348 research outputs found
Response to UK Government’s Department for Energy Security and Net Zero technical consultation on Policy Framework to Grow the Market for Low-Carbon Industrial Products
No full textIn June–September 2025, the UK Government’s Department for Energy Security and Net Zero launched a technical consultation entitled “A Policy Framework to Grow the Market for Low-Carbon Industrial Products.” This consultation solicits stakeholder input on how to design a demand-side policy regime, focused initially on emissions-intensive sectors such as steel, cement, and concrete, to catalyse market growth in low-carbon industrial goods. The document presents aggregated responses and interprets them through the lens of technical analysis conducted by Dr. Gaurav Chand, Research Associate in the Department of Civil Engineering at the University of Manchester
Response to UK Government’s Department for Energy Security and Net Zero technical consultation on Policy Framework to Grow the Market for Low-Carbon Industrial Products
No full textIn June–September 2025, the UK Government’s Department for Energy Security and Net Zero launched a technical consultation entitled “A Policy Framework to Grow the Market for Low-Carbon Industrial Products.” This consultation solicits stakeholder input on how to design a demand-side policy regime, focused initially on emissions-intensive sectors such as steel, cement, and concrete, to catalyse market growth in low-carbon industrial goods. The document presents aggregated responses and interprets them through the lens of technical analysis conducted by Dr. Gaurav Chand, Research Associate in the Department of Civil Engineering at the University of Manchester
First person – Gaurav Barve
No full textABSTRACT
First Person is a series of interviews with the first authors of a selection of papers published in Journal of Cell Science, helping early-career researchers promote themselves alongside their papers. Gaurav Barve is the first author on ‘Septins are involved at the early stages of macroautophagy in S. cerevisiae’, published in Journal of Cell Science. Gaurav is a PhD student in the laboratory of Ravi Manjithaya at Jawaharlal Nehru Centre for Advanced Scientific Research, Bangalore, India, investigating the role of septins in autophagy.</jats:p
Linguistic representations of visual events
No full textThis thesis explores the nature of linguistic representations that correspond to verbal descriptions of events. In two experiments, participants watched captioned videos and decided whether the captions accurately described the videos. In the videos, two geo-metric shapes moved around the screen. [In half of the trials, the geometric shapes had "eyes."] The verbs used to describe the shapes' actions were either source-to-goal verbs (chase, follow, trail ) or goal-to-source verbs (flee, lead, guide). Sometimes the captions were active sentences (e.g., The circle is chasing the square) and sometimes passive sentences (The square is chased by the circle). Analyses of participants' reaction times indicate that the level of linguistic and visual detail encoded reflected the complexity of the task participants had to perform. These results are consistent with "good enough" models of language processing (e.g., Ferreira and Henderson (2007)) in which people process sentences heuristically or syntactically depending on the nature of the task they must perform.M.S.Includes bibliographical referencesby Gaurav Kharkwa
Semantic parsing using lexicalized well-founded grammars
No full textResearch in semantic parsing has focused on developing computational systems capable of simultaneously performing syntactic, i.e. structural, and semantic, i.e., meaning-based, analyses of given sentences. We present an implementation of a semantic parsing system using a constraint-based grammatical formalism called Lexicalized Well-Founded Grammars (LWFGs). LWFGs are a type of Definite Clause Grammars, and use an ontology-based framework to represent syntactico-semantic information in the form of compositional and interpretation constraints. What makes LWFGs particularly interesting is the fact that these are the only constraint-based grammars that are provably learnable. Furthermore, there exist tractable learning algorithms for LWFGs, which make these especially useful in resource-poor language settings. In this thesis, we present a revised parsing implementation for Lexicalized Well-Founded Grammars. Previous work implemented semantic parsers using Prolog, a declarative language, which is slow and does not allow for an easy extension to a stochastic parsing framework. Our implementation utilizes Python's Natural Language Toolkit which not only allows us to easily interface our work with the natural language processing community, but also allows for a future possibility of extending the parser to support broad-coverage and stochastic parsing.M.S.Includes bibliographical referencesby Gaurav Kharkwa
Altered Expression of the CB1 Cannabinoid Receptor in the Triple Transgenic Mouse Model of Alzheimer's Disease
No full textThe endocannabinoid system has gained much attention as a new potential pharmacotherapeutic target in various neurodegenerative diseases, including Alzheimer's disease (AD). However, the association between CB1 alterations and the development of AD neuropathology is unclear and often contradictory. In this study, brain CB1 mRNA and CB1 protein levels were analyzed in 3 × Tg-AD mice and compared to wild-type littermates at 2, 6 and 12 months of age, using in-situ hybridization and immunohistochemistry, respectively. Semiquantitative analysis of CB1 expression focused on the prefrontal cortex (PFC), prelimbic cortex, dorsal hippocampus (DH), basolateral amygdala complex (BLA), and ventral hippocampus (VH), all areas with high CB1 densities that are strongly affected by neuropathology in 3 × Tg-AD mice. At 2 months of age, there was no change in CB1 mRNA and protein levels in 3 × Tg-AD mice compared to Non-Tg mice in all brain areas analyzed. However, at 6 and 12 months of age, CB1 mRNA levels were significantly higher in PFC, DH, and BLA, and lower in VH in 3 × Tg-AD mice compared to wild-type littermates. CB1 immunohistochemistry revealed that CB1 protein expression was unchanged in 3 × Tg-AD at 2 and 6 months of age, while a significant decrease in CB1 receptor immunoreactivity was detected in the BLA and DH of 12-month-old 3 × Tg-AD mice, with no sign of alteration in other brain areas. The altered CB1 levels appear, rather, to be age-and/or pathology-dependent, indicating an involvement of the endocannabinoid system in AD pathology and supporting the ECS as a potential novel therapeutic target for treatment of AD
