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The purpose of this study was to design a paper strip-based non-invasive urine analysis system for the qualitative detection of biomarker aquaporin-1 (AQP1) in renal cancer (RC). RC accounts for 3% of all cancers and 85% of all kidney tumors and mainly originates from the kidney cortex. In recent times, higher urine concentration of AQP1 in patients with RC was confirmed as a specific biomarker of the disease. Hence, the noninvasive, user-friendly and self-diagnostic method is required for the detection of aquaporin biomarkers in RC.

The present research work was focused on the development and characterization of a dye conjugated cyclodextrin-based miniaturized system for impregnation on Whatman filter paper to identify RC using AQP1 biomarker present in urine samples.

It was observed that the test strip dipped into the urine sample, and the yellow color intensity increased with a decrease in AQP1 concentration due to the transformation of the dye system of free basic form into bound acidic form. The Hue-Saturation-Value profiling was used to observe the effect of color change using a smartphone application. The paper strip-based urine analysis system is highly sensitive for the detection of AQP1 in the range of 10 to 1,000 ng.

The successful validation indicated that this biosensor is likely to contribute to the development of point-of-care, novel, personalized diagnostics and ensure prolonged survival of RC patients in the near future.

The purpose of this paper is to analyze risk profiles of projects based on project characteristics and provide key managerial insights.

A total of 37 project cases from engineering and construction (E&C), information system/technology (IS/IT), and new product development (NPD) sectors with detailed information on project characteristics and risks were identified from published literature. An integrated framework was developed to analyze the prominent risk categories associated with novelty, technology, complexity, and pace (NTCP) project characteristics.

Within-sector analysis revealed that schedule, resource, and scope risks are the most prominent risk categories in E&C, IS/IT, and NPD projects, respectively. Similarly, interesting key insights have been drawn from detailed cross-sector analysis, depicting different risk categories based on NTCP project characteristics.

The findings are based on the case studies adopted from the literature that provides details of project characteristics and risk profiles.

Depending upon the risks associated with different project characteristics, an integrated framework developed in the study can be used for the development of highly authentic risk management plans at the onset.

This is one of the earliest studies to provide an integrated risk framework for projects based on their NTCP characteristics. The two contrasting perspectives of within-sector and cross-sector analyses were adopted. Overall, the study will enhance the future preparedness toward risks.

Buying online has become a widespread and common activity for consumers, and, for many organizations, e-commerce has become a very profitable alternative to sell their products and services, also allowing them to leverage their strategy in new geographical markets immediately. Although the literature on the subject is comprehensive, there is a gap in identifying the holistic constructs that are the determinants of consumers' choice of an online store. This research resorts to an exploratory study, based on a nonsystematic literature review, seeking to identify these constructs. The results obtained allowed us to identify the following constructs: consumer behavior, customer experience, web content, catalog, terms and conditions, customer support, perceived value, trust, security and privacy, satisfaction, and loyalty. Customer experience, satisfaction, and loyalty constructs stand out from a strategic perspective.

This study aims to identify factors affecting Generation Z (Gen-Z)’s online learning (OL) behavioural intention (BI) using the extended technology acceptance model by investigating gender differences in the BI of Indian students to adopt OL.

The proposed model was tested on 284 students from a higher education institution (HEI) in Gujarat, India, using the partial least square–structural equation modelling. Further, the subgroup analysis was conducted using Statistical Package for Social Sciences (SPSS) to determine male and female OL adoption variances.

Based on the research findings, all the constructs positively influence the BI of Gen-Z to adopt OL, except the influence of information technology infrastructure (INF) on perceived usefulness (PU). However, no substantial difference was observed in the BI adoption of OL amongst males and females. Also, when gender was kept as a moderator between computer self-efficacy (CSE) and PU, and INF and perceived ease of use (PEU), no substantial difference was observed in the OL of Gen-Z.

The study will benefit HEIs and associated government departments from a deeper understanding of Gen-Z’s BI to speed up deployment and consider key elements essential while considering OL.

This article found major determinants of Gen-Z’s BI to adopt the OL in HEI. To the best of the author’s understanding, this is amongst the few studies to explore these ideas in the context of India. The uniqueness of the topic has been brought to light by the fact that “gender” has been employed as a moderator between attitude and BI, INF and PEU, and CSE and PU.