A new modular [Fe(II)(Fe(III)L(2))(3)](PF(6))(2) species with discoid (disk-like) topology exhibits redox and surfactant properties and points to a new approach for multimetallic Langmuir film precursors.
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http://dx.doi.org/10.1021/ic1009626 | DOI Listing |
Heart Rhythm O2
December 2024
Cardiology Department, Bichat Hospital, Paris, France.
Background: Detection of atrial tachyarrhythmias (ATA) on long-term electrocardiogram (ECG) recordings is a prerequisite to reduce ATA-related adverse events. However, the burden of editing massive ECG data is not sustainable. Deep learning (DL) algorithms provide improved performances on resting ECG databases.
View Article and Find Full Text PDFAngew Chem Int Ed Engl
January 2025
Zhejiang University, Chemistry, Department of Chemistry, ZhiJinGang Campus, 310058, Hangzhou, CHINA.
Integrating two or more materials to construct membranes with heterogeneous pore structures is an effective strategy for enhancing separation performance. Regularly arranging these heterogeneous pores can significantly optimize the combined effect of the introduced components. Porous Organic Cages (POCs), an emerging subclass of porous materials composed of discrete molecules, assemble to form interconnected pores and exhibit permanent porosity in the solid state.
View Article and Find Full Text PDFInt J Pharm
January 2025
Department of Pharmacy, Faculty of Health and Medical Sciences, University of Copenhagen 2100 Copenhagen, Denmark. Electronic address:
Additively manufactured drug products, typically produced using small-scale, on-demand batch mode, require rapid and non-destructive quantification methods. A tunable modular design (TMD) approach combining porous polymeric freeze-dried modules and an additive manufacturing method, inkjet printing, was proposed in an earlier study to fabricate accurate and patient-tailored doses of an antidepressant citalopram hydrobromide. This approach addresses the unmet medical needs associated with antidepressant tapering.
View Article and Find Full Text PDFSensors (Basel)
January 2025
State Key Laboratory of Intelligent Vehicle Safety Technology, Chongqing 401133, China.
With the advancement of federated learning (FL), there is a growing demand for schemes that support multi-task learning on multi-modal data while ensuring robust privacy protection, especially in applications like intelligent connected vehicles. Traditional FL schemes often struggle with the complexities introduced by multi-modal data and diverse task requirements, such as increased communication overhead and computational burdens. In this paper, we propose a novel privacy-preserving scheme for multi-task federated split learning across multi-modal data (MTFSLaMM).
View Article and Find Full Text PDFSensors (Basel)
December 2024
Department of Automation and Industrial Informatics, Faculty of Automatic Control and Computer Sciences, National University of Science and Technology Polithenica Bucharest, 313 Spl. Independenței, RO060042 Bucharest, Romania.
Every day, a considerable number of new cybersecurity attacks are reported, and the traditional methods of defense struggle to keep up with them. In the current context of the digital era, where industrial environments handle large data volumes, new cybersecurity solutions are required, and intrusion detection systems (IDSs) based on artificial intelligence (AI) algorithms are coming up with an answer to this critical issue. This paper presents an approach for implementing a generic model of a network-based intrusion detection system for Industry 4.
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