Self-Embedding Authentication Watermarking with Effective Tampered Location Detection and High-Quality Image Recovery.

Recently, sensor networks have emerged as a high-impact research area, and a number of high profile applications have been proposed. Although significant progress has already been made on securing basic network protocols, additional research is needed to produce techniques and methods for protecting canonical tasks in wireless sensor networks. In this paper, we propose an effective self-embedding authentication watermarking method for tampered location detection and image recovery. The proposed detection method is classified into block-wise and pixel-wise. In block-wise detection, if the size of the block is small, the false positive rate (FPR) will be low. In pixel-wise detection, when the tampered pixels are detected, only the corresponding pixel area is marked. Therefore, the FPR will be lower than that of the block-wise detection. The experimental results demonstrate that the proposed method was effective, and accurate tamper detection and high-quality recovery can be realized even in highly tampered images.

A Comprehensive Review of Artificial Intelligence in Prostate Cancer Care: State-of-the-Art Diagnostic Tools and Future Outlook.

Prostate cancer remains a significant global health challenge, characterized by high incidence and substantial morbidity and mortality rates. Early detection is critical for improving patient outcomes, yet current diagnostic methods have limitations in accuracy and reliability. Artificial intelligence (AI) has emerged as a promising tool to address these challenges in prostate cancer care. AI technologies, including machine learning algorithms and advanced imaging techniques, offer potential solutions to enhance diagnostic accuracy, optimize treatment strategies, and personalize patient care. This review explores the current landscape of AI applications in prostate cancer diagnostics, highlighting state-of-the-art tools and their clinical implications. By synthesizing recent advancements and discussing future directions, the review underscores the transformative potential of AI in revolutionizing prostate cancer diagnosis and management. Ultimately, integrating AI into clinical practice can potentially improve outcomes and quality of life for patients affected by prostate cancer.

Detection of SARS-CoV-2 BA.2.86 by lateral flow devices.

We evaluated the performance of 12 lateral flow devices by assessing their analytical sensitivity for SARS-CoV-2 variant BA.2.86. Kits from ACON, Orient Gene, Xiamen Biotime, Getein, and SureScreen detected variant BA.2.86 to sufficient sensitivity levels, comparable to those observed with previous Omicron variants. The stocks of lateral flow devices currently held by the UK government do not currently need changing for deployment for this variant.

Cyberloafing: Exploring the Role of Psychological Wellbeing and Social Media Learning.

Due to the advances in internet communications technology (ICT), the use of digital devices, such as laptops, tablets, or smartphones, in the educational setting has become very common among young people. A considerable body of research has shown that there are adverse effects of in-class internet usage, termed "cyberloafing" on students' academic performance, making it a rising concern for scholars. Within this context, the present study examines cyberloafing as a multidimensional construct and studies the mediating effects of psychological wellbeing and social media learning between cyberloafing behaviour and cyberloafing activities of students. Using an online survey, data was collected from 240 undergraduate and graduate students at a private university in India. The data were analyzed using structural equation modelling and mediation analysis. The results indicate that cyberloafing behaviour negatively influences student's psychological wellbeing, whereas psychological wellbeing is positively related to cyberloafing activities. It was also found that, on one hand, cyberloafing behaviour negatively influences social media learning, whereas social media learning did not have any effect on cyberloafing activities in students. This study highlights that it is crucial for educators and course instructors to incorporate appropriate practices and interventions to manage the misuse of the internet through cyberloafing in classrooms.

Communication Apprehension and Psychological Well-Being of Students in Online Learning.

The current pandemic has modified how education, learning, and technology interact with one another inside universities. The usage of technology for instructional purposes raises the question of whether learning that happens in an online environment is as effective as traditional classroom models. Within this context, this study explores the psychological well-being of students during the COVID-19 pandemic, using an online cross-sectional survey. Data were collected from 246 university students currently studying at a private university in India. Hierarchical regression analysis and structural equation modelling were used to study the mediating effects between communication apprehension, perceived learning, and psychological well-being under the moderating effects of intention to use social media and psychological stress. Results show that higher intentions to use social media alleviated the negative effects of communication apprehension on perceived learning. Interestingly, it was also found that perceived learning had a significant positive relationship with psychological well-being when students experienced higher levels of psychological stress (eustress). Based on the technology acceptance model (TAM) and the transactional theory of stress and coping, we attempt to integrate the findings related to these theories, which can be considered distinct to previous studies. Implications, limitations, and future directions for research and practice have also been discussed.

A protocol for representative sampling of solid tumors to improve the accuracy of sequencing results.

Owing to spatial segregation of tumor subclones, solid tumor sampling using formalin-fixed, paraffin-embedded blocks is often inadequate to represent the genomic heterogeneity of solid tumors. We present an approach, representative sampling, to dissect and homogenize leftover residual surgical tissue prior to sequencing. We also detail optional tumor cell enrichment and DNA preparation. This method, applicable only to surgically removed tumors with leftover tissue, facilitates robust sampling to avoid missing or over-representing actionable variants. For complete details on the use and execution of this protocol, please refer to Litchfield et al. (2020).