Implications of buy-online-and-assemble-in-store approach for firms, consumers and environment
Peer-Reviewed Publication
Updates every hour. Last Updated: 17-May-2025 23:10 ET (18-May-2025 03:10 GMT/UTC)
By building a game-theoretic model, researchers have found that a larger proportion of professional consumers can incentivize firms to adopt the buy-online-and-assemble-in-store (i.e., BOAS), while higher handling or traveling costs may lead firms to avoid its use. This study not only contributes to the existing literature, but also provides actionable insights for practitioners.
This study develops an Au-catalyzed strategy for constructing atomically rough surfaces (ARSs) on AuPd/AuAg alloys through sequential nanoalloy synthesis and Au-site-triggered metal ion reduction. The ARSs combine low-coordinated atoms and Au-induced ligand effects, achieving exceptional ethanol oxidation (EOR) performance in alkaline media. The optimized AuPd-Pt ARSs exhibit record EOR activity (14.9 mA cm⁻² specific, 28.5 A mg⁻¹ mass activity), surpassing commercial Pd/C and most Pd-based catalysts. In situ FTIR and DFT calculations confirm preferential incomplete oxidation pathways on these surfaces.
Metastatic cancer remains a major cause of death. MT1-MMP is a key enzyme facilitating cancer cells' invasion and spread. Researchers from Yunnan University have made a surprising discovery: the VPS35/Retromer complex regulates MT1-MMP levels through a dual mechanism, both stabilizing the MT1-MMP protein and increasing its transcription via the STAT3 pathway. This leads to increased MT1-MMP levels and accelerates melanoma metastasis. The findings offer a potential new therapeutic target for preventing or treating metastatic cancer.
A new study published in National Science Review introduces a redox energy barrier strategy using 1,1′-bis(diphenylphosphino)ferrocene (DPPF) to suppress Sn²⁺ oxidation and reduce defects in Sn-Pb perovskite solar cells (PerSCs). The DPPF additive passivates Sn vacancies, yielding a 23.5% efficient inverted PerSC with an open-circuit voltage of 0.89 V and energy loss of 0.36 eV. Combined with a wide-bandgap PerSC, a four-terminal tandem cell achieves 26.4% efficiency.
Scientists have uncovered a key driver of triple-negative breast cancer (TNBC) progression—a metabolic enzyme called LPCAT1—and developed a targeted nanoparticle therapy to block it. By silencing LPCAT1, the treatment disrupts cancer cell energy production and halts tumor growth and lung metastasis in TNBC, the most aggressive breast cancer subtype. This breakthrough offers a promising new strategy for treating advanced TNBC, which currently has limited therapeutic options.
Researchers have developed a novel wearable biosensor for continuous cortisol monitoring, leveraging computational chemistry and advanced electronics. The system integrates molecularly imprinted polymers (MIPs) optimized via density functional theory for high selectivity, paired with organic electrochemical transistors (OECTs) for high sensitivity, achieving an ultra-low detection limit (0.36 nmol/L). Unlike traditional sensors, the device allows in-situ regeneration of MIPs using electric fields, enabling eight reuse cycles. A microfluidic sweat-sampling module and iontophoresis-driven sweat induction ensure noninvasive, real-time tracking, validated by circadian rhythm studies matching ELISA results. Encased in 3D-printed flexible packaging, the wireless system maintains stability under bending, paving the way for closed-loop therapeutics and precision health applications.
Inspired by the hollow skeletal structure of bird bones, which optimizes oxygen storage and respiratory efficiency, researchers from the University of Science and Technology Beijing developed a 3D hollow diamond-enhanced PEG composite PCM. The composite, HDF/PEG, leverages the excellent thermal conductivity of diamond and the advantages of a 3D interconnected structure to create a high-conductivity transport network.
This study introduces an Artificial Intelligence (AI) empowered search engine to accelerate the discovery of altermagnetic materials under the condition of limited labeled samples, demonstrating the potential of AI-driven methods to identify functional materials with novel properties.