PurposeThis study examines the role of financial service providers (FSPs) in assessing the supply chain credit of small and medium-sized enterprises (SMEs) and how they help SMEs obtain supply chain finance (SCF) through an established digital platform using big data analytics (BDA).Design/methodology/approachThis study conducted data mining analysis on the archival data of China's FSPs in the mobile production industry from 2015 to 2018, using neural networks in the first stage and multiple regression in the second stage.FindingsThe findings suggest that digital platforms sponsored by FSPs have a discriminative effect based on implicit BDA on identifying the quality and potential risks of borrowers. The results also show that tailored information utilised by FSPs has a supportive effect based on explicit BDA in helping SMEs obtain financing.Originality/valueThis study contributes to the emergent research on BDA in supply chain management by extending the contextual research on information signalling and platform theory in SCF. Furthermore, it examines the distinctive financing decision models of FSPs and provides a solution that addresses the information deficiency and overload of both lenders and borrowers and plays a certain reference role in alleviating the financing problems of SMEs.

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Microalgae are one of the most promising renewable energy sources with environmental sustainability. The surface free energy of microalgal cells determines their biofouling and bioflocculation behavior and hence plays an important role in microalgae cultivation and harvesting. To date, the surface energetic properties of microalgal cells are still rarely studied. We developed a novel spectrophotometric method for directly determining the surface free energy of microalgal cells. The principles of this method are based on analyzing colloidal stability of microalgae suspensions. We have shown that this method can effectively differentiate the surface free energy of four microalgal strains, i.e., marine Chlorella sp., marine Nannochloris oculata, freshwater autotrophic Chlorella sp., and freshwater heterotrophic Chlorella sp. With advantages of high-throughput and simplicity, this new spectrophotometric method has the potential to evolve into a standard method for measuring the surface free energy of cells and abiotic particles.

In vivo monitoring of cerebral pH is of great significance because its disturbance is related to some pathological processes such as neurodegenerative diseases, for example, Parkinson's disease (PD). In this study, we developed an electrochemical microsensor based on poly(melamine) (P Mel ) films for ratiometric monitoring of pH in subacute PD mouse brains. In this microsensor, P Mel films were prepared from a simple electropolymerization approach in a melamine-containing solution, serving as the selective pH recognition membrane undergoing a 2H + /2e − process. Meanwhile, electrochemically oxidized graphene oxide (EOGO) produced a built-in correction signal which helped avoid the environmental interference of the complicated brain systems. The potential difference between the peaks generated from EOGO and P Mel gradually decreased with the aqueous pH increasing from 4.0 to 9.0, constituting the detection foundation of the ratiometric electrochemical microsensor (REM). The in vitro studies demonstrated that this proposed method exhibited a high sensitivity (a Nernstian response of −61.35 mV/pH) and remarkable selectivity against amino acids, anions, cations, and biochemical and reactive oxygen species coexisting in the brain. Coupled with its excellent stability and reproducibility and good antibiofouling based on short-term detection, the developed REM could serve as a disposable sensor for the determination of cerebral pH in vivo. Its following successful application in the real-time measurement of pH in the striatum, hippocampus, and cortex of rat brains in the events of global cerebral ischemia/reperfusion verified the reliability of this method. Finally, we adopted this robust REM to systematically analyze and compare the average pH in different regions of normal and subacute PD mouse brains.

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