has been used in this paper for the RUL estimation of the milling cutter. The accuracy of the prediction is based on the quality of feature engineering performed on the unprocessed data. Feature extraction is a crucial phase in RUL prediction. In this work, the authors considers the time–frequency domain (TFD) features such as short-time Fourier-transform (STFT) and different wavelet transforms (WT) along with deep learning (DL) models such as long short-term memory (LSTM), different variants of LSTN, convolutional neural network (CNN), and hybrid models that are a combination of CCN with LSTM variants for RUL estimation. The TFD feature extraction with LSTM variants and hybrid models performs well for the milling cutting tool RUL estimation.
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Author: Ajith Abraham
A Secure Big Data Storage Framework Based on Blockchain Consensus Mechanism With Flexible Finality
Publisher: IEEE Access, 2023
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Data security and integrity are becoming increasingly important as the volume of data being created and stored grows. A controlled third party that provides most of the existing big data security systems makes them susceptible to several security risks. By resolving current technology challenges, including scalability, non-tampering, trustworthiness, data governance, and transparency, blockchain technology plays a vital role and has a significant potential to safeguard personal information. Therefore, this work focuses on addressing real-time big data storage issues based on a transdisciplinary research approach. This study introduces a brand-new approach to big data storage security that leverages blockchain technology and applies highway protocol to generate new blocks. The proposed highway protocol works based on the flexible finality condition to overcome issues of baseline models. The highway allows blocks to run the consensus mechanism to configure security thresholds more freely. The proposed protocol also allows blocks with lower thresholds to reach finality more quickly than blocks requiring greater degrees of confidence. Therefore, the proposed big data framework can dynamically control data manipulation and continuously support individuals to participate in the data-sharing process. A comparison was performed with the number of data requests in terms of hit ratio, and a highway protocol provides better results than baseline models. The proposed model provides a data processing period of 13 to 30 ms and an energy consumption of 32 to 41 mJ.
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Author: Ajith Abraham
Adaptive variable sampling model for performance analysis in high cache-performance computing environments
Publisher: Heliyon, 2023
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High-performance computing provides computing power for a variety of scientific disciplines, supporting advancements by offering insights beyond metacognition. Maximizing computing performance without wasting resources is a major research issue. Predicting the performance of a computer's next state is effective for scheduling. However, hardware performance monitors representing the computer's state require high expert knowledge, and there is no standardized model. In this paper, we propose an adaptive variable sampling model for performance analysis in high-performance computing environments. Our method automatically classifies the optimal variables from numerous variables related to performance prediction and predicts performance using the sampled variables. The optimal variables for performance analysis do not require expert knowledge during the sampling process. We conducted experiments in various architectures and applications to validate this method. This model performed at least 24.25% and up to 58.75% faster without any loss in accuracy.
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