This study reports a newly identified mutation (c.2024A>C) in the SLC4A11 gene segregating with the diseased haplotype in two consanguineous Pakistani families.
Examining the quality perceptions of consumers has often been recommended as an international research paradigm. This study is grounded in the Pakistani consumer market to evaluate the impact of food packaging cues on perceived product quality. The moderating effect of consumer knowledge was also taken into consideration in the study. A signaling theory was used in the study for its established predictive power in consumer behavior, marketing, and various fields of research. Based on the essence of the signaling theory, this study hypothesized that food packaging cues cast a positive impact on perceived product quality and consumer knowledge moderates these relationships. By using the sample of 504 consumers, data were gathered using the mall intercept method following a multi-stage sampling technique. The responses were analyzed using Statistical Package for Social sciences (SPSS) and Smart Partial Least Square (PLS). The findings of this study unveil that the extrinsic cues' brand name, price, nutritional labels, and precautionary labels were positively and significantly related to the perceived product quality. However, the country of origin cast no impact on the perceived product quality. Consumer knowledge reflected a moderation effect on the relationships between brand name and country of origin with the perceived product quality whereas it exerted no moderation impact on the relationships of price, nutritional labels, and precautionary labels with the perceived product quality. As the results exhibit that Pakistani consumers rely on food packaging cues for perceiving a product, hence it is recommended that marketers and policymakers develop appropriate marketing strategies focused on the significance of food packaging cues.
In the modern World, diseases may occur at any time. Early diagnosis can prevent the serious consequences of the disease. The Computer Aided Diagnosis has very positively influenced the medical field. It helps the Radiologists to diagnose the diseases very quickly, precisely and accurately. The earlier diagnosis can help doctors to cover further spreading of the disease and to overcome at all. In this paper presented the following step to implements the Diagnosis process including the image preprocessing, Feature Extraction, Segmentation and classification. There are different techniques used in Image Segmentation like Fuzzy-C-Mean (FCM) Algorithm, Thresholding, Watershed Clustering Method and Region Growing etc. Feature extraction is the second phase that includes the calculation of different features of segmented lesion. It transforms the data that is in high-dimensional space to some extent of lesser dimensions. This is the final phase the classification phase that which is deals the Measurement of feature that are used the input to support the vector machine in last classify the lesion. This paper works of Computer Aided Diagnosis on liver lesion has briefly described.
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