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Exploring the impact of differences between AI streamers and human streamers on consumer purchase intention in live e-commerce: A grounded theory approach
With the rapid development of live e-commerce, AI streamers have gradually emerged as a new industry trend. However, significant differences exist between AI streamers and human streamers in terms of interaction styles, emotional expression, and user experience. How these differences influence consumer purchase intention has not yet been systematically investigated. Based on this, the present study employs grounded theory and the stimulus-organism-response model to explore the mechanism through which the differences between AI streamers and human streamers in live e-commerce affect consumer purchase intention. Data were collected through in-depth interviews and analyzed using open coding, axial coding, and selective coding. A research model was constructed, incorporating sensory differences, affective differences, and functional differences (stimulus factors), perceived entertainment and social presence (organism factor), and purchase intention (response factor), with consumer purpose as a moderating factor. Our results reveal that AI and human streamers differ in sensory, affective, and functional dimensions. Under purchase motivation, AI streamers, with their standardized and concise sensory presentation, better meet the need for quick decision-making, thus outperforming human streamers in functional differences. In contrast, under viewing motivation, human streamers excel in all three dimensions. These differences affect purchase intention through the mediating roles of perceived entertainment and social presence. Consumer purpose (purchase vs. viewing) moderates these effects. This study bridges the gap in understanding how AI and human streamers’ differences shape consumer behavior, offering practical insights for e-commerce platforms to optimize streamer strategies and guiding the anthropomorphic development of AI streamers.
Do rats double-dip food with their tails?
Preparation and application conductive concrete from iron tailings to the teaching reform in engineering materials courses
Healthcare employees’ perspectives on organizational communication about preventive mental health interventions: A focus group study
The COVID-19 pandemic exposed healthcare employees to stressful situations with possible long-term mental health consequences, stressing the need for supportive interventions. However, in practice healthcare employees’ use of preventive mental health interventions seems limited. Persuasive communication strategies may help to bridge this gap. The aim of this study was to further refine our understanding of healthcare employees’ perspectives on organizational communication about preventive mental health interventions. A qualitative approach was used, consisting of 5 focus groups with hospital workers, either with (K = 3) or without (K = 2) direct patient contact. We used vignettes as a method to discuss three different scenarios to reflect the different levels of prevention (primary, secondary, tertiary). Focus group sessions were audio-taped and transcribed verbatim. Two researchers independently analyzed the data applying thematic analysis within each prevention level. This qualitative study on the employee perspective on communication about preventive mental health interventions demonstrated an overarching funnel movement in which the source and content/channel become increasingly targeted towards the individual employee as mental health symptoms increase. The primary prevention level revealed the theme ‘Multilevel sources of communication and various channels’, the secondary prevention level revealed the theme ‘Specific sources of communication and specific channels’, and the tertiary prevention level revealed the theme ‘A central role for supervisors’. A safe culture in the workplace appeared an important prerequisite for timely discussion of employee mental health. These insights contribute to the development of more tailored organizational communication about mental health of healthcare employees.
Carbon credits are failing to help with climate change — here’s why
Investigating environmental determinants and spatiotemporal dynamics of highly pathogenic avian influenza H5N1 outbreaks in India through machine learning
TB will never end because of us: Experiences of TB preventive treatment among people living with HIV/AIDS in South Africa
Background Tuberculosis (TB) remains a major global health challenge, particularly for people living with HIV/AIDS (PLWHA). TB preventive treatment (TPT) has been found to reduce the risk of TB among PLWHA. As TPT has become a standard component of HIV care, understanding client-level perceptions and knowledge of TPT is crucial to optimizing uptake. Methods This qualitative sub-study was conducted within a cluster-randomized trial evaluating a TPT initiation strategy in two provinces of South Africa. The qualitative component explored patient understanding and experiences with HIV, TB, and TPT through in-depth interviews. PLWHA receiving care at participating public-sector healthcare facilities in the North West and Free State provinces were systematically purposively selected. Thematic analysis was used to identify themes. Results Thirty-three adult PLWHA were interviewed. Most participants understood TB, household transmission risk, and that PLWHA are more susceptible to TB. Participants were aware TB is curable and associated its risk and transmission to dirty environments, neglecting flu-like symptoms and lifestyle habits (alcohol use and smoking). Participants highlighted that health-seeking behaviors, treatment adherence, and community perception influence TB burden, stressing TB prevention and treatment as community challenges. Knowledge of TPT varied, with most participants emphasizing the need for clients to take initiative in their treatment. Participants requested that healthcare workers provide more details about TPT through posters and pamphlets in clinics, and suggested community engagement to encourage uptake. While adherence was acknowledged, concerns included side effects and the burden of taking both antiretroviral therapy and TPT. Conclusion Individual and community social and health-related factors, along with acceptability of TPT, might affect uptake and retention. While TPT was seen as important, concerns about side effects and dual treatment burdens highlight the need for improved education and support. Strengthening healthcare communication, expanding TPT information, and promoting TPT as a proactive health decision may motivate uptake.
