Detection of fungal damaged popcorn using image property covariance features

Cataloged from PDF version of article.Covariance-matrix-based features were applied to the detection of popcorn infected by a fungus that causes a symptom called "blue-eye". This infection of popcorn kernels causes economic losses due to the kernels' poor appearance and the frequently disagreeable flavor of the popped kernels. Images of kernels were obtained to distinguish damaged from undamaged kernels using image-processing techniques. Features for distinguishing blue-eye-damaged from undamaged popcorn kernel images were extracted from covariance matrices computed using various image pixel properties. The covariance matrices were formed using different property vectors that consisted of the image coordinate values, their intensity values and the first and second derivatives of the vertical and horizontal directions of different color channels. Support Vector Machines (SVM) were used for classification purposes. An overall recognition rate of 96.5% was achieved using these covariance based features. Relatively low false positive values of 2.4% were obtained which is important to reduce economic loss due to healthy kernels being discarded as fungal damaged. The image processing method is not computationally expensive so that it could be implemented in real-time sorting systems to separate damaged popcorn or other grains that have textural differences. (C) 2012 Elsevier B.V. All rights reserve

The impact of pretreatment with simvastatin on kidney tissue of rats with acute sepsis

It has been reported that changes in cytokine levels affect mitochondrial functions, levels of hypoxia-inducible factor α (HIF-1α), and tissue damage during sepsis. We aimed to investigate the effects of simvastatin pretreatment on mitochondrial enzyme activities, and on levels of ghrelin, HIF-1α, and thiobarbituric acid reactive substances (TBARS) in kidney tissue during sepsis. Rats were separated into four groups, namely, control, lipopolysaccharides (LPS) (20 mg/kg), simvastatin (20 mg/kg), and simvastatin + LPS. We measured the levels of mitochondrial enzyme activities and TBARS in the kidney using spectrophotometry. The histological structure of the kidney sections was examined after staining with hematoxylin and eosin. Tumor necrosis factor α (TNF-α), IL-10, HIF-1α, and ghrelin immunoreactivity were examined using proper antibodies. In tissue, TNF-α (p  0.05). Ghrelin immunoreactivity was lower in the LPS group (p  0.05). We observed that pretreatment of simvastatin caused favorable changes on ghrelin and TBARS levels in rats with sepsis

Archaeogenetic analysis of Neolithic sheep from Anatolia suggests a complex demographic history since domestication

Sheep were among the first domesticated animals, but their demographic history is little understood. Here we analyzed nuclear polymorphism and mitochondrial data (mtDNA) from ancient central and west Anatolian sheep dating from Epipaleolithic to late Neolithic, comparatively with modern-day breeds and central Asian Neolithic/Bronze Age sheep (OBI). Analyzing ancient nuclear data, we found that Anatolian Neolithic sheep (ANS) are genetically closest to present-day European breeds relative to Asian breeds, a conclusion supported by mtDNA haplogroup frequencies. In contrast, OBI showed higher genetic affinity to present-day Asian breeds. These results suggest that the east-west genetic structure observed in present-day breeds had already emerged by 6000 BCE, hinting at multiple sheep domestication episodes or early wild introgression in southwest Asia. Furthermore, we found that ANS are genetically distinct from all modern breeds. Our results suggest that European and Anatolian domestic sheep gene pools have been strongly remolded since the Neolithic

Academic student satisfaction and perceived performance in the e-learning environment during the COVID-19 pandemic: Evidence across ten countries

The outbreak of the COVID-19 pandemic has dramatically shaped higher education and seen the distinct rise of e-learning as a compulsory element of the modern educational landscape. Accordingly, this study highlights the factors which have influenced how students perceive their academic performance during this emergency changeover to e-learning. The empirical analysis is performed on a sample of 10,092 higher education students from 10 countries across 4 continents during the pandemic’s first wave through an online survey. A structural equation model revealed the quality of e-learning was mainly derived from service quality, the teacher’s active role in the process of online education, and the overall system quality, while the students’ digital competencies and online interactions with their colleagues and teachers were considered to be slightly less important factors. The impact of e-learning quality on the students’ performance was strongly mediated by their satisfaction with e-learning. In general, the model gave quite consistent results across countries, gender, study fields, and levels of study. The findings provide a basis for policy recommendations to support decision-makers incorporate e-learning issues in the current and any new similar circumstances.info:eu-repo/semantics/publishedVersio