WE SHOULD PAY MORE ATTENTION TO THE COMMUNITY CONTEXT IN THE DISASTER MANAGEMENT: LESSONS LEARNED FROM THE FIRST DAYS AFTER THE KHOY EARTHQUAKE

We should pay more attention to the community context in the disaster management: lessons learned from the first days after the Khoy earthquake

Dear Editor-in-Chief On January 28, the city of Khoy (the northwest of Iran) was struck by a strong earthquake with a magnitude of 5.9 on the Richter scale at 21:44:44 and a depth of 7 km, X: 45.01 and Y: 38.05 (1).This earthquake occurred 117 kilometers from Urmia, the capital of the West Azerbaijan Province.Over 370,000 people were affected by th

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Role of Coffee Caffeine and Chlorogenic Acids Adsorption to Polysaccharides with Impact on Brew Immunomodulation Effects

Coffee brews have High Molecular Weight (HMW) compounds with described immunostimulatory activity, namely polysaccharides and melanoidins.Melanoidins are formed during roasting and are modified during brews technological processing.In addition, brews have Low Molecular Shelving Accessories Weight (LMW) compounds, namely free chlorogenic acids and c

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Antimicrobial efficacy of herbal, homeopathic and conventional dentifrices against oral microflora: An in vitro study

Introduction This study compares the efficacy of herbal, homeopathic, and conventional Rear View Mirror Accessory dentifrices, on oral microflora using antibiotic susceptibility tests.Methods Three strains of microorganisms, Streptococcus Mutans, Escherichia Coli, and Candida Albicans, were taken and incubated in Mutans media, Mueller Hilton agar,

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Integrating machine learning algorithms and explainable artificial intelligence approach for predicting patient unpunctuality in psychiatric clinics

Allergy Relief This study addresses patient unpunctuality, a major concern affecting patient waiting time, resource utilization, and quality of care.We develop and compare four machine learning models, including multinomial logistic regression, decision tree, random forest, and artificial neural network, to accurately predict patient arrival patter

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