Frequent consumption of aflatoxins-contaminated spices has been linked to serious adverse health effects among consumers. The likelihood of exposure to these toxins is influenced by the level of public awareness. Controlling aflatoxins contamination throughout the food chain is critical for public health. This study aimed to assess the handling practices and awareness of aflatoxin contamination among micro- and small-scale spice processors. A total of 60 processors from 4 districts of two regions of Tanzania were interviewed. The results showed that while 56.7% of interviewed processors were aware of aflatoxin contamination in spices primarily through training (38.3%) and mass media (30%). However, there were still misconceptions regarding the causes and effects of aflatoxins to human health. It was observed that, poor drying and storage practices, inadequate monitoring of processors aggravated the situation. Nonetheless, all interviewed processors expressed willingness to participate in training programs to ensure quality and safety along the chain. The study findings underscore the necessity for targeted interventions to reduce aflatoxin risks in the spice value chain. These should include strengthened food safety inspections and enforcement, as well as tailored training and support for micro and small-scale spice processors. Enhancing their knowledge and ability to adopt proper handling, drying and storage practices is critical for enhancing food safety and safeguarding public health.

Introduction: Pain is considered as the fifth vital sign that should be considered in assessing patients. For clinicians to evaluate and determine the right pain interventions, there should be parameters such as pain scale. Our objective in this study is to determine factors affecting pain scale preferences in suburban and rural populations. The pain scales used in this study are FPS-R (Faces Pain Scale-Revised), VRS (Verbal Rating Scale), VAS (Visual Analogue Scale), and NRS (Numering Rating Scale). Method: This study uses observational design with an interview approach and a cross-sectional study. Areas covered are within Indonesia, which are marginal areas of Tangerang district border, and two rural areas in Serukam, West Kalimantan, and Soe, East Nusa Tenggara. Data collected will be analyzed using SPSS 25 software. Result: Populations within the suburban areas prefer NRS (52.08%) as their pain scale, and populations in rural areas prefer FPS-R 76.92%). Factors affecting pain scale preferences are location areas, as well as last education, with statistical significance of p<0.05. Discussion: Our study showed that the choice of several pain scales is not appropriate for specific demographics due to the complexity of these scales. Factors that should be considered are the location areas and education level, as some population in remote areas have better understanding of simpler pain scales. Conclusion: Complexity or simpler components may be an underlying reason for the preference of score selection to assess pain scales in some population. Therefore, the selection of pain scales should be adjusted to specific demographics so that clinicians can provide appropriate management with appropriate pain scales.

Artificial Immune Systems (AIS) are bio-inspired computational frameworks that emulate the adaptive mechanisms of the human immune system, such as self/non-self discrimination, clonal selection, and immune memory. These systems have demonstrated significant potential in addressing complex challenges across optimization, anomaly detection, and adaptive system control. This paper provides a comprehensive exploration of AIS applications in domains such as cybersecurity, resource allocation, and autonomous systems, highlighting the growing importance of hybrid AIS models. Recent advancements, including integrations with machine learning, quantum computing, and bioinformatics, are discussed as solutions to scalability, high-dimensional data processing, and efficiency challenges. Core algorithms, such as the Negative Selection Algorithm (NSA) and Clonal Selection Algorithm (CSA), are examined, along with limitations in interpretability and compatibility with emerging AI paradigms. The paper concludes by proposing future research directions, emphasizing scalable hybrid frameworks, quantum-inspired approaches, and real-time adaptive systems, underscoring AIS's transformative potential across diverse computational fields.

Recent field investigations, performed across some of the less floristically known sectors of Calabria, have led to the discovery of Salsola tragus and Thymelaea gussonei, two new species for the regional vascular flora. By providing crucial biogeographical and taxonomic remarks, this work aims to contribute to the improvement of the knowledge of the rich, diversified and still poorly known native flora of Calabria. The biogeographical value of these new findings underlines the decisive role of field survey in the enhancement of the information on regional biodiversity, the essential basis for every further ecological study and conservation effort.