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1.
Int J Food Sci ; 2024: 9526283, 2024.
Artículo en Inglés | MEDLINE | ID: mdl-39119017

RESUMEN

Meat content and physically hazardous contaminants in the internal section of meatballs cannot be detected by the naked eye or surface detectors. This study is aimed at analyzing the meat content of cattle meatballs and detecting foreign objects using ultrasonography (USG), digital radiography (DR), and electrical impedance tomography (EIT). Meatballs were produced using four different meat formulations (0%, 25%, 50%, and 75% meat) and three treatments (no preservative (control), borax, and formalin preservatives). Cast iron and plastic beads were used as models of foreign objects embedded in the samples. The echogenicity, opacity, and resistivity values of each sample were evaluated and compared across groups. The results showed that the shelf life of the control meatballs was shorter than that of meatballs with preservatives. The echogenicity and opacity values for the different meat formulations were hypoechoic in USG and grey in DR. USG was able to distinguish between control and preservative-treated meatballs but could not differentiate meat content and detect foreign objects. Conversely, DR effectively assessed meat content and detected iron-based foreign objects, while EIT showed higher resistivity values for iron and plastic beads compared to the meatball bodies.

2.
Arch Craniofac Surg ; 25(1): 11-16, 2024 Feb.
Artículo en Inglés | MEDLINE | ID: mdl-38461823

RESUMEN

BACKGROUND: The pathogenesis of orofacial cleft (OFC) is multifactorial, involving both genetic and non-genetic factors, the latter of which play a key role in the development of these anomalies. This paper addresses the incidence of OFC in Indonesia, with a focus on identifying and examining the distribution of contributory factors, including parental medical history, pregnancy history, and environmental influences. METHODS: The study was conducted through the collection of primary data. An interdisciplinary research team from Indonesia administered a standardized questionnaire to parents who had children with OFC and who had provided informed consent. The case group comprised 133 children born with cleft lip and/or palate, and the control was 133 noncleft children born full-term. The risk factors associated with OFC anomalies were analyzed using the chi-square test and logistic regression. All statistical analyses were performed using SPSS version 25. A p-value of 0.05 or less was considered to indicate statistical significance. RESULTS: The study comprised 138 children, of whom 82 were boys (59.4%) and 56 were girls (40.6%). Among them, 45 patients (32.6%) presented with both cleft lip and cleft palate, 25 individuals (18.1%) had a cleft palate only, and 28 patients (20.3%) had a cleft lip only. OFC was found to be significantly associated with a maternal family history of congenital birth defects (p< 0.05), complications during the first trimester (p< 0.05), consumption of local fish (p< 0.05), caffeine intake (p< 0.05), prolonged medication use (p< 0.05), immunization history (p< 0.05), passive smoking (p< 0.05), and X-ray exposure during pregnancy (p< 0.05). CONCLUSION: The findings indicate close relationships between the incidence of OFC and maternal medical history, prenatal factors, and environmental influences.

3.
Heliyon ; 7(7): e07482, 2021 Jul.
Artículo en Inglés | MEDLINE | ID: mdl-34377849

RESUMEN

Indonesia is a country that is surrounded by active volcanoes, which may erupt at any time; therefore, an online early warning system of volcanic eruption is crucial. In this paper, an online early warning system is constructed based on the changepoints detection on earthquake magnitude time series. This online early warning system is built using a Bayesian Online Changepoint Detection (BOCPD) method. One of the method's advantages is that one can customize the parameters (initial hyper-parameters and hazard-rate parameter) of BOCPD to follow a chosen constraint. These parameters determine the time and number of changepoints. An algorithm, called Appropriate Parameters of Bayesian Online Changepoint Detection for Early Warning (APBOCPD-EW), is proposed to get the parameters that lead the detection to the early warning points before eruption. We apply the algorithm for online early warning of mount Merapi eruptions. The results show that the proposed method produces parameters that give good estimation time for early warnings of mount Merapi's eruptions.

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