The photovoltaic performance of copper indium gallium diselenide (CIGS)-based solar cells with Cd-free single buffer layers and a barium disulfide (BaSi2) back-surface field (BSF) has been studied through a numerical approach using a one-dimensional solar cell capacitance simulator (SCAPS-1D).The efficacy of the buffer layer of cadmium sulfide (CdS
Exploring the Genomic Traits of Non-toxigenic Vibrio parahaemolyticus Strains Isolated in Southern Chile
Vibrio parahaemolyticus is the leading cause of seafood-borne gastroenteritis worldwide.As reported in other countries, after the rise and fall of the pandemic strain in Chile, other post-pandemic strains have been associated with clinical cases, including strains lacking the major toxins TDH and TRH.Since the presence or absence of tdh and trh gen
A função multidisciplinar do compositor eletroacústico – Uma abordagem operacional
As particularidades do material Swim - Mens Suits - Training eletroacústico moveram a composição musical para outras dimensões operacionais.Dentre tantos, dois aspectos mostraram-se essenciais para o desenvolvimento da cena eletroacústica: modelos de representação específicos e o contato direto do compositor com seu instrumental.Neste artig
CUL4B Upregulates RUNX2 to Promote the Osteogenic Differentiation of Human Periodontal Ligament Stem Cells by Epigenetically Repressing the Expression of miR-320c and miR-372/373-3p
Mesenchymal stem cells (MSCs) within the periodontal ligament (PDL), termed periodontal ligament stem cells (PDLSCs), have a self-renewing capability and a multidirectional differentiation potential.The molecular mechanisms that regulate multidirectional differentiation, such as the osteogenic differentiation of PDLSCs, remain to CALM CHAI LATTE RE
Deep Neural Network Regression with Advanced Training Algorithms for Estimating the Compressive Strength of Manufactured-Sand Concrete
Manufactured sand has high potential for replacing natural sand and reducing the negative impact of the construction industry on the environment.This paper aims at developing a novel deep learning-based approach for estimating the compressive strength of manufactured-sand concrete.The deep neural networks are trained by the advanced optimizers of R