The fast-growing field of nanotheranostics is revolutionizing cancer treatment by allowing for precise diagnosis and targeted therapy at the cellular and molecular levels. These nanoscale platforms provide considerable benefits in oncology, including improved disease and therapy specificity, lower systemic toxicity, and real-time monitoring of therapeutic outcomes. However, nanoparticles' complicated interactions with biological systems, notably the immune system, present significant obstacles for clinical translation. While certain nanoparticles can elicit favorable anti-tumor immune responses, others cause immunotoxicity, including complement activation-related pseudoallergy (CARPA), cytokine storms, chronic inflammation, and organ damage. Traditional toxicity evaluation approaches are frequently time-consuming, expensive, and insufficient to capture these intricate nanoparticle-biological interactions. Artificial intelligence (AI) and machine learning (ML) have emerged as transformational solutions to these problems. This paper summarizes current achievements in nanotheranostics for cancer, delves into the causes of nanoparticle-induced immunotoxicity, and demonstrates how AI/ML may help anticipate and create safer nanoparticles. Integrating AI/ML with modern computational approaches allows for the detection of potentially dangerous nanoparticle qualities, guides the optimization of physicochemical features, and speeds up the development of immune-compatible nanotheranostics suited to individual patients. The combination of nanotechnology with AI/ML has the potential to completely realize the therapeutic promise of nanotheranostics while assuring patient safety in the age of precision medicine.

Farm households in developing countries are often involved in a variety of livelihood income-generating activities to achieve basic needs and enhance food security. However, little attention has been given to investigating the effect of livelihood diversification strategies on the adoption of agricultural land management practices. This study explored the nexus between livelihood diversification and Agricultural Land Management (ALM) practices in the Southern Ethiopian Highlands. Data for this study were gathered through a structured questionnaire, interviews, and focus group discussions. A total of 423 sample respondents were selected by using multistage random sampling techniques. The data were analyzed using the Inverse Herfindahl Hirschman Diversity Index (IHHDI), the multinomial logit model (MNL), and the probit regression model. The findings of the study revealed that on-farm income activities are the most dominant livelihood income strategies (69.1%), followed by non-farm (21%) and off-farm (9.64%). The multinomial logit model analysis demonstrated that variables such as sex, education, family size, distance to market, land size, extension contact, membership in cooperatives, and household income were the major drivers of farmers income diversification activities (p<0.05). The results of the probit analysis indicated that income from crop production, daily labor work, rents from farmland, and farm assets have a positive and significant effect on households' decisions to implement ALM practices. In contrast, incomes from remittance and migrant sources have a negative but statistically significant impact on the adoption of ALM measures. The farm household sources of income-generating strategies substantially affected the adoption intensity of ALM measures. Income generated from the on-farm sector alone cannot be considered a core income-generating activity for households or a means of achieving food security. Therefore, land management policies and program implementations should consider farmers’ livelihood diversification and income-generating strategies. In addition, such interventions need to promote sustainable farming practices, enhance innovation, and related measures for the adoption of ALM measures to ensure land sustainability.

Static atomic charges affect key ground-state parameters of quasi-planar boron clusters B_n, n ≤ 20, which serve as building blocks of borophenes and other two-dimensional boron-based materials promising for various advanced applications. Assuming that the outer valence shells partial electron density of the constituent B atoms are shared between them proportionally to their coordination numbers, the static atomic charges in small planar boron clusters in the electrically neutral and positively and negatively singly charged states are estimated to be in the ranges of –0.750e (B₇⁰) to +0.535e (B₂₀⁰), –0.500e (B₇⁺, B₈⁺, and B₉⁺) to +0.556e (B₁₇⁺), and –1.000e (B₇^–) to +0.512e (B₂₀^–), respectively.

The rise of internet-based pharmacies has transformed the healthcare sector, giving patients access to medications, information, and direct interaction with pharmacists. While online pharmacies have become popular around the world, there are challenges hindering their widespread use in developing countries due to a limited understanding of the factors affecting their acceptance and usage. To bridge this knowledge gap, a study utilized a model combining the unified theory of acceptance and use of technology (UTAUT 2) with the technology acceptance model (TAM) to explore the drivers behind online pharmacy usage in Oman. Through this framework, twelve hypotheses were. A survey involving 378 individuals familiar with online pharmacies was conducted. Structural equation modeling (SEM) was applied to analyze the data and test these hypotheses. The results indicate that factors such as perceived expectancy effort expectancy and facilitating conditions hedonic motivation, habit perceived risk, technology trust, and technology awareness play roles in influencing the adoption of online pharmacies in Oman. The findings suggest that personal innovation plays a moderating role in the connection between perceived risk and behavioral intention, while it has a negative moderating influence on the relationship between technology trust and behavioral intention. Word of mouth was identified as a moderator in enhancing the correlation between behavioral intention and online pharmacy adoption. This research emphasizes the moderating relationship of personal innovation and word of mouth on shaping consumer attitudes towards online pharmacies and their acceptance. In summary, these results add to the existing knowledge on pharmacy adoption and in developed areas such as provide practical insights for online pharmacy providers to improve their offerings and attract a larger customer base.

This study explores approaches to optimizing inclusive education through international and local perspectives. It examines the role of educators in inclusive settings, highlights strategies for early detection of children’s developmental needs, and evaluates inclusive school management practices. Using qualitative case study methods, the research includes comprehensive observations and interviews at Fatma Kenanga Islamic Character School. Findings emphasize the importance of individualized learning plans, shadow teacher involvement, and collaborative stakeholder engagement. Integrating global insights, this study contributes to advancing inclusive education practices in Indonesia and beyond.

The rapid growth of e-commerce in South Africa has increased the demand for efficient last-mile delivery. Motorcycle delivery drivers play a crucial role in the last-mile delivery process to bridge the gap between retailers and consumers. However, these drivers face significant challenges that impact both logistical efficiency and their socio-economic well-being. This study critically analyzes media narratives on the safety and working conditions of motorcycle delivery drivers in the e-commerce sector in South Africa. The thematic analysis of newspaper articles identified recurring themes. This study reveals critical safety and labor vulnerabilities affecting motorcycle delivery drivers in South Africa’s e-commerce sector. Key findings include heightened risks of violence, hijackings, and road accidents, exacerbated by inadequate infrastructure and safety gear. Coupled with low wages, job insecurity, and limited benefits, these conditions expose drivers to significant precarity. Policy interventions are urgently needed for driver safety and sustainable logistics. By integrating insights from multiple disciplines, this study offers a comprehensive understanding of the complex challenges within this rapidly growing sector.