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The purpose of this paper is to improve the generation efficiency of singlet oxygen of methylene blue molecules through finely controlling their aggregation states in drug carriers.

As a photosensitiser in photodynamic therapy, methylene blue (MB) was loaded on citrate-modified hydroxyapatite (HAp) through an electrostatic interaction and followed by encapsulation of coordination complexes of tannic acid (TA) and Fe(III) ions. Ultraviolet-visible absorption spectrum of the supernatant after incubation of samples was recorded at certain time interval to investigate the release behaviour of MB. Photodynamic activity of MB was determined by the oxidation reaction of uric acid by singlet oxygen generated by MB under illumination.

Almost all MB molecules were immediately released from HAp-MB, whilst an initial burst release of MB from HAp-MB@TA was followed by a sustainable and pH-sensitised release. In comparison with HAp-MB, photocatalystic reduction of HAp-MB@TA by titanium dioxide hardly occurred under illumination, indicating the stability against reduction to leukomethylene blue in vitro. Generation efficiency of singlet oxygen by MB released from HAp-MB@TA was significantly higher than that from HAp-MB because of the control of TA and Fe(III) ions complexes on molecular structures of released MB.

A facile method was herein demonstrated to optimise the generation efficiency of singlet oxygen by controlling aggregation states of PS molecules and improve PDT efficiency to damage tumour tissues.

This study employs bibliometric analysis to map the research landscape of social media trending topics during the COVID-19 pandemic. The authors aim to offer a comprehensive review of the predominant research organisations and countries, key themes and favoured research methodologies pertinent to this subject.

The authors extracted data on social media trending topics from the Web of Science Core Collection database, spanning from 2009 to 2022. A total of 1,504 publications were subjected to bibliometric analysis, utilising the VOSviewer tool. The study analytical process encompassed co-occurrence, co-authorship, citation analysis, field mapping, bibliographic coupling and co-citation analysis.

Interest in social media research, particularly on trending topics during the COVID-19 pandemic, remains high despite signs of the pandemic stabilising globally. The study predominantly addresses misinformation and public health communication, with notable focus on interactions between governments and the public. Recent studies have concentrated on analysing Twitter user data through text mining, sentiment analysis and topic modelling. The authors also identify key leading organisations, countries and journals that are central to this research area.

Diverging from the narrow focus of previous literature reviews on social media, which are often confined to particular fields or sectors, this study offers a broad view of social media's role, emphasising trending topics. The authors demonstrate a significant link between social media trends and public events, such as the COVID-19 pandemic. The paper discusses research priorities that emerged during the pandemic and outlines potential methodologies for future studies, advocating for a greater emphasis on qualitative approaches.

The peer-review history for this article is available at: https://publons.com/publon/10.1108/OIR-05-2023-0194.

The purpose of this paper is to present a novel image sensor technology for raised characters based on line structured‐light. It can convert raised character's three‐dimensional (3D) features into image's grayscale levels.

The measurement principle and mathematical model are described. An experimental device is established and system parameters are calibrated. A grayscale conversion algorithm is proposed to convert the distortion of laser stripe to the grayscale intensity of image. The article also introduces a four‐factor method to assess the image quality of characters.

Experimental results show that the method can get high‐contrast images of raised characters that are conventionally low‐contrast with the background. Besides, the method does not need complicated calibration and mass computation, which makes the system structure simple and increases the speed of image acquisition.

The paper presents a novel image acquisition method for raised characters.

Institutional trust is vital for social and economic activity and crucial in reducing uncertainty for entrepreneurs and society. To shed light on the role of institutional trust on productive entrepreneurial activity, this paper analyses the impact of six urban entrepreneurial ecosystems (EEs) using the contexts of the transition economies of Eastern Europe, Caucasus and Central Asia. This study aims to pursue the research question: what role does institutional trust play in the relationship between formal institutions and productive entrepreneurship in the EEs of transition economies? This paper aims to posit that the development and enforcement of formal institutions and institutional trust enhance productive entrepreneurship.

In this study, the authors apply a mixed-method approach. The authors’ dataset includes 657 respondents (ecosystem stakeholders) from six city-level entrepreneurial ecosystems in the transition economies of Georgia, Ukraine and Kazakhstan, as well as 51 semi-structured interviews from EE representative stakeholders to examine the validity of the findings.

Institutional trust in many cities has been negatively affected by institutionalised corruption and continuous non-transparent reforms, furthering prior research in developing and transition economies. The authors’ findings suggest that institutional trust can be investigated not as a country phenomenon but as a regional phenomenon extending prior research towards understanding the institutional trust – productive entrepreneurship research domain at the city EE level.

