The solar-driven photocatalytic reduction of CO₂ represents a vital frontier, offering substantial potential to concurrently alleviate the energy crisis and reduce environmental pollution. In this study, a core-shell BaTiO3/B-In2O3 (BTO/B-In2O3) heterojunction was constructed to combine photothermal effect of black indium oxide (B-In2O3) and polarization of tetragonal BTO. The BTO/B-In2O3 exhibited the excellent photocatalytic efficiency in reduction of CO2 to CO, with the yield of 146.56 and 188 μmol·g−1·h−1 under full-spectrum light with and without cooling water, being 6.07 and 7.79 times of that by BTO (24.14 μmol·g−1·h−1). Spin-polarized DFT is applied to further explore how CO2 reduction proceeds on BTO/B-In2O3, focusing on its electronic structure, electron flow, and underlying reaction mechanism. The heterojunction's photocatalytic CO2 reduction performance is enhanced by modulating its electronic structure and facilitating the reaction process. This study provides a theoretical foundation for the design of efficient ferroelectric-based photocatalysts.
Around 10% of global births are preterm (before 37 weeks of gestation), posing a significant challenge to maternal and neonatal health. Preterm infants face an increased risk of mortality and long-term health complications, impacting their survival and development across all life stages. Despite decades (~ 80 years) of research, effective methods to predict and prevent idiopathic or spontaneous preterm birth remain limited. Therefore, a deeper understanding of the pathophysiology of spontaneous preterm birth is warranted. This review explores some aspects of recent progress in unravelling the complex pathophysiology of both normal and preterm human birth. We present parturition as an inflammatory event, triggered by stressors affecting the uterine reproductive tissues (myometrium, decidua, and cervix), and involving multiple endocrine and paracrine pathways. These pathways, along with signals from fetal membrane senescence and the vaginal microbiome, contribute to labor induction. Proposed perspectives in parturition research include using mathematical modeling and machine learning (artificial intelligence) to map pregnancy trajectories and identify patient phenotypes associated with preterm birth risk. Additionally, incorporating preterm birth history into routine life course medical surveillance for affected individuals and their offspring is recommended. Finally, increased investment and prioritization from national funding bodies, along with greater support for international collaborations, are essential to identify the causes of preterm birth across multiple populations and develop new, effective treatments.
Despite invasive methods are the gold standard for intracranial pressure (ICP) measurement, several non-invasive techniques (nICP) have been proposed as surrogate, although their use remains insufficiently recognized in clinical practice. These include transcranial Doppler blood flow velocity assessment (arterial or venous), optic nerve sheath diameter (ONSD), automated pupillometry, measurement of skull expansion and compliance, brain imaging, double-depth ophthalmic artery blood flow velocity, and ultrasound time-of-flight. The main limitations of all indirect methods are calibration and zeroing, which constrain the absolute accuracy of non-invasive ICP monitoring. For transcranial Doppler-based methods, the 95
Quantum communication has developed into various classes, including recent novel quantum secure direct communication (QSDC) schemes. The QSDC method transmits confidential information directly between parties over a quantum channel without requiring a shared private key. Even though QSDC offers improved security guarantees and reduces the possibility of security loopholes, practical applications such as secure information rates, long-distance quantum communication and networking, and integration with existing technologies still requires improvement. Meanwhile, advances in artificial intelligence (AI) and machine learning (ML) continue to revolutionize several fields, including quantum communication, which is challenging to control and maintain effectively for optimum performance. Various ML techniques have been applied to quantum communication systems to mitigate noise-induced errors, analyze communication protocols, and optimize secure key generation rates. While this represents a significant development and has the potential to address challenges facing QSDC applications, we are unaware of ML applications specifically improving QSDC systems. Due to this, we bring forward the discussion and unveil the critical need to integrate AI and ML models into QSDC to enhance security, improve fault tolerance, increase communication distance, and optimize resource allocation. Consequently, this work establishes a practical framework for unlocking the full potential of QSDC protocols and, more broadly, practical quantum communication.
Heterocycles are an important class of compounds that are extensively used in pharmaceutical and industrial applications. The quest for efficient and sustainable approaches for such valuable molecules under green conditions has led to the exploration of various heterogeneous catalysts. Among these, graphitic carbon nitride (g-C3N4) functionalized with active Lewis-Brønsted acid sites stands out as an attractive candidate owing to its tailor-made characteristics. Hence, this review provides a comprehensive and systematic analysis on the design and utility of acidic functionalized g-C3N4 materials as novel carbonaceous catalysts for the chemical/photochemical establishment of numerous bioactive heterocyclic scaffolds and furanic derivatives. Several key synthetic strategies (protonation, immobilization of heteropolyacids/organic acids, sulfonation, sulfonation-metal doping, acid group/ionic liquid grafting, or hybridization with biochar/polymeric ionic liquids) along with catalyst characterization/performance/reusability and reaction optimizations for such transformations are elaborated. Last but not least, perspectives and challenges in the application of these promising hybrid nanomaterials are presented.
