The global significance of SMEs has traditionally been recognized as a key driver of economic growth and sustainability. The emergence of digital technologies and Information and Communication Technology for Development (ICT4D) holds significant potential to further enhance this impact. However, SMEs in developing countries have faced challenges in adopting sustainable, resource-intensive digital systems. Factors such as limited skills, financial constraints, and the alignment of suitable solutions hinder this adoption. To address these challenges and promote sustainable digital transformation, this study proposes a two-tier approach. The first prong employs Natural Language Processing (NLP) techniques, including Word2Vec, for global analysis and digital systems identification. The second prong involves a country-specific analysis of SMEs’ digital requirements. This two-tier analysis aims to uncover the actual digital needs of SMEs while shedding light on high-intensity global SME activities that, if integrated through ICT4D, could effectively address the risks and challenges SMEs face in adopting, implementing, and maintaining digital systems. In addition, the study develops systems required by SMEs to optimize their business processes and production, thereby promoting their growth and sustainability in the digital era. The results of this study demonstrate the effectiveness of these proposed methods in addressing digital challenges for SMEs and fostering sustainable development.

The transition to affordable and clean energy sources is essential for creating a sustainable future. Green hydrogen, as an emerging energy carrier, has the potential to meet increasing energy demands while mitigating environmental impact and achieving SDG 7. The incorporation of green hydrogen into any energy system is a complex process that entails numerous challenges. These challenges include fluctuating energy outputs from renewables, the technical demands of storing hydrogen across varying pressures and temperatures, the intricate logistics required for its safe transportation, skills, and other considerations. Given these complexities and the constantly evolving knowledge around green hydrogen, it becomes important to identify skills and technologies propelling the development of the green hydrogen value chain. This study presents a systematic approach for identifying and analysing the skills and technologies pivotal to the green hydrogen value chain. Using natural language processing techniques, hard skills, soft skills, and emerging technologies are extracted and categorised from published literature. A token classification model, built upon the pre‐trained BERT architecture and fine‐tuned with domain‐specific data, enables the precise identification of contextually relevant entities. The results reveal a taxonomy of skills and technologies, highlighting critical workforce capabilities such as material science expertise, project management, and leadership skills, alongside emerging technologies like PEM electrolysers and nanostructured materials. These results provide actionable insights for addressing skill sustainability, fostering workforce development, advancing decent work and economic development, and guiding technological innovation to strengthen the green hydrogen value chain. The integration of real‐time updates ensures that the analysis remains current.

The $B\left(E2\right)$ value for the decay of the $2_1^{+}$ state of ${}^{16}\mathrm{C}$ to ground has been the subject of much discussion. The existing measurements extend over a large range, almost an order of magnitude, from 0.63 to $4.15e^2{\mathrm{fm}}^4$. Analyses assuming a simple model of two neutrons coupled to a ${}^{14}\mathrm{C}$ core give reasonable agreement but require the inclusion of a large effective charge for the neutrons. To assess this situation, a large-scale $(2+4)\hslash \omega$ shell-model calculation of ${}^{16}\mathrm{C}$ has been made from which the wave functions have been used to obtain the $B\left(E2\right)$ value. As a check, comparison is made with available data on the spectrum of ${}^{16}\mathrm{C}$ and intermediate-energy elastic proton scattering. It is found that with the new model a much smaller effective charge is needed, if at all, to explain the accepted $B\left(E2\right)$ value.

The spectra of mass-11 nuclei are unusual, and so pose a challenge for nuclear-structure theory. Relating to nucleon emission, the set of isobars range from being well-bound ( $$^{11}$$11 B, $$^{11}$$11 C) through weakly bound ( $$^{11}$$11 Li, $$^{11}$$11 Be), to being proton unstable ( $$^{11}$$11 N, $$^{11}$$11 O). To add complexity, the weakly bound $$^{11}$$11 Li takes the form of a two-nucleon halo nucleus. A self-consistent approach to understand this set of nuclei is especially important as the mirror pair $$^{11}$$11 Be- $$^{11}$$11 N exhibit a parity-inverted ground state compared to their neighboring nuclei. Herein, the Multi-Channel Algebraic Scattering method (MCAS) has been used to describe the low excitation spectra of those isobars in terms of nucleon-nucleus clusters. A collective model description of the low-excitation states of the mass-10 mass-10 core nuclei has been used to form the coupled-channel interactions required in the method. For comparison, and to understand the underlying configurations, a shell model approach has been used to obtain those spectra with no-core $$(0+2+4)\hbar \omega $$( 0 + 2 + 4 ) ħ ω and $$(0+2)\hbar \omega $$( 0 + 2 ) ħ ω shell-model spaces for the mass 10 and mass 11 nuclei respectively. The results of the calculations suggest the need of a strong coupling in the collective coupled-channel vibrational model. In particular, the strong coupling of the collective $$2^+_1$$2 1 + state of $$^{10}$$10 Be to the valence neutron plays a decisive role in forming the positive parity ground state in $$^{11}$$11 Be; an effect confirmed by the shell-model results.

The investigation of many astrophysical processes is dependent upon an understanding of nuclear reaction rates. However, nuclear capture reactions of astrophysical interest occur at extremely low energies, taking place at the Gamow energy within the stellar environment. Hence, they are hard to study experimentally due to Coulomb repulsion. They may also involve compound resonances stemming from a delicate interplay of many quantum states in the colliding bodies. The multi-channel algebraic scattering (MCAS) method is one that addresses both of these challenges; it has a history of successfully modelling narrow compound resonance structures, incorporating as many channels as are important for a given problem, but is also proven in recreating the lowenergy, non-resonant elastic scattering cross sections needed for these astrophysics problems. We provide an overview of MCAS’ techniques of modelling elastic scattering reactions, how these may be extended to capture reactions, and current work in this area.