Corporate performance is the key indicator of availing the economic performances in all economies. Especially for the emerging economy, it is the oxygen for smooth economic operations. The study aims to investigate the influence of board characteristics on the corporate performance of the listed pharmaceuticals and chemicals sector from a developing country, namely Bangladesh. This empirical study examines eight attributes of the board and four financial performance indicators of the businesses. Here, the annual reports of the DSE-listed pharmaceutical and chemicals companies are considered to examine the impact of board attributes on corporate performance. Based on panel data analysis, this empirical study concludes that the fixed effect regression model is suitable for all four models. Except board size, the results demonstrate that all board attributes are generally statistically significant. Furthermore, it confirms that all the significant characteristics of the board are positively associated with corporate performance, except for board independence. The research offers valuable insights for policymakers, investors, organizations, and scholars, promoting optimal board structures, innovative solutions, and an enhanced understanding of corporate governance matters. This research explores the challenges in board attributes, which enhances our understanding of corporate governance matters and their impact over the last decade in the listed pharmaceutical and chemicals sectors in Bangladesh.

Our study investigates the relationship between firm profitability, board characteristics, and the quality of sustainability disclosures, while examining the moderating effects of financial leverage and external audit assurance. A key focus is the distinction between Big 4 and non-Big 4 audit firms. Using data from Malaysia’s top 100 publicly listed organizations from 2018 to 2020, we analyze sustainability reports based on the Global Reporting Initiative (GRI) standards. Unexpectedly, our results indicate a negative association between firm profitability and board characteristics, challenging traditional assumptions. We find that non-Big 4 audit firms significantly enhance sustainability disclosure quality, contradicting the widely held belief in the superiority of Big 4 firms. Our finding introduces the “Big 4 dilemma” in the Malaysian context and calls for a reassessment of audit firm selection practices. Our study offers new perspectives on the strategic role of board composition and audit firm selection in advancing sustainability disclosures, urging Malaysian organizations to evaluate audit firms on criteria beyond the global prestige of Big 4 firms to improve sustainability reporting.

Cross-border ecological cooperation is always a challenging issue. Ecological cooperation in the Guangdong-Hong Kong-Macao Greater Bay Area has its own uniqueness as it is cross-border cooperation under “One Country, Two Systems”, which is different from multinational cooperation or regional collaboration within one country. This paper analyses the cooperation documents of Guangdong, Hong Kong and Macao, official reports and academic literature, and then summarises the unique pattern of ecological cooperation in the Greater Bay Area under “One Country, Two Systems”. It outlines four characteristics: different priorities in ecological management of each side, case by base cooperation, government-dominated cooperation with low public participation, and huge institutional gap between three sides. This article also identifies several problems and causes: lack of common ecological targets for each side and effective cross-border regulative measures, cumbersome coordination in cross-border cooperation. Finally, four feasible recommendations have been put forwarded: creating new institutional arrangements under the context of “One Country, Two Systems”, establishing the efficient decision-making platform for the inter-city cooperation, introducing the market-based resource allocation, and encouraging public participation in ecological monitoring.

Nanoscale zero-valent iron (nZVI) is thought to be the most effective remediation material for contaminated soil, especially when it comes to heavy metal pollutants. In the current high-industrial and technologically advanced period, water pollution has emerged as one of the most significant causes for concern. In this instance, silica was coated with zero-valent iron nanoparticles at 650 and 800 ℃. Ferric iron with various counter-ions, nitrate (FN) and chloride (FC), and sodium borohydride as a reducing agent were used to create nanoscale zero-valent iron in an ethanol medium with nitrogen ambient conditions. X-ray diffraction (XRD) and field emission scanning electron microscopy (FE-SEM) techniques were employed to describe the structures of the generated zero-valent iron nanoparticles. Further, we investigated the electrical properties and adsorption characteristics of dyes such as alizarin red in an aqueous medium. As a result, zero-valent nano iron (nZVI), a core-shell environmental functional material, has found extensive application in environmental cleanup. The knowledge in this work will be useful for nZVI-related future research and real-world applications.

We report on the measurement of the response of Rhodamine 6G (R6G) dye to enhanced local surface plasmon resonance (LSPR) using a plasmonic-active nanostructured thin gold film (PANTF) sensor. This sensor features an active area of approximately ≈ 2.5 × 10¹³ nm² and is immobilized with gold nanourchins (GNU) on a thin gold film substrate (TGFS). The hexane-functionalized TGFS was immobilized with a 90 nm diameter GNU via the strong sulfhydryl group (SH) thiol bond and excited by a 637 nm Raman probe. To collect both Raman and SERS spectra, 10 μL of R6G was used at concentrations of 1 μM (6 × 10¹² molecules) and 10 mM (600 × 10¹⁴ molecules), respectively. FT-NIR showed a higher reflectivity of PANTF than TGFS. SERS was performed three times at three different laser powers for TGFS and PANTF with R6G. Two PANTF substrates were prepared at different GNU incubation times of 10 and 60 min for the purpose of comparison. The code for processing the data was written in Python. The data was filtered using the filtfilt filter from scipy.signals, and baseline corrected using the Improved Asymmetric Least Squares (ISALS) function from the pybaselines.Whittaker library. The results were then normalized using the minmax_scale function from sklearn.preprocessing. Atomic force microscopy (AFM) was used to capture the topography of the substrates. Signals exhibited a stochastic fluctuation in intensity and shape. An average corresponding enhancement factor (EF) of 0.3 × 10⁵ and 0.14 × 10⁵ was determinedforPANTFincubated at 10 and 60 min, respectively.