The authors apply the institutional trust perspective to the EEs in cities in order to examine how institutional trust affects productive entrepreneurship in challenging institutional environments. The authors contribute to the literature on institutions and entrepreneurship by using a mixed-method analysis to examine the relationship between formal institutions and institutional trust in the context of EEs in transition economies.

The paper examines whether, along with the financial performance, the disclosure of research and development (R&D) expenses, patent portfolios, patent citations and innovation activities affect the market capitalization of Russian companies.

The paper opted for a set of techniques including bag-of-words (BoW) to retrieve additional innovation-related data from companies' annual reports, self-organizing maps (SOM) to perform visual exploratory analysis and panel data regression (PDR) to conduct confirmatory analysis using data on 74 Russian publicly traded companies for the period 2013–2019.

The paper observes that the disclosure of nonfinancial data on R&D, patents and primarily product and marketing innovations positively affects the market capitalization of the largest Russian companies, which are mainly focused on energy, raw materials and utilities and are operating on international markets. The study suggests that these companies are financially well-resourced to innovate at risk and thus to provide positive signals to stakeholders and external agents.

Our findings are important to management, investors, financial analysts, regulators and various agencies providing guidance on corporate governance and sustainability reporting. However, the authors acknowledge that the research results may lack generalizability due to the sample covering a single national context. Researchers are encouraged to test the proposed approach further on other countries' data by using the compiled lexicons.

The study aims to expand the domains of signaling theory and market valuation by providing new insights into the impact that companies' reporting on R&D, patents and innovation activities has on market capitalization. New nonfinancial factors that previous research does not investigate – innovation disclosure indicators (IDI) – are tested.

The study aims to discover the spatial relationship between financial development, energy consumption and economic growth in 11 ASIA countries, using panel data from 1980 to 2016.

The study applies three popular spatial models, namely, (1) spatial error model (SEM), (2) spatial autoregressive model (SAR) and (3) spatial Durbin model (SDM), to explore the direct and spillover effect of financial development and energy consumption on economic growth. Furthermore, a novel test proposed by Juodis et al. (2020) is employed to check the Granger non-causality between each pair of variables.

The empirical outcomes found direct and spillover effects of financial development and energy consumption on economic growth in 11 ASIA countries. Accordingly, an expansion of the financial development in country i is beneficial for the growth of the host country and neighboring countries, and vice versa. However, an increase in energy consumption in country i leads to a decrease in the economic growth of neighboring countries. The test of Granger non-causality indicated a bidirectional causality between financial development and economic growth, and unidirectional causality running from economic growth to energy consumption.

Spillover effects of financial development and energy consumption on growth have largely been ignored in previous studies, especially in emerging countries. Thus, the study enriches the literature and provides some policy implications for ASIA countries.

Spillover effects of financial development and energy consumption on growth have largely been ignored in previous studies, especially in emerging countries. Thus, the study enriches the literature and provides some policy implications for ASIA countries.

Spillover effects of financial development and energy consumption on growth have largely been ignored in previous studies, especially in emerging countries. Thus, the study enriches the literature and provides some policy implications for ASIA countries.

This paper aims to uncover the significance of capacity, capacity utilization (CU) and its role in the quality and productivity improvement in an industrial environment. Besides, the current study is also aiming to explore the various ways to estimate CU and its status across the world.

In the present study, a comprehensive literature review on capacity and CU is carried out to expose the research direction in the field of CU. This work is primarily focused on capacity, CU and their estimation methods based on the research in various industries of different countries and current status in present scenario across the world.

The literature reveals that CU estimation is carried out by some government/central agencies at the national or sector level rather than the industry level in most of the productive nations. As far as industrial growth is concerned, capacity management should be carried out at a particular industry level so that engineering managers can be able to find out loopholes for huge capacity waste within the plant. It is observed that CU in the industrial sectors mainly computed by time series method, survey method, economic approach and engineering approach worldwide.

This paper tries to cover almost all research work in the field of CU in various industrial sectors. However, the organizations which are producing the product with limited demand may get benefit inadequately.

This paper provides a vision to management toward productivity improvement through optimal utilization of available resources. As in most organizations, CU issues are much neglected areas.

This paper provides valuable insights on capacity and CU in the industrial sector across the world. Besides, it focused on comprehensive literature of capacity and various methods to estimate CU in industrial sectors.