Publications by authors named "Vishwanathan Mohan"

Aim: To evaluate the incidence and predictors of postpartum dysglycaemia among high-risk women who develop early gestational diabetes (eGDM) prior to 20 weeks' gestation.

Methods: This is a sub-study of the Treatment of Booking Gestational Diabetes (TOBOGM) Study, a randomised controlled trial of early or deferred treatment for women with risk factors for gestational diabetes diagnosed with eGDM, using current WHO criteria. Overt diabetes in pregnancy was excluded.

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Unlabelled: Multiple interlinked factors like demographics, migration patterns, and economics are presently leading to the critical shortage of labour available for low-skilled, physically demanding tasks like soft fruit harvesting. This paper presents a biomimetic robotic solution covering the full 'Perception-Action' loop targeting harvesting of strawberries in a state-of-the-art vertical growing environment. The novelty emerges from both dealing with crop/environment variance as well as configuring the robot action system to deal with a range of runtime task constraints.

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Introduction: Measures to address the COVID-19 pandemic in India included a ban on the sale and use of tobacco products during 2020 when stay at home guidance (lockdown) was in place. In this study we examined the extent of reduction in frequency of tobacco consumption across all products.

Methods: Telephone survey was conducted between July and August 2020 across an existing cohort of tobacco users (n=801) residing in Delhi (55.

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Aim: Type 2 diabetes (T2D) is a progressive disease characterized by relentless deterioration of pancreatic β-cell function. Traditionally, insulin is used in later stages of T2DM. This study looks at use of insulin at time of diagnosis of T2DM and its effect on glycemic control and beta cell function.

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From social dining in households to product assembly in manufacturing lines, goal-directed reasoning and cooperation with other agents in shared workspaces is a ubiquitous aspect of our day-to-day activities. Critical for such behaviours is the ability to spontaneously anticipate what is doable by oneself as well as the interacting partner based on the evolving environmental context and thereby exploit such information to engage in goal-oriented action sequences. In the setting of an industrial task where two robots are jointly assembling objects in a shared workspace, we describe a bioinspired neural architecture for goal-directed action planning based on coupled interactions between multiple internal models, primarily of the robot's body and its peripersonal space.

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The next generation of robot companions or robot working partners will need to satisfy social requirements somehow similar to the famous laws of robotics envisaged by Isaac Asimov time ago (Asimov, 1942). The necessary technology has almost reached the required level, including sensors and actuators, but the cognitive organization is still in its infancy and is only partially supported by the current understanding of brain cognitive processes. The brain of symbiotic robots will certainly not be a "positronic" replica of the human brain: probably, the greatest part of it will be a set of interacting computational processes running in the cloud.

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Emerging trends in neurosciences are providing converging evidence that cortical networks in predominantly motor areas are activated in several contexts related to 'action' that do not cause any overt movement. Indeed for any complex body, human or embodied robot inhabiting unstructured environments, the dual processes of shaping motor output during action execution and providing the self with information related to feasibility, consequence and understanding of potential actions (of oneself/others) must seamlessly alternate during goal-oriented behaviors, social interactions. While prominent approaches like Optimal Control, Active Inference converge on the role of forward models, they diverge on the underlying computational basis.

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Article Synopsis
  • Pulmonary vein isolation (PVI) is key in treating atrial fibrillation (AF), but many patients still experience arrhythmia recurrence despite advancements in technology.
  • Ablating localized rotational or focal sources of AF outside the pulmonary veins has shown promise in improving treatment success, as these sources have been identified through various studies and mapping techniques.
  • This review highlights the importance of understanding these localized sources, discusses successful ablation techniques, and aims to guide future improvements in individualized treatment approaches for complex arrhythmias.
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Introduction: The role of atrial fibrillation (AF) substrates is unclear in patients with paroxysmal AF (PAF) that recurs after pulmonary vein isolation (PVI). We hypothesized that patients with recurrent post-ablation (redo) PAF despite PVI have electrical substrates marked by rotors and focal sources, and structural substrates that resemble persistent AF more than patients with (de novo) PAF at first ablation.

Methods: In 175 patients at 11 centers, we compared AF substrates in both atria using 64 pole-basket catheters and phase mapping, and indices of anatomical remodeling between patients with de novo or redo PAF and first ablation for persistent AF.

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Emerging studies indicate that several species such as corvids, apes and children solve 'The Crow and the Pitcher' task (from Aesop's Fables) in diverse conditions. Hidden beneath this fascinating paradigm is a fundamental question: by cumulatively interacting with different objects, how can an agent abstract the underlying cause-effect relations to predict and creatively exploit potential affordances of novel objects in the context of sought goals? Re-enacting this Aesop's Fable task on a humanoid within an open-ended 'learning-prediction-abstraction' loop, we address this problem and (i) present a brain-guided neural framework that emulates rapid one-shot encoding of ongoing experiences into a long-term memory and (ii) propose four task-agnostic learning rules (elimination, growth, uncertainty and status quo) that correlate predictions from remembered past experiences with the unfolding present situation to gradually abstract the underlying causal relations. Driven by the proposed architecture, the ensuing robot behaviours illustrated causal learning and anticipation similar to natural agents.

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The body-schema concept is revisited in the context of embodied cognition, further developing the theory formulated by Marc Jeannerod that the motor system is part of a simulation network related to action, whose function is not only to shape the motor system for preparing an action (either overt or covert) but also to provide the self with information on the feasibility and the meaning of potential actions. The proposed computational formulation is based on a dynamical system approach, which is linked to an extension of the equilibrium-point hypothesis, called Passive Motor Paradigm: this dynamical system generates goal-oriented, spatio-temporal, sensorimotor patterns, integrating a direct and inverse internal model in a multi-referential framework. The purpose of such computational model is to operate at the same time as a general synergy formation machinery for planning whole-body actions in humanoid robots and/or for predicting coordinated sensory-motor patterns in human movements.

