PurposeAs the race toward net-zero intensifies, manufacturing firms are rethinking how innovation can serve as a catalyst for sustainable transformation. This study explores how ambidextrous green innovation, integrating both exploratory and exploitative innovation strategies enables small- and medium-sized enterprises (SMEs) to achieve net-zero based green performance. Drawing on dynamic capabilities theory, the study constructs and empirically tests a conceptual framework that connects innovation ecosystem engagement, innovation capability and ambidextrous green innovation. It further examines how the broader innovation ecological environment enhances these relationships and supports sustainability outcomes.Design/methodology/approachData were gathered through a three-wave, time-lagged survey from Chinese manufacturing SMEs. The proposed hypotheses were tested using Hayes' PROCESS macro, allowing for robust analysis of both mediation and moderation effects.FindingsThe results confirm that strong collaborative linkages with core organizations and service intermediaries significantly enhance innovation capabilities. Moreover, a supportive innovation ecological environment strengthens the influence of innovation capability on ambidextrous green innovation. In turn, ambidextrous green innovation contributes positively to net-zero based green performance.Originality/valueThis study provides a novel theoretical integration by linking innovation ecosystem, innovation capability and ambidextrous green innovation within the framework of dynamic capabilities theory. It extends the literature by empirically demonstrating how these constructs jointly influence net-zero based green performance in SMEs. Additionally, it highlights the contextual importance of the innovation ecological environment in strengthening the pathway from innovation capability to ambidextrous green innovation, offering valuable insights for both theory and managerial practice in sustainability-driven innovation.
PurposeThe research aim was to work on the discrepancies and ambiguities that have emerged with the application of individual multi-criteria decision-making (MCDM) methods in the determination of key factors in sustainable supply chain management. It aims at improving reliability of the decision-making process by suggesting an aggregation procedure to combine the various decision outcomes.Design/methodology/approachSeveral decision methods, including analytic hierarchy process (AHP), best-worst method (BWM) and fuzzy AHP, were employed to assess and rank the factors for achieving sustainability in steel supply chain. These methods produce different ranking since they make different assumptions, have different preference structures and different data processing mechanisms. To counter this, we made use of the half quadratic (HQ) theory to enable us to compile these rankings. HQ-based method combines varying expert estimation and methodological opinion into single final ranking.FindingsThe HQ-based aggregation can improve consistency and sturdiness of the final ranking; it eliminates the difference in approach. This method facilitates stable and consistent decision-making and helps in consistent strategic planning and policy making of sustainable supply chain management.Originality/valueThe novelty of this study lies in the use of HQ theory in aggregating the ranking based on two or more decision-making methods. It shows how this method is effective in eliminating the uncertainty that comes with single method methods as well as reveals how aggregating is important in enhancing the validity of MCDM in the use of sustainability in analysing a supply chain.
Designing efficient, stable, and environmentally friendly metal-free electrocatalysts is a significant challenge in the development of next-generation clean energy systems. In this study, a novel D-A type organic small molecule, 2,3,6,7-tetra(thiophen-2-yl)quinoxaline (TTQx), was designed and synthesized to act as a metal-free bifunctional electrocatalyst, which was effectively active in both the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER). This study experimentally investigated the thermal, optical, and electrochemical properties of the TTQx molecule, which were complemented by DFT-derived HOMO and LUMO energy levels. Electrostatic surface potential (ESP) mapping and structural analysis of a high-quality TTQx single crystal were performed to interpret the charge-density distributions and reveal the atomic-level characteristics governing the active sites for the HER and OER. TTQx demonstrated outstanding catalytic performances in various electrolytes, namely, 0.5 M H2SO4, 1.0 M KOH, and 1.0 M PBS, with low HER overpotentials of -108, -152, and -163 mV and OER overpotentials of 233, 251, and 271 mV at 10 mA cm-2, respectively. Remarkably, TTQx maintained a high catalytic activity for over 24 hours of continuous operation in all electrolytes, with minimal degradation. Furthermore, TTQx-based devices delivered a current density of 10 mA cm-2 at low cell voltages of 1.66 V in H2SO4, 1.76 V in KOH, and 1.79 V in PBS while maintaining a stable overall water splitting performance for over 70 hours. Notably, the superior performance of TTQx under acidic conditions highlighted the durability of this organic small molecular electrocatalyst. This work establishes an entirely metal-free electrocatalyst based on a pi-extended organic small molecule that efficiently drives both the HER and OER, highlighting the potential of pi-conjugated heterocycles for sustainable green hydrogen production via water splitting process.
This study investigates the inhibitory effects of 5 bioactive compounds isolated from Fernandoa adenophylla on two key enzymes involved in neurodegenerative diseases, Beta-secretase 1 (BACE-1) and monoamine oxidase-B (MAO-B). The compounds, namely lapachol (1), alpha-lapachone (2), peshawaraquinone (3), dehydro-alpha-lapachone (4), and the indanone derivative methyl 1,2-dihydroxy-2-(3-methylbut-2-enyl)-3-oxoindene-1-carboxylate (5) were tested in vitro and investigated by means of computational tools. Lapachol (1) resulted to be the most effective BACE-1 inhibitor of the set, while peshawaraquinone (3) strongly inhibited MAO-B. Enzyme kinetic analyses were carried out, and the inhibitory mechanisms were also elucidated. Molecular docking studies showed that the compounds target key residues in the active sites of the enzymes and density functional theory (DFT) investigation suggested a higher reactivity of lapachol (1) towards electron transfer. Overall, the findings support the potential role of these natural compounds as BACE-1 and MAO-B inhibitors.
Supernumerary Robotic Fingers (SRFs) have proven their capabilities in enhancing manipulation and dexterity in precision tasks enabling multitasking in healthy individuals, while also playing a compensatory role for those with motor impairments. However, the literature on SRF adaptation and embodiment remains scarce, particularly in terms of the neurophysiological basis underlying their introduction, use, and assimilation. This study employed a controlled-time-delay-stability (CTDS) framework to investigate physiological embodiment by capturing multimodal signals (encephalography (EEG), electrodermal-activity (EDA), photoplethysmography (PPG), and respiratory) in 30 adults performing three activities-of-daily-living. Tasks were completed across three phases: without SRF, with SRF immediately after attachment, and with SRF following individualized training. CTDS quantified pairwise strength and directionality of dynamic interactions while controlling for indirect effects. Network visualization provided a holistic view of brain-body reconfiguration with SRF use. Resting baselines showed no significant differences across phases, suggesting SRF attachment alone did not introduce sufficient stress to alter brain-body interactions. During tasks, brain-body interactions exhibited task-dependent modulation. This modulation was suppressed with initial SRF attachment but reappeared after training/familiarization, with post-training patterns becoming statistically indistinguishable from those without the SRF. These results indicate that SRFs can be effectively embodied into the body schema after targeted training. The transient plasticity observed in first-time users may serve as a biomarker for customizing SRF training and tracking neurorehabilitation progress. Extending prior findings of rapid cortical adaptation, this study shows that brain-body networks reconfigure in a task-specific manner toward assimilation following brief familiarization. Future work warrants clinical validation and translation.
