Cobalt-based sulfides have emerged as promising candidates for next-generation high-performance anode materials for lithium-ion batteries (LIBs) due to their high theoretical specific capacity and reversible conversion reaction mechanisms. However, their practical application is hindered by volume expansion effects and relatively low rate performance. Guided by theoretical principles, this study synthesizes nanoscale Bi/CoS-C and Bi/Co4S3-C (denoted as Bi/CS-C) composite materials using Co and Bi2S3 as precursors via a solid-state ball milling method. The electrochemical properties of these materials were systematically investigated. When employed as anodes for LIBs, Bi/CoS-C and Bi/CS-C exhibit excellent rate capabilities. At current densities of 0.1, 0.5, 1, 4, and 10 A/g, the reversible capacities of Bi/CoS-C were 939.2, 730.7, 655.6, 508.1, and 319 mAh/g, respectively. In contrast, Bi/CS-C exhibited reversible capacities of 760.4, 637.6, 591.9, 484.3, and 295.4 mAh/g, respectively. Moreover, Co4S3, as an active component, enables superior long-cycle performance compared to CoS. After 300 cycles at 0.2 A/g, the Bi/CoS-C and Bi/CS-C electrodes retained capacities of 193.1 and 788.8 mAh/g, respectively. This study demonstrates that nanostructure design and carbon-based composite materials can effectively mitigate the volume expansion issue of cobalt-based sulfides, thereby enhancing their rate performance and cycling stability. This strategy provides new insights for the development of high-performance anode materials for lithium-ion batteries and is expected to accelerate their practical application in next-generation energy storage devices.
The paper assesses the threshold at which climate change impacts banking system stability in selected Sub-Saharan economies by applying the panel threshold regression on data spanning 1996 to 2017. The study found that temperature reported a threshold of −0.7316 ℃. Further, precipitation had a threshold of 7.1646 mm, while the greenhouse gas threshold was 3.6680 GtCO2eq. In addition, the climate change index recorded a threshold of −0.1751%. Overall, a non-linear relationship was established between climate change variables and banking system stability in selected Sub-Saharan economies. The study recommends that central banks and policymakers propagate the importance of climate change uncertainties and their threshold effects to banking sectors to ensure effective and stable banking system operations.
The MDA-MB-231 cell line is derived from triple-negative breast cancer (TNBC), representing one of the most aggressive forms of breast cancer. Innovative therapeutic strategies, including s targeted therapies using nanocarriers, hold significant promise, particularly for difficult-to-treat cancers such as TNBC. Nanoparticles have transformed the medical field by serving as advanced drug delivery systems for cancer treatment. They play a critical role in overcoming the drug resistance often associated with cancer therapies. When utilized as drug delivery vehicles, nanoparticles can specifically target cancer cells and effectively reduce or eliminate multidrug resistance. Among them, chitosan-coated magnetic nanoparticles (MNPs) have been widely explored for the loading and controlled release of various anticancer agents. In this study, we evaluated the effects of dexamethasone-loaded chitosan-coated MNPs on MDA-MB-231 cell lines. Fourier transform infrared spectroscopy and scanning electron microscopy were employed to verify the successful loading of dexamethasone onto the nanoparticles. To assess cytotoxicity, empty nanoparticles, free drug, and drug-loaded nanoparticles were tested on the cells. The results indicated that empty nanoparticles exhibited no toxic effects. The IC50 value of the free drug was 123 µg/mL, while the IC50 value of the drug-loaded nanoparticles was significantly lower, at 63 µg/mL. These findings confirmed the successful conjugation of dexamethasone to the chitosan-coated MNPs, demonstrating substantial cytotoxic effects on breast cancer cells. Although dexamethasone has been reported to exhibit both tumor-suppressive and pro-metastatic effects, its specific impact on TNBC warrants further investigation in future studies.
The expanding adoption of artificial intelligence systems across high-impact sectors has catalyzed concerns regarding inherent biases and discrimination, leading to calls for greater transparency and accountability. Algorithm auditing has emerged as a pivotal method to assess fairness and mitigate risks in applied machine learning models. This systematic literature review comprehensively analyzes contemporary techniques for auditing the biases of black-box AI systems beyond traditional software testing approaches. An extensive search across technology, law, and social sciences publications identified 22 recent studies exemplifying innovations in quantitative benchmarking, model inspections, adversarial evaluations, and participatory engagements situated in applied contexts like clinical predictions, lending decisions, and employment screenings. A rigorous analytical lens spotlighted considerable limitations in current approaches, including predominant technical orientations divorced from lived realities, lack of transparent value deliberations, overwhelming reliance on one-shot assessments, scarce participation of affected communities, and limited corrective actions instituted in response to audits. At the same time, directions like subsidiarity analyses, human-cent
This study aimed to examine the impact of digital leadership among school principals and evaluate the mediating effect of Professional Learning Communities (PLCs) on enhancing teachers’ innovation skills for sustainable technology integration, both in traditional classroom settings and e-learning environments. Employing a quantitative approach with a regression design model, Structural Equation Modelling (SEM) and Partial Least Squares (PLS-SEM) were utilized in this research. A total of 257 teachers from 7 excellent senior high schools in Makassar city participated in the study, responding to the questionnaires administered. The study findings indicate that while principal digital leadership does not directly influence teachers’ innovation skills in technology integration, it directly impacts Professional Learning Communities (PLCs). Moreover, PLCs themselves have a significant influence on teachers’ innovation skills in technology integration. The structural model presented in this study illustrates a noteworthy impact of principal digital leadership on teachers’ innovation skills for technology integration through Professional Learning Communities (PLCs), with a coefficient value of 47.4%. Principal digital leadership is crucial in enhancing teachers’ innovation skills for sustainable technology integration, primarily by leveraging Professional Learning Communities (PLCs). As a result, principals must prioritize the creation of supportive learning environments and implement programs to foster teachers’ proficiency for sustainable technology integration. Additionally, teachers are encouraged to concentrate on communication, collaboration, and relationship-building with colleagues to exchange insights, address challenges, and devise solutions for integrating technology, thereby contributing to sustained school improvement efforts. Finally, this research provides insights for school leaders, policymakers, and educators, emphasizing the need to leverage PLCs to enhance teaching practices and student outcomes, particularly in sustainable technology integration.
The rapid expansion of smart cities has led to the widespread deployment of Internet of Things (IoT) devices for real-time data collection and urban optimization. However, these interconnected systems face critical cybersecurity risks, including data tampering, unauthorized access, and privacy breaches. This paper proposes a blockchain-based framework designed to enhance the security, integrity, and resilience of IoT data in smart city environments. Leveraging a private blockchain, the system ensures decentralized, tamper-proof data storage, and transaction verification through digital signatures and a lightweight Proof of Work consensus mechanism. Smart contracts are employed to automate access control and respond to anomalies in real time. A Python-based simulation demonstrates the framework’s effectiveness in securing IoT communications. The system supports rapid transaction validation with minimal latency and enables timely detection of anomalous patterns through integrated machine learning. Evaluations show that the framework maintains consistent performance across diverse smart city components such as transportation, healthcare, and building security. These results highlight the potential of the proposed solution to enable secure, scalable, and real-time IoT ecosystems for modern urban infrastructures.
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