The study’s only original quantitative analysis is a forecasting exercise built on annual domestic and foreign visitor counts from the Uttar Pradesh State Tourism Department and the Open Government Data Platform India, covering 2016 to 2023. The authors deployed a Long Short-Term Memory (LSTM) recurrent neural network, a deep-learning architecture whose gated memory cells are designed to capture temporal dependencies and non-linear dynamics in sequential data. That choice mattered because the series is anything but a smooth trend: it contains an abrupt structural break in 2020, when the COVID-19 pandemic collapsed arrivals, followed by a sharp, non-linear rebound that culminated in a surge in 2023. Classical linear forecasting methods assume stable trends or seasonal patterns, precisely what this series lacks, which is why the researchers argued that a recurrent architecture was worth trying even on so short a record.

The technical implementation was deliberately transparent about its limits. The eight-year series was Min-Max normalised to the interval between zero and one, with the scaler fitted only on the training partition to prevent information leakage. A sliding-window procedure with a two-year look-back converted the univariate series into six supervised input-output sequences, five for training and a single held-out year, 2023, for testing. The network itself was a stacked LSTM with 64 units, a dropout layer, a second LSTM of 32 units, further dropout, a 16-unit ReLU dense layer and a linear output neuron, compiled with the Adam optimiser and mean squared error loss. Training ran with early stopping and learning-rate reduction callbacks, terminating at epoch 400 with the best weights restored from epoch 201. Because the test set contains only one observation, the reported error metrics are explicitly framed as indicative rather than statistically robust estimates of generalisation.

To keep the deep-learning ambition honest, the team benchmarked the LSTM against three classical baselines on the identical data split: a naïve persistence model that simply repeats the previous year’s value, an ordinary least-squares linear trend model, and a simple exponential smoothing model with a heavily damped smoothing parameter. The comparison proved sobering. The LSTM returned a negative R-squared of minus 0.5370 for domestic visitors, meaning it fell marginally below a naïve mean baseline, while performing better for foreign arrivals. Rather than treating this as a failure, the authors read it as an informative finding: the pandemic collapse, the depressed 2021 figure and the violent post-pandemic rebound broke the temporal regularity on which sequence models depend, so the network could not recover a single stable mapping from past to future years. The 2024 to 2028 projections should therefore be treated as illustrative model-based estimates, not reliable predictions of demand.

What the secondary data do show unambiguously is an economic transformation reported across government and media sources. Hotels, guesthouses and homestays have seen bookings climb sharply during pilgrimage seasons, prompting new lodging construction, while restaurants and eateries catering to diverse visitor preferences have flourished. Small enterprises have been swept along: souvenir shops selling religious artefacts, artisans producing temple-themed merchandise, and transport operators running auto-rickshaws, cycle-rickshaws and taxis have all expanded. The construction phase itself generated employment and stimulated supply chains for building materials, and external investors have poured capital into roads, smart parking and public spaces. The ripple extends into real estate, with rising demand for both residential and commercial space. To contextualise this trajectory, the authors compared Ayodhya’s visitor statistics with three purposively selected North Indian pilgrimage cities, Varanasi, Mathura and Prayagraj, chosen because comparable year-wise visitor data exist for all four. The authors stress this is an illustrative, non-random comparison, and no causal inference about the relative effect of temple construction across cities should be drawn from it.

The urban-planning dimension is equally striking. Ayodhya’s historic layout, in which landmarks such as Hanuman Garhi, Kanak Bhavan and Treta Ke Thakur were interwoven with residential neighbourhoods along narrow, informally arranged lanes, has been reorganised around the Ram Janmabhoomi complex. Major infrastructure projects documented in the study include the 67.17-kilometre Ayodhya Ring Road, an investment of roughly 3,935 crore rupees split between a northern and southern bypass, the widening of the central Ram Path corridor from Sahadatganj to Naya Ghat completed in early 2024 at approximately 700 crore rupees, and a proposed 20-kilometre Bharat Path corridor costing around 900 crore rupees. The major religious sites now form a connected corridor of worship within roughly one to two kilometres of the temple, converging on wider pedestrian and vehicular routes rather than the old lanes, a pattern the authors link to the concept of the ‘sacredscape’ in Indian pilgrimage urbanism.

