Results 151 to 160 of about 69,629 (213)

Bayes Factor-Based Regulatory Gene Network Analysis of Genome-Wide Association Study of Economic Traits in a Purebred Swine Population. [PDF]

Genes (Basel), 2019
Lee J, Kang JH, Kim JM.
europepmc   +1 more source

Food Prices and Inflation Expectations in New Zealand

Agribusiness, EarlyView.
ABSTRACT Food prices are conspicuous, and spending on food constitutes a considerable share of household expenditure. In this study, we use partially identified Bayesian structural vector autoregression models to analyze the effects of food price shocks on core inflation and 1‐ and 5‐year inflation expectations in New Zealand.
Puneet Vatsa, Gabriel Pino, Alex Acheampong   +2 more
wiley   +1 more source

Assessment of relationship between rainfall and Escherichia coli in clams (Chamelea gallina) using the Bayes Factor. [PDF]

Ital J Food Saf, 2017
Ciccarelli C, Semeraro AM, Leinoudi M, Trani VD, Murru S, Capocasa P, Ciccarelli E, Sacchini L.   +7 more
europepmc   +1 more source

Pesticide MRLs as Trade Barriers: Evidence From Vietnam's Coffee and Rice Exporters

Agribusiness, EarlyView.
ABSTRACT As tariffs have declined globally through bilateral and regional trade agreements, food safety standards have emerged as significant determinants of agricultural trade flows. This study examines the impact of maximum residue limits (MRLs) for five pesticides—Azoxystrobin, Chlorpyrifos, Chlorantraniliprole, Clothianidin, and Cyhalothrin—on ...
Nhat Mai Nguyen, Hoa‐Thi‐Minh Nguyen, Kaliappa Kalirajan   +2 more
wiley   +1 more source

Not All Agreements Are Equal: Heterogeneous Effects of RTAs on Latin American Agri‐Food Exports, 1990–2019

Agribusiness, EarlyView.
ABSTRACT Since the final decade of the 20th century, Latin American countries have increasingly regarded the signing of regional trade agreements (RTAs) as a promising strategy for expanding their exports. Within this context, the main objective of this study is to assess the impact of RTAs on agri‐food exports in Latin America over the period 1990 ...
María‐Isabel Ayuda, Ignacio Belloc, Vicente Pinilla   +2 more
wiley   +1 more source

Comparison Between Upfront Surgery and Preoperative Chemotherapy for CY1P0 Gastric Cancer: A Japanese Sub‐Analysis of CONVO‐GC‐1

Annals of Gastroenterological Surgery, EarlyView.
ABSTRACT Background Radical gastrectomy, followed by adjuvant chemotherapy has been a common practice in Japan for peritoneal lavage cytology‐positive (CY1) but peritoneal dissemination‐negative (P0) stage IV gastric cancer. This study aimed to clarify the differences in treatment outcomes between upfront surgery and preoperative chemotherapy, followed
Kenichiro Furukawa, Itaru Yasufuku, Hironori Ishigami, Masahiro Yura, Takanobu Yamada, Shigeaki Baba, Takeshi Kubota, Erina Nagai, Seito Fujibayashi, Mitsumasa Yoshida, Takahiro Kinoshita, Nobuhisa Matsuhashi, Masanori Terashima   +12 more
wiley   +1 more source

What Are the Odds? Modern Relevance and Bayes Factor Solutions for MacAlister's Problem From the 1881 Educational Times. [PDF]

Educ Psychol Meas, 2017
Jamil T, Marsman M, Ly A, Morey RD, Wagenmakers EJ.   +4 more
europepmc   +1 more source

MiR‐146a‐5p Suppresses M1 Polarization of Tumor‐Associated Macrophages via IRAK1/NF‐κB Signaling in Colorectal Polyps

Annals of Gastroenterological Surgery, EarlyView.
MiR‐146a‐5p is downregulated in colorectal polyps, leading to IRAK1 upregulation and NF‐κB activation, which promotes M1 macrophage polarization and inflammation. Overexpression of miR‐146a‐5p suppresses IRAK1/NF‐κB signaling, reduces M1 polarization, and alleviates inflammatory responses.
Peng Song, Lianhui Wu, Huabin Qiu, Lei Luo, Jianzhao Qiu, Shuping Xiao, Jincai He   +6 more
wiley   +1 more source

Artificial Intelligence‐Driven Insights into Electrospinning: Machine Learning Models to Predict Cotton‐Wool‐Like Structure of Electrospun Fibers

Advanced Intelligent Discovery, EarlyView.
Electrospinning allows the fabrication of fibrous 3D cotton‐wool‐like scaffolds for tissue engineering. Optimizing this process traditionally relies on trial‐and‐error approaches, and artificial intelligence (AI)‐based tools can support it, with the prediction of fiber properties. This work uses machine learning to classify and predict the structure of
Paolo D’Elia, Giovanna Pappalardo, Aldo R. Boccaccini, Liliana Liverani   +3 more
wiley   +1 more source

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source