The role of endocannabinoid signaling in the molecular mechanisms of neurodegeneration in Alzheimer's disease
Get PDFAlzheimer's disease (AD) is the most common form of progressive neurodegenerative disease characterized by cognitive impairment and mental disorders. The actual cause and cascade of events in the progression of this pathology is not fully determined. AD is multifaceted in nature and is linked to different multiple mechanisms in the brain. This aspect is related to the lack of efficacious therapies that could slow down or hinder the disease onset/progression. The ideal treatment for AD should be able to modulate the disease through multiple mechanisms rather than targeting a single dysregulated pathway. Recently, the endocannabinoid system emerged as a novel potential therapeutic target to treat AD. In fact, exogenous and endogenous cannabinoids seem to be able to modulate multiple processes in AD, although the mechanisms that are involved are not fully elucidated. This review provides an update of this area. In this review, we recapitulate the role of endocannabinoid signaling in AD and the probable mechanisms through which modulators of the endocannabinoid system provide their effects, thus highlighting how this target might provide more advantages over other therapeutic targets
Microstructural study of sustainable cements produced from industrial by-products, natural minerals and agricultural wastes: A critical review on engineering properties
No full textA paradigm shift is observed in the production of ordinary Portland cement (OPC) due to its high carbon emission worldwide and the need for adopting sustainability in construction industry. For the same, newer practices have been proposed, which includes the production of sustainable cement whose escalating demand is associated with utilization of different supplementary cementitious materials (SCMs). These SCMs, act as a key component in sustainable construction by emitting lesser carbon. This review endeavors to critically examine the role of different SCMs obtained from industrial by-products, natural minerals and agricultural wastes likes blast furnace slag, silica fume, calcined kaolin, calcined dead burnt magnesite, Ye'elimite, Anhydrite and sugarcane ash in producing sustainable cement and discusses their hydration reactivity at microstructural level. Insights derived from different published research work shows the formation of strength compounds like C–S–H and C-A-S-H which are responsible for improved engineering properties
Aberrant insulin signaling in Alzheimer’s disease: current knowledge
Get PDFAlzheimer’s disease (AD) is the most common form of dementia affecting elderly people. AD is a multifaceted pathology characterized by accumulation of extracellular neuritic plaques, intracellular neurofibrillary tangles (NFTs) and neuronal loss mainly in the cortex and hippocampus. AD etiology appears to be linked to a multitude of mechanisms that have not been yet completely elucidated. For long time, it was considered that insulin signaling has only peripheral actions but now it is widely accepted that insulin has neuromodulatory actions in the brain. Insulin signaling is involved in numerous brain functions including cognition and memory that are impaired in AD. Recent studies suggest that AD may be linked to brain insulin resistance and patients with diabetes have an increased risk of developing AD compared to healthy individuals. Indeed insulin resistance, increased inflammation and impaired metabolism are key pathological features of both AD and diabetes. However, the precise mechanisms involved in the development of AD in patients with diabetes are not yet fully understood. In this review we will discuss the role played by aberrant brain insulin signaling in AD. In detail, we will focus on the role of insulin signaling in the deposition of neuritic plaques and intracellular NFTs. Considering that insulin mitigates beta-amyloid deposition and phosphorylation of tau, pharmacological strategies restoring brain insulin signaling, such as intranasal delivery of insulin, could have significant therapeutic potential in AD treatment
Framework for Investigating Functional Encryption
No full textThesis: M. Eng. in Computer Science and Engineering, Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (pages 95-102).In functional encryption, keys are associated with functions, and ciphertexts with messages. Decrypting a message with a key gives the evaluation of the associated function on that message. We look at bounded-collusion functional encryption, where the number of keys for which security is guaranteed is bounded, as it is possible to realize using standard building blocks. For such schemes we aim to understand their practicality for real-world applications. There are some theoretical constructions of functional encryption, but few implementations. We rectify this by creating the Framework for Investigating Functional Encryption (FIFE). FIFE includes the first implementations for Sahai and Seyalioglu's one-key scheme (CCS 2010), and Gorbunov, Vaikuntanathan, and Wee's bounded-collusion scheme (CRYPTO 2012), and is easily extendable. We used FIFE to evaluate their performance, and to measure the impact of using different public-key or secret-key encryption schemes, bounds on collusion, and security levels, for interesting classes of functions.by Gaurav Singh.M. Eng. in Computer Science and Engineerin
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