Water, power and waste systems have been overhauled alongside the roads. New reservoirs, treatment plants and pipelines aim to secure supply for residents and the swelling visitor population, with regular quality testing and sustainability-minded groundwater management, since urbanisation is placing pressure on local aquifers. The electrical grid has been expanded into newly developed areas, with solar power incorporated as a renewable component of generation. Waste management has been scaled up through strategically placed bins, more frequent collection in high-density zones, recycling plants, source-segregation campaigns and sanitary landfill provision for non-recyclable material. The authors also flag an honest data gap: Ayodhya’s last official census population figure is 55,890 from 2011, no newer national census exists, and verified current counts of new water or electrical connections were not available in public sources, a limitation they note explicitly rather than fill with estimates.

The study does not shy away from the project’s contested history and continuing frictions. It traces the dispute from the 1528 construction of the Babri Masjid, through the 1949 idol placement that locked the premises, the 1992 demolition that triggered nationwide communal riots, the Liberhan Commission report, the 2010 Allahabad High Court three-way division of the land, and finally the Supreme Court’s November 2019 verdict that awarded the site for the temple while declaring the demolition a violation of law. On present-day impacts, the authors distinguish between groups: business owners in hospitality, retail and transport generally report rising demand and income, while residents affected by road-widening and land acquisition have raised concerns about displacement, compensation and loss of livelihoods. A cited sentiment analysis of Twitter reactions to the 2019 verdict found responses spanning relief, resignation and continued concern about implications for communal relations, neither uniformly celebratory nor uniformly critical. The authors acknowledge they hold no primary survey data from Ayodhya’s religious-minority residents, and they decline to fill that gap with unsupported claims.

Looking forward, the authors frame Ayodhya’s sustainability challenge through the lens of the UNESCO Recommendation on the Historic Urban Landscape, which treats development in historic cities as managed change requiring sustained stakeholder engagement rather than a one-time construction milestone. Economic gains, they argue, must be distributed equitably across the local population, with social welfare programmes, skill development and measures to prevent displacement of vulnerable and minority communities. Cultural preservation, community participation in decision-making, eco-friendly transport options such as electric and hybrid vehicles, curated nature trails and tourist education programmes all feature in their roadmap. The forecasting exercise, for all its humility about a seven-observation dataset, captures the central tension the city now faces: a visitor economy surging on the back of faith, infrastructure racing to keep up, and a historic landscape whose future depends on whether growth and heritage can be made to evolve together rather than in conflict.

Subject of Research: Socioeconomic, cultural and urban impacts of the Ram Mandir construction on Ayodhya, India

Article Title: Socioeconomic and cultural impacts of ram mandir construction on urban transformation in Ayodhya India

Article References: Choudhury, R., Choudhury, T., Singh, M., Bachute, M., Kandpal, V., & Gite, S. (2026). Socioeconomic and cultural impacts of ram mandir construction on urban transformation in Ayodhya India. Discover Global Society, 4(1), Article 260. https://doi.org/10.1007/s44282-026-00615-z

Image Credits: AI Generated

DOI: 10.1007/s44282-026-00615-z

Keywords: Ayodhya, Ram Mandir, pilgrimage tourism, urban transformation, LSTM forecasting, heritage management, socioeconomic impact, infrastructure development, sustainable tourism, India, historic urban landscape, religious tourism

Across the United States, severe weather events have been shown to precipitate large-scale power outages, leading to significant socioeconomic repercussions. These outages can have dire implications, particularly in times when power is essential for the operation of medical equipment, heating, air conditioning, and other critical services. The ongoing climate crisis serves to exacerbate these challenges, as it increases both the severity and frequency of severe weather events, necessitating a better understanding of the patterns and distributions of power outages to inform community preparedness and resource management.