A drug–diet combination could improve childhood cancer treatment
Distinct mechanochromic and piezochromic behaviors of thermally activated delayed fluorescence 4CzTPN crystal
Correction: Who should be first? How and when AI-human order influences procedural justice in a multistage decision-making process
Red lines for religious AI
An enhanced instantaneous detonation model for underwater explosions involving condensed explosives
Effective implementation of the Sport Education Model in physical education: A meta-analysis of participant and intervention characteristics
Despite substantial evidence supporting the positive effects of the Sport Education Model (SEM) on students’ physical abilities, mental health, and social skills, significant knowledge gaps persist regarding the moderating variables that influence its effectiveness. This study investigates the facilitative effects of SEM on students’ physical education learning and examines the Participant and Intervention Characteristics that modulate its impact. Following the PICOS framework, two researchers independently conducted a comprehensive literature search across Web of Science, Scopus, PubMed, and EBSCOhost (CINAHL with Full Text and SPORTDiscus with Full Text) databases. The quality of the included studies was assessed using the Cochrane Handbook for Systematic Reviews of Interventions, and a meta-analysis was performed on the selected studies. A total of 15 studies involving 2,890 participants were included in this meta-analysis. The results indicate that SEM significantly improves students’ physical education learning outcomes (Effect size = 0.590, 95% CI: 0.284–0.897, P < 0.001). Subgroup analyses revealed that SEM intervention was particularly effective for secondary school students (Effect size = 1.055, 95% CI: 0.361–1.759, P = 0.003), those in small class sizes (Effect size = 1.058, 95% CI: 0.314–1.802, P = 0.005), and students without prior SEM experience (Effect size = 0.604, 95% CI: 0.136–1.072, P = 0.011), and the most effective SEM intervention plan comprises 2 sessions per week (Effect size = 1.820, 95% CI: 0.486–3.154, P = 0.008), with each session lasting at least 60 minutes (Effect size = 1.002, 95% CI: 0.437–1.568, P = 0.001) and a total of no more than 18 sessions (Effect size = 0.654, 95% CI: 0.297–1.010, P = 0.001). SEM effectively enhances students’ physical education learning and positively influences their cognitive and non-cognitive abilities. The most effective intervention includes two weekly lessons of at least 60 minutes each, totaling no more than 18 lessons, targeting secondary students without prior SEM experience in small class sizes. This study offers practical recommendations for SEM implementation and theoretical support for the high-quality development of school sports.
The spectre of malnutrition is back and must be tackled — fast
PSO-DT based BagDT: a robust lightweight ensemble framework for efficient feature selection and DDoS attack detection in IoT environment
Abstract The recent decade has seen enormous growth in the Internet of Things field. This development has significantly expanded the space for cyber-threats, among which the Distributed Denial of Service attacks have become one of the most important and common threats. These attacks might severely disrupt critical services if not detected and handled on time. To provide a reliable and secure IoT environment, accurate and effective mechanisms for detecting DDoS attacks in real-time are the most required. While state-of-the-art deep learning models like CNNs and LSTMs offer high accuracy, their computational overhead often makes them unsuitable for resource-constrained IoT environments. To address this gap, we have proposed a robust hybrid framework, the PSO-DT-based BagDT ensemble model. This model utilizes Particle Swarm Optimization in combination with Decision Tree for effectively finding the best feature subset. This lowers the dimension by reducing complexity. The proposed PSO-DT feature selection algorithm is evaluated across variants of ensemble learners, namely Random Subspace KNN, AdaBoost, RUSBoost, and Bagged Decision Trees. The PSO-DT helps in reducing the computational cost and the model size. Our PSO-DT based Bagged DT model demonstrates superior performance, achieving an accuracy of 99.96 % along with a macro-average precision, recall, and F1-score of 0.99. Among all the variants, BagDT performed better with an increase in accuracy by 4.13% and a reduction in training time by 95.49%. The overall throughput is increased by 63.52% thereby confirming the efficiency of the proposed PSO-DT-based BagDT Ensemble model for providing a real-time, scalable solution that is appropriate for implementation in contemporary smart environments.
