Results 131 to 140 of about 525,476 (324)

Different Estimation Methods Using Ranked Set Sampling for the Ramos–Louzada Distribution

Engineering Reports
The data collection is a vital aspect of any scientific inquiry. Advanced data collection techniques, such as ranked set sampling (RSS), use the ranking information of the sample units to provide representative sample data.
Diaa S. Metwally, Amal S. Hassan, Mohammed Elgarhy, Ehab M. Almetwally, Abdoulie Faal, Ahmed M. Gemeay   +5 more
doaj   +1 more source

Highly Sensitive Electrochemical Biosensor Based on Hairy Particles with Controllable High Enzyme Loading and Activity

Advanced Functional Materials, EarlyView.
For the first time, a highly sensitive electrochemical biosensor based on SiO2‐based hairy particles with a grafted PDMAEMA polymer brush containing a quantifiable and large amount of immobilized Laccase is reported. The fabricated biosensor exhibits a sensitivity of 0.14 A·m⁻¹, a limit of detection (LOD) of 0.1 µm, and a detection range of 0.3–750 µm,
Pavel Milkin, Anila Antony, Hongtao Cai, Antonia Debevc, Ceyda Topal, Anne Linhardt, Alla Synytska, Leonid Ionov   +7 more
wiley   +1 more source

Strategic Synergies: ESG Performance, Political Connection, and Audit Committees in Enhancing Company Value

The Indonesian Journal of Accounting Research
This study examines the impact and implications of Environmental, Social, and Governance (ESG) performance, political connections, and audit committees on firm value in companies listed on the Indonesia Stock Exchange for the 2019–2023 period, with a ...
Dwi Septiani, Agus Munandar
doaj   +1 more source

Patterning the Void: Combining L‐Systems with Archimedean Tessellations as a Perspective for Tissue Engineering Scaffolds

Advanced Functional Materials, EarlyView.
This study introduces a novel multi‐scale scaffold design using L‐fractals arranged in Archimedean tessellations for tissue regeneration. Despite similar porosity, tiles display vastly different tensile responses (1–100 MPa) and deformation modes. In vitro experiments with hMSCs show geometry‐dependent growth and activity. Over 55 000 tile combinations
Maria Kalogeropoulou, Kenny A. van Kampen, Pierpaolo Fucile, Carlos Mota, Lorenzo Moroni   +4 more
wiley   +1 more source

Reevaluating the Activity of ZIF‐8 Based FeNCs for Electrochemical Ammonia Production

Advanced Functional Materials, EarlyView.
Though receiving much attention, the field of electrochemical nitrogen reduction reaction (eNRR) to ammonia is marked by doubts about whether this reaction is possible in aqueous media. This work sheds light on this question for iron single‐atom on N‐doped carbon (FeNC) catalysts—a class of well‐known catalysts that is also worth testing for the sister
Caroline Schneider, S. Esmael Balaghi, Niklas Ortlieb, Patrick Elsaesser, Sima Heidari, Christopher S. Allen, Anna Fischer   +6 more
wiley   +1 more source

Residual Risk Revisited [PDF]

The Capital Asset Pricing Model in conjunction with the usual market model assumptions implies that well-diversified portfolios should be mean variance efficient and ,hence, betas computed with respect to such indices should completely explain expected ...
Bruce N. Lehmann
core  

Implementation of Drug‐Induced Rhabdomyolysis and Acute Kidney Injury in Microphysiological System

Advanced Functional Materials, EarlyView.
A modular Muscle–Kidney proximal tubule‐on‐a‐chip integrates 3D skeletal muscle and renal proximal tubule tissues to model drug‐induced rhabdomyolysis and acute kidney injury. The coculture system enables dynamic tissue interaction, functional contraction monitoring, and quantification of nephrotoxicity, revealing drug side effect‐induced metabolic ...
Jaesang Kim, Zhuo Feng Lee, Gi‐Dong Sim, Sejoong Kim, Jessie S. Jeon   +4 more
wiley   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Expanding Chemical Space of Nucleic Acid Nanoparticles for Tunable Antiviral‐Like Immunomodulatory Responses and Potent Adjuvant Activity

Advanced Functional Materials, EarlyView.
We introduce a nucleic acid nanoparticle (NANP) platform designed to be rrecognized by the human innate immune system in a regulated manner. By changing chemical composition while maintaining constant architectural parameters, we identify key determinants of immunorecognition enabling the rational design of NANPs with tunable immune activation profiles
Martin Panigaj, Hannah S. Newton, Jian Wang, Laxmi Pandey, Yelixza I. Avilla, Phong Nguyen, Morgan Chandler, Justin Halman, Yasmine Radwan, Stephanie Smith, Elijah Edmondson, Simone Difilippantonio, Chelsea Sanders, Bao Tran, Yongmei Zhao, Shaojun Xie, Edward Cedrone, Barry W. Neun, Meni Wanunu, Nikolay V. Dokholyan, Marina A. Dobrovolskaia, Kirill A. Afonin   +21 more
wiley   +1 more source

Drivers of Fund Performance: A Panel Data Analysis [PDF]

The principle aim of this research is to elucidate the factors driving the total rate of return of non-listed funds using a panel data analytical framework. In line with previous results, we find that core funds exhibit lower yet more stable returns than
Franz Fuerst, George Matysiak
core