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Accurate prediction of the structural condition of urban critical infrastructure is crucial for predictive maintenance. However, the existing prediction methods lack precision due to limitations in utilizing heterogeneous sensing data and domain knowledge as well as insufficient generalizability resulting from limited data samples. This paper integrates implicit and qualitative expert knowledge into quantifiable values in tunnel condition assessment and proposes a tunnel structure prediction algorithm that augments a state-of-the-art attention-based long short-term memory (LSTM) model with expert rating knowledge to achieve robust prediction results to reasonably allocate maintenance resources.

Through formalizing domain experts' knowledge into quantitative tunnel condition index (TCI) with analytic hierarchy process (AHP), a fusion approach using sequence smoothing and sliding time window techniques is applied to the TCI and time-series sensing data. By incorporating both sensing data and expert ratings, an attention-based LSTM model is developed to improve prediction accuracy and reduce the uncertainty of structural influencing factors.

The empirical experiment in Dalian Road Tunnel in Shanghai, China showcases the effectiveness of the proposed method, which can comprehensively evaluate the tunnel structure condition and significantly improve prediction performance.

This study proposes a novel structure condition prediction algorithm that augments a state-of-the-art attention-based LSTM model with expert rating knowledge for robust prediction of structure condition of complex projects.

The study aims to analyze the impact of market participation on small paddy farmers' income and consumption expenditure. The study also estimates various determinants affecting the market participation of smallholders. Further, the study computes the efficiency of different paddy marketing channels and identifies the determinants that impact the marketing channel selection of paddy growers in Eastern India.

The study used the propensity score matching (PSM) approach to measure the impact of market participation on farm income and per capita consumption. Further, the study employed Acharya and Aggarwal's composite index approach to estimate the marketing efficiency of various paddy marketing channels. Further, a multinomial logit model was used to determine the marketing channel selection constraints.

The outcomes indicate that market participation positively impacts farm income and consumption expenditure. Education, membership in farmers' organizations, price information and distance to the marketplace significantly affect farmers' market participation. The results show that the producer–retailer marketing channel is the most efficient compared to others. However, most paddy farmers sell paddy to farmgate collectors due to a lack of market information, vehicle ownership, storage system, and inability to take the risk of venturing out of the farmgate into markets.

The study uses primary data and captures only farmers' perspectives to measure the impact of market participation, marketing channel efficiency and determinants for market channel selection. The other stakeholder's perceptions can be included in future studies.

Rarely does any study identifies the efficiency of different marketing channels for paddy farmers in India and includes cognitive factors like risk perception and trust in buyers as constraints for market channel selection.

This paper aims to map the evolution of hydrogen-based technologies (HBTs) by examining the patenting activity associated to these technlogies from 1930 to 2020. In doing so, the study provides a novel perspective on the development of HBTs and offers implications for managers and policymakers.

We collected patent data at the level of patent families (PFs). Our sample includes 317,089 PFs related to hydrogen production and 62,496 PFs to hydrogen storage. We examined PF data to delineate the state of the art and major technical advancements of HBTs.

Our analysis provides evidence of an increasing patenting activity in the area of HBTs, hence suggesting relatively high levels of expectations on the economic potential of these technologies. US and Japan hold the largest proportion of PFs related to HBTs (about 60%), while European applicants hold the highest proportion of highly cited PFs (about 60%). While firms represent the applicant with the highest share of PFs, our analysis reveals that firms holding HBT PFs are primarily from the chemical sector.

While our analysis is limited to examining patent data which capture some aspects of the innovation activity around HBTs (namelly, patented inventions), our study enriches existing literature by performinng a patent analysis on a much larger sample of data when compared to previous studies.

Two main implications emerge from our study. Firstly, there seems to be an urgent need to support the emergence of a dominant design so as to facilitate the consolidation and diffusion of the HBTs, hence the transition to a more sustainable energy production. Secondly, the majority of HBT PFs are held by a small number of countries. This, in turn, suggests opportunities to develop cross-country cooperation (e.g. international agreements, research and technology offices) to support the development and adoption of HBTs globally.

Considering the results obtained in this study, from a social point of view, the attention that organizations have paid to hydrogen related technologies is evident. This suggests that the development HBTs can function as a social enabler for a sustianable energy transition.

Extant research has focused on the individual components of the hydrogen chain. As a result, we lack a comprehensive understanding of the progress made in the area of HBTs. To address this gap, this study examined HBTs by focusing on both production and storage technologies since their initial developments, hence adopting an observation period of about 70 years.