Exploring the role of routine brain imaging in detecting asymptomatic brain metastases in first diagnosed HER2-positive breast cancer
Background HER2-positive breast cancer is leading to aggressive tumor growth and a higher risk of metastasis, particularly to the central nervous system (CNS). Routine brain imaging for asymptomatic HER2-positive patients is debated, with no current consensus; Given the severe clinical implications of brain metastases, further research is needed to determine the cost-effectiveness and clinical utility of routine imaging for high-risk patients to improve outcomes and inform targeted screening protocols. Methods This retrospective, monocentric study at the General Hospital of Vienna (AKH Wien) examined female HER2-positive breast cancer patients at first diagnosis to assess brain metastasis from January 2019 to February 2024. The study included patients with asymptomatic confirmed HER2 positive breast cancer. Data were collected through comprehensive medical records and brain imaging with MRI. Results Among 110 female patients meeting the inclusion criteria, 4 (3.6%) were diagnosed with brain metastases. Ki67 showed a marginal association with brain metastasis (p = 0.054), and tumor grade was a significant predictor, with intermediate differentiated tumors (G2 vs. G3) associated with a higher risk of brain metastases (p = 0.041) and brain metases are correlating with the axillary lymphnode status and the tumor sizeAlso, the absence of positive Östrogen and Progesteron receptors is a predictor in upcoming brain metastases (p < 0.001). Other factors like age were not significantly associated. Conclusion This study found limited benefit in routine MRI for detecting asymptomatic brain metastases in HER2-positive breast cancer, given the low prevalence (3.6%). A targeted imaging approach for high-risk patients, like those with the absence of Hormon receptors and higher stage tumors, may be effective.
Longer grant cycles would boost research in Africa
Factors influencing employment and absenteeism in working age people with multiple sclerosis
IGF2BP2 contributes to thyroid cancer progression by enhancing the stability of m6A-modified CTSH mRNA
Background N6-methyladenosine (m6A) is a prevalent RNA modification in eukaryotes that regulates RNA stability and translation. Dysregulated m6A modification is implicated in cancer progression. This study investigated the role of the m6A reader protein, insulin-like growth factor 2 mRNA-binding protein 2 (IGF2 BP2), in the progression of thyroid cancer (TC). Methods Cell proliferation was assessed using cell counting kit-8 (CCK8) and 5-ethynyl-2’-deoxyuridine (EdU) assays. Cell migration and invasion were evaluated by Transwell assays. A xenograft tumor model was employed to examine the impact of IGF2 BP2 on tumor growth in vivo. Gene functional annotation was performed through GO analysis. Spearman correlation analysis was utilized to evaluate the relationship between the expression levels of cathepsin H (CTSH) and IGF2 BP2. RIP-qPCR and RNA pull-down assays were conducted to confirm the interaction between IGF2 BP2 and CTSH mRNA. Results Elevated IGF2 BP2 expression correlated significantly with advanced N stage in TC. Knockdown of IGF2 BP2 inhibited TC cell proliferation, migration, and invasion in vitro, as well as tumor growth in vivo. CTSH expression mirrored IGF2 BP2 expression. IGF2 BP2 interacted with CTSH mRNA, enhancing its stability in an m6A-dependent manner. Overexpression of CTSH counteracted the effects of IGF2 BP2 knockdown on TC cell proliferation, migration, invasion, and epithelial-to-mesenchymal transition (EMT). Conclusion IGF2 BP2 accelerates TC progression by recognizing and stabilizing m6A-modified CTSH mRNA. IGF2 BP2 and CTSH represent potential diagnostic and therapeutic targets for TC.