30988 research outputs found
Sort by
Опыт недоверия к переводчикам. Влияние социального недоверия на формирование институционального доверия к базовым услугам Финляндии
No full text
Resilience In Crisis: Navigating Global Value Chain Disruptions In Bangladeshi Outsourcing SME's
No full text1D Light-Emitting MAPbBr3 Perovskite Encapsulated in Carbon Nanotubes
No full textThe instability and broad optical features of perovskites limit the full realization of their unique optoelectronic potential. In this study, a novel MAPbBr3@SWCNTs hybrid material is presented, in which methylammonium lead bromide perovskite (MAPbBr3) is successfully encapsulated in single-walled carbon nanotubes (SWCNTs), fabricated in the form of thin films. Encapsulation enables the formation of 1D perovskite structures with narrowband light-emission, confined within a protective carbon nanoshell. A thorough investigation is conducted into the hybrid material's structure, linear optical properties, ultrafast carrier dynamics, and THz conductivity. The encapsulation preserves the distinct characteristics of both MAPbBr3 and SWCNTs while introducing novel optoelectronic effects, including the tuning and spectral unification of perovskite photoluminescence (PL), as well as doping-induced modifications to SWCNT carrier relaxation dynamics. Furthermore, the observation of negative photoconductivity (NPC) response of MAPbBr3@SWCNTs thin films highlights the potential of this innovative material as a strong candidate for future energy-efficient photodetectors, optoelectronic switches, neuromorphic computing devices, photovoltaic enhancers, and flexible electronics
Tietosuojaperiaatteiden yhteensovittaminen DSM-direktiivin 17 artiklan 4 kohdan b ja c alakohdan nojalla toteutettuihin toimiin
No full textModeling Physical and Medical Lifetime Data Using the Inverse Power Entropy Chen Distribution
No full textThis paper presents a new model that surpasses traditional distributions, specifically the three-parameter distribution of the Inverse Power Entropy Chen (IPEC) model. In comparison to the existing distributions, the latest one presents an exceptionally diverse array of probability functions. The density and hazard rate functions have characteristics indicating that the model is adaptable to many types of data. The study explores the mathematical features of the IPEC distribution, including moments with some related measures, quantile function, Rényi entropy, Tsallis entropy, and order statistics. To estimate the parameters of the IPEC model, we utilized seven classical estimation strategies, including maximum likelihood estimators, Anderson–Darling estimators, right-tail Anderson–Darling estimators, Cramér–von Mises estimators, percentile estimators, least-squares estimators, and weighted least-squares estimators. To evaluate the efficacy of these estimating approaches across varying sample sizes, Monte Carlo simulations are performed. The efficacy of each estimator is evaluated through comparisons of average relative bias and mean squared error, highlighting their suitability for the used samples. Three applications utilize real-world datasets related to medical and physical fields, demonstrating the usefulness of the new model in relation to several established competitive models. This empirical investigation further supports the utility and adaptability of the inverse power entropy Chen model in capturing the intricacies of distinct datasets, hence delivering useful insights for practitioners in numerous domains
