United States Nuclear Regulatory Commission

ABSTRACTBackgroundMany African countries, including Namibia, face challenges with the availability of essential medicines, impacting health outcomes. This study aimed to evaluate the availability of essential medicines in Namibia by examining the registration of medicines on the Namibia Essential Medicines List (NEMList) as a proxy.MethodsAn in-depth analysis of the registration of essential medicines was carried out by comparing medicines in the NEMList against registered medicines on the Namibian Human Medicines Register as of February 2024. Microsoft Excel was used to capture details about the generic names of medicines, strengths, and dosage forms in which the medicines were available. A sub-analysis of antibiotics, which classified them using the Access, Watch and Reserve (AWaRe) classification, was also conducted.ResultsA high proportion of essential medicines listed in the NEMList, 80.2% (386/481) are registered in the country. However, essential medicines only accounted for 23.7% (1,288/5,444) of all medicines on the Namibian Human Medicines Register. Among the essential medicines registered in Namibia, only 45.5% (176/386) had at least three registered products. Of the 55 antibiotics on the NEMList, 94.5% (52/55) had registered products, with 96.2% (25/26), 92.0% (23/25) and 100% (4/4) of Access, Watch and Reserve group antibiotics having registered products, respectively. Despite the high proportions of registered essential antibiotics, only 65.4% of Access group antibiotics, 68.0% of Watch group antibiotics and 25.0% of Reserve antibiotics had at least three registered products.ConclusionRegistration of essential medicines is crucial to ensure access and availability. Further studies are needed to understand the bottlenecks encountered by the Namibia Medicines Regulatory Council (NMRC) in registering essential medicines. Concerted programmes and policies to strengthen regional harmonisation of medicines registration should be developed, and essential medicines should be prioritised.

This article explores the institution of children's rights commissioner in Russia and internationally. It examines the historical background to the institution's emergence and development, as well as the specifics of its formation in modern legal systems. Particular attention is paid to the role of children's rights commissioners within government bodies and the specifics of their legal status. The objectives, powers, and functions of commissioners at the federal and regional levels, their contribution to the realization and protection of children's rights and legitimate interests, and their interactions with government agencies and society are analyzed. Practical examples of successful commissioner experience are provided. The conclusion emphasizes the importance and necessity of the institution of children's rights commissioners as an additional guarantee for protecting children's interests in the modern world.

For decades, the deconvolution analysis of the thermoluminescence glow curve has been assessed using the figure of merit (FOM). In the present study, it has been shown that the FOM is not sufficient to assess the deconvolution analysis of TL glow curves. An alternative criterion has been proposed based on the uncertainty of the deconvolution analysis. A comparison between the proposed criterion and the FOM was conducted using theoretical simulations and experimental results. It has been shown that the developed criterion can provide detailed information about the fitting quality for each region in the glow curve as well as give an overall assessment of the deconvolution process. The uncertainty of deconvolution analysis using the general-order kinetics has been estimated for various glow curves. The TL-SDA toolkit has been updated to include the feature of evaluating the uncertainty of the deconvolution process.

Abstract Ceramics, which have been manufactured at a specific location from local clayey raw materials following a particular workflow of clay paste processing, are assumed to exhibit a characteristic composition in terms of elemental concentrations, mineralogical compounds and petrographic fabric. The examination of ceramics from different manufacturing sites or regions for example through elemental analysis allows for defining compositional categories as reference for the origin of manufacture. The examination of ceramics from trading or consumption sites, on the other hand, allows for assigning them to these reference categories and, thus, for investigating their origin and dissemination. In the particular case of transport amphorae, ancient trade networks for commodities, such as wine, oil or grain, can be investigated. For the elemental analysis of archaeological ceramics commonly laboratory methods are applied, such as neutron activation analysis (NAA) or wavelength-dispersive X-ray fluorescence spectrometry (WD-XRF), providing high analytical performance requiring, though, the sampling of an albeit minute material amounts from a ceramic artifact. Handheld portable energy dispersive XRF (pXRF), on the other hand, allows for non-invasive analysis of large numbers of ceramic artifacts within comparably short time periods. A major drawback of pXRF, though, concerns the higher analytical uncertainties in terms of precision or reproducibility as well as in terms of accuracy impeding eventually the statistical data evaluation following approaches commonly applied to multivariate quantitative data collected with laboratory analyses and the comparison with external reference data. However, even though pXRF data might be more blurry or fuzzy they still represent compositional similarities or dissimilarities, which might be revealed with alternative approaches for categorization. An initial case study testing unsupervised machine learning with self-organizing maps (SOM) on a dataset of Hellenistic transport amphorae from the Paphos Agora, a market place in Cyprus, indicated the potential of automated categorization of pXRF data through machine learning. In the present case study supervised machine learning models, such support vector machines (SVM), random forest (RF) as well as supervised artificial neural networks (ANN), have been tested on pXRF data of transport amphorae from East Aegean islands and from Paphos. For this, NAA data of a part of the analysed amphora fragments have been used for predefining compositional categories in the training data. The present data repository at our laboratory comprises c. 2200 measurements of c. 1400 individual amphora fragments from production centres as well as exchange centres in the Eastern Mediterranean region. Even though this is a comparably large number of data records the generation of synthetic training data was tested. The ultimate scope of the present case study will be to train a machine learning model for automated pattern recognition and prediction of the origin of manufacture of transport amphorae in order to study trading networks in the region.

The article provides an overview of the Scientific and Practical Forum "Children's Law". Regional commissioners for children’s rights, government and public figures, law enforcement officers, educators, and scientists attended the Forum. The Forum covered a wide range of issues related to the protection of the rights and legitimate interests of minors. Special attention was paid to interdepartmental cooperation on childhood issues, the prevention of social orphan hood, the role of non-profit organizations in supporting the institution of the family, as well as legal education of the younger generation. A presentation of a unique educational publication, Children's Law, took place within the framework of the Forum.