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The role played by recently discovered novel cytokine IL-33 in controlling T-helper (Th)1 and Th2 cytokines under conditions of diabetic nephropathy (DN) is less well studied. In the present study, we estimated the levels of IL-33 along with both Th1 and Th2 cytokines in the serum of normal glucose tolerant (NGT), diabetic subjects with (DN) or without nephropathy (DM) and correlated it with the clinical risk factors of diabetes and nephropathy. 222 study subjects were recruited from the Chennai Urban Rural Epidemiology Study (CURES): 61 NGT, 79 DM and 82 DN.

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Cumulatively developing robots offer a unique opportunity to reenact the constant interplay between neural mechanisms related to learning, memory, prospection, and abstraction from the perspective of an integrated system that acts, learns, remembers, reasons, and makes mistakes. Situated within such interplay lie some of the computationally elusive and fundamental aspects of cognitive behavior: the ability to recall and flexibly exploit diverse experiences of one's past in the context of the present to realize goals, simulate the future, and keep learning further. This article is an adventurous exploration in this direction using a simple engaging scenario of how the humanoid iCub learns to construct the tallest possible stack given an arbitrary set of objects to play with.

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This article presents results from a multidisciplinary research project on the integration and transfer of language knowledge into robots as an empirical paradigm for the study of language development in both humans and humanoid robots. Within the framework of human linguistic and cognitive development, we focus on how three central types of learning interact and co-develop: individual learning about one's own embodiment and the environment, social learning (learning from others), and learning of linguistic capability. Our primary concern is how these capabilities can scaffold each other's development in a continuous feedback cycle as their interactions yield increasingly sophisticated competencies in the agent's capacity to interact with others and manipulate its world.

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Article Synopsis
  • The text presents an integrated model for coordinating whole body movements in a humanoid robot that mimics human mechanics, particularly focusing on a compliant ankle.
  • It features a synergy formation component to handle the body's motor redundancy effectively.
  • Additionally, it incorporates an intermittent controller that stabilizes postural sway, merging both hip and ankle strategies for improved balance.
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  • Continued increases in type 2 diabetes prevalence and related healthcare costs highlight the need for improved prevention and treatment policies.
  • Four key policy shifts are proposed: integrating prevention strategies along a clinical continuum, emphasizing early detection of prediabetes and undiagnosed diabetes for cost-effective solutions, combining community and clinical resources for organized care, and promoting evidence-based policies globally.
  • A focus on these shifts aims to better address type 2 diabetes and its implications for healthcare systems.
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  • Optimal Control Theory (OCT) has become a key method in studying how the brain controls movement and motor cognition, addressing challenges like the "degrees of freedom" problem in both behavioral neuroscience and humanoid robotics.
  • The authors present an alternative approach called the Passive Motion Paradigm (PMP), which emphasizes internal simulations and the body’s biomechanical dynamics rather than complex calculations to resolve motor tasks.
  • They suggest that this new perspective, informed by advancements in neuroscience and robotics, can enhance our understanding of motor cognition, moving beyond the traditional engineering-focused OCT framework.
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Several animal studies have shown a protective effect of helminth infections against type-1 diabetes mellitus (T1DM). However, epidemiologic studies demonstrating this protective relationship with T1DM are largely lacking, although an inverse correlation between the prevalence of lymphatic filariasis (LF) and prevalence of allergies and autoimmunity has been shown. A cross-sectional study was undertaken in southern India to assess the baseline prevalence of seropositivity of LF among persons with T1DM (n = 200) and normal glucose tolerant (NGT) persons (n = 562).

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  • This study examined the link between cystatin-C levels and the severity of metabolic syndrome in Asian Indians.
  • Five groups of participants with varying numbers of metabolic risk factors were analyzed, with serum cystatin-C levels measured and found to decrease as the number of risk factors decreased.
  • The results indicated that higher cystatin-C levels are strongly associated with more metabolic abnormalities, suggesting it could be a useful biomarker for assessing metabolic syndrome severity in this population.
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Background: This study assessed the relationship between and risk factors for microvascular complications of diabetes in an urban South Indian type 2 diabetes population.

Methods: Subjects with diabetes (n = 1,736) were selected from the population-based Chennai Urban Rural Epidemiology Study (CURES) Eye Study conducted on a representative population of Chennai city in south India. Four-field stereo retinal color photography was done, and diabetic retinopathy (DR) was classified according to the Early Treatment DR Study grading system.

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Article Synopsis
  • The study was conducted in Muthialpet, Pondicherry, analyzing diabetes risk among a population of 40,000 using the Indian Diabetes Risk Score from July to October 2007, involving 616 participants (53% female, 47% male).
  • A significant portion of participants (85%) were Hindu, with 62% having completed higher secondary education and 87% from upper middle to upper socioeconomic backgrounds, while 68% were over 35 years old.
  • Findings revealed that 90.5% engaged in mild to moderate physical activity, 51% were overweight, and the prevalence of diabetes was 8.27%, particularly high among individuals with elevated BMI and high IDRS scores, indicating a direct correlation between
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Background: Epidemiological studies in India have shown that the prevalence of diabetes in the population is at least twice the number of persons diagnosed with diabetes residing in the given area. Similarly, community-based prevalence figures are unavailable in Puducherry,.

Aims: The aim of this study was to estimate the number of persons diagnosed with diabetes mellitus in Puducherry.

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The present study proposes a computational model for the formation of whole body reaching synergy, i.e., coordinated movements of lower and upper limbs, characterized by a focal component (the hand must reach a target) and a postural component (the center of mass must remain inside the support base).

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