In this meticulous research effort, the authors, led by Vivian Do, a PhD candidate specializing in environmental health sciences, utilized comprehensive data sets spanning from 2018 to 2020. This extensive investigation focused on over 1,600 counties nationwide, evaluating the correlation between severe weather events—such as rain, snow, extreme heat, intense cold, cyclones, and wildfires—and significant power outages that lasted eight hours or longer. The findings underscored that approximately three-quarters of the analyzed counties experienced major power outages coinciding with severe weather occurrences during the observed three-year span. Alarmingly, over half of these counties dealt with outages associated with multiple simultaneous weather events, illustrating a complex and interlinked system of vulnerability.

The research highlighted that power outages were most frequently linked to severe precipitation and extreme heat, revealing significant regional disparities in the distribution of these outages. For instance, counties in the Northeast U.S. were more prone to precipitation-related outages, whereas heat-related outages were predominantly observed in the Southeast. Additionally, the researchers noted a growing trend of co-occurring outages and wildfires along the West Coast, marking a worrying development that raises important questions about the management of electrical grids in wildfire-prone areas.

Despite the insightful findings presented by Do and her colleagues, it is important to acknowledge the limitations in the data. In particular, reliable data was not uniformly available for all counties, creating gaps in information that left regions such as the Southwest and Mountain West less represented in the study. In light of these limitations, the authors advocate for further research that can provide additional data, as well as realistic simulations of severe weather combinations across diverse geographies, to enhance the capability of municipalities to construct effective mitigation and response strategies.

The implications of this research extend beyond merely identifying problem areas; they delve into the broader societal importance of understanding the interdependencies between infrastructure and environmental factors. In an era when the electrical grid is becoming increasingly antiquated, and as severe weather continues to pose escalating threats, strategies that preemptively address the intersection of severe weather challenges and power failures are crucial. The careful mapping of outage patterns, as highlighted in this study, is fundamental for designing robust systems geared toward minimizing public health risks and economic losses.

Vivian Do emphasized the practical importance of recognizing these patterns, stating: “Power outages frequently co-occur with severe weather events like heavy precipitation, tropical cyclones, or multiple severe weather events simultaneously.” Understanding when and where these phenomena will likely converge is vital for developing strategic responses that can effectively reduce adverse societal consequences. This becomes even more urgent as communities adapt to the realities of a changing climate.

Furthermore, as climate models predict increasingly dramatic shifts in weather patterns, researchers and policymakers must work in tandem to preemptively address the vulnerabilities associated with energy dependence. These insights could be incorporated into future revisions of national response frameworks, ensuring that contingencies are established to protect critical infrastructure in times of weather-related crises. This can also enhance public awareness and preparedness initiatives, ensuring that communities are equipped to handle power loss and its cascading effects.

The study received financial backing from several prominent institutions, including the National Institute for Environmental Health Sciences and the National Institute on Aging, underscoring the broad interest in understanding the health impacts of environmental hazards. Importantly, the funding bodies had no direct influence over the study’s design, data collection, or the conclusions drawn, thereby ensuring the integrity of the research process.

As climate change continues to reshape the landscape, studies such as this one serve as crucial tools for informing public health policies, energy conservation measures, and community resilience planning. The convergence of severe weather events and power outages is not merely an infrastructure issue; it encapsulates broader societal challenges, including equity in public health and the necessity for robust disaster preparedness systems.

As communities across the U.S. grapple with these evolving threats, the findings of this research underscore the imperative of a collective response to strengthen resilience against the dual challenges posed by climate change and electrical grid vulnerabilities. This holistic approach will be essential for safeguarding public health, ensuring equitable access to vital services, and reinforcing the electric grid against the increased strains brought on by an unpredictable climate.

In conclusion, understanding the shifting relationship between severe weather and power outages is not only a scholarly endeavor but a fundamental necessity for fostering community health and safety in an era where extreme weather becomes the norm rather than the exception. The integration of science-informed strategies into community planning will be essential for minimizing disruption and safeguarding the well-being of populations at risk.

Subject of Research: Relationship between severe weather events and power outages.
Article Title: Spatiotemporal patterns of individual and multiple simultaneous severe weather events co-occurring with power outages in the United States.
News Publication Date: 22-Jan-2025.
Web References: PLOS Climate
References: Not provided.
Image Credits: Not provided.

Keywords: Climate data, Environmental health, Electrical power generation, Weather.