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Assessing soft skills in primary education requires observable indicators that inform teaching without reducing children to fixed labels. This conceptual conference paper proposes a brief formative as…

Assessing soft skills in primary education requires observable indicators that inform teaching without reducing children to fixed labels. This conceptual conference paper proposes a brief formative assessment procedure connecting a learning target, an accessible opportunity, a documented response, and a subsequent instructional decision. Selected scholarship on social and emotional learning and educational assessment informs the design. Communication, collaboration, self-regulation, and responsible decision-making are illustrated through indicators with suggested adaptations for earlier and later primary grades. The procedure distinguishes absence of opportunity from unsuccessful performance and records assistance separately from response quality. An illustrative classroom episode shows how evidence can guide feedback and re-observation. The proposed indicators are not standardised measures or developmental norms; their clarity, accessibility, and consistency require empirical examination. No original participant data are reported.

Initial release of nf-core/tumourevo a bioinformatics pipeline to model tumour evolution that can run the following tools: VEP CNAqc TINC VIBER MOBSTER PyClone-VI ctree SparseSignatures SigProfiler

In 1941, the Germans deported and murdered almost all the local Polish Jews from Dawidgródek. Among those murdered were Zygmunt and Adela Skotnicki, the parents of Aleksander Skotnicki. Despite…

In 1941, the Germans deported and murdered almost all the local Polish Jews from Dawidgródek. Among those murdered were Zygmunt and Adela Skotnicki, the parents of Aleksander Skotnicki. Despite his excellent education, his good position in Warsaw, and his family, Aleksander Skotnicki left his wife, Genowefa, and daughter and crossed the Bug River to the vicinity of Pińsk, where he joined the partisans in order to avenge the deaths of his parents. He adopted the pseudonym “Zemsta” (“Revenge”). To me, the veterinarians of that period were admirable citizens of the young Polish Republic, distinguished by courage and patriotism.

This repository provides a framework for studying disordered Heisenberg spin chains using both classical and quantum approaches. It combines tensor network simulations and quantum hardware execution t…

This repository provides a framework for studying disordered Heisenberg spin chains using both classical and quantum approaches. It combines tensor network simulations and quantum hardware execution to enable a direct comparison between classical ground-state methods and variational quantum algorithms. The classical simulations include Density Matrix Renormalization Group (DMRG) calculations and variational circuit simulations implemented with the quimb library.  The quantum part implements variational circuits based on strong disorder renormalization group (RG) singlet structures and executes them on IQM backends. Error mitigation techniques are included, such as Zero Noise Extrapolation (ZNE), twirling, and TREX calibration. Measurement results are processed to obtain expectation values and energy estimates. The repository is organized into three main components:- `simulation`: classical DMRG and variational tensor network simulations- `experiment`: execution of variational circuits with error mitigation on quantum hardware- `data`: datasets used for benchmarking and analysis - `data_shots`: shot results from running the models on IQM devices This code accompanies the study “Emergent-Coupling-Based Ansatz Evaluated on a Superconducting Quantum Processor” and enables reproducibility of the numerical and experimental results presented therein.

Figure 1. Conceptual framework linking production, market access and household welfare. Figure 1 summarises the study’s conceptual transmission mechanism. Farm production and resource exposure i…

Figure 1. Conceptual framework linking production, market access and household welfare. Figure 1 summarises the study’s conceptual transmission mechanism. Farm production and resource exposure influence market access and travel costs, which subsequently affect prices, wages, labour allocation and household consumption welfare. The integration channel operates through stronger competition, lower transaction costs and improved conversion of production into consumption. The pressure channel captures the possibility that local price increases, labour reallocation, congestion and unequal bargaining power may weaken or redistribute the welfare gains from improved connectivity. Figure 2. Marginal association of log production with log consumption across market access and resource dependence. Figure 2 plots the marginal association between agricultural production and household consumption over the observed market-access range at low, median and high levels of resource dependence. The three lines slope upward, indicating that better market access strengthens the conversion of production into consumption welfare. The slope is steepest under low resource dependence and weakest under high resource dependence, showing that resource dependence attenuates, but does not reverse, the production-access welfare premium. The shaded bands represent 95% confidence intervals. Figure 3. Country-specific production-by-market-access estimates with 95% confidence intervals. Figure 3 compares the production-by-market-access coefficient across Ghana, Mozambique, Nigeria, Tanzania, Uganda and Zambia. Every point estimate is positive, and every 95% confidence interval lies above zero, indicating a consistently positive production-access complementarity across the six countries. The estimated association is strongest in Mozambique and Tanzania and smallest in Nigeria and Ghana. The wider interval for Mozambique reflects lower statistical precision associated with its smaller national sample. Sources of data The empirical dataset combines harmonised household-survey observations with spatial-accessibility, geological, climatic, nighttime-lights, price and labour-market information. The complete analytical file contains 68,000 household observations from Ghana, Mozambique, Nigeria, Tanzania, Uganda and Zambia. Country survey names, waves, panel structures, observation counts and regional coverage are documented in the Survey_Metadata worksheet of the replication workbook.

The increasing demand for intelligent, low-latency services in edge–cloud continuum systems poses new challenges for dynamic and efficient task offloading. We propose a Multi Agent Reinforcement…

The increasing demand for intelligent, low-latency services in edge–cloud continuum systems poses new challenges for dynamic and efficient task offloading. We propose a Multi Agent Reinforcement Learning (MARL) framework for dis tributed task offloading under partial observability, where each device offloads only a portion of its computation to a target edge server while executing the remaining portion locally (partial offloading). The problem is formulated as a Markov Decision Pro cess (MDP), where each device independently learns an optimal policy under partially observable system states. To address the non-convexity, high-dimensional state space, and continuous ac tion space, we develop a multi-agent Advantage-Weighted Actor Critic (AWAC)-enhanced Proximal Policy Optimization (PPO) based computation offloading algorithm. The proposed method combines the stable policy updates of PPO with an advantage weighting mechanism inspired by AWAC to emphasize higher quality actions during training. To encourage cooperation without inter-device communication, a shared global reward aligned with system cost is employed. Extensive simulations demonstrate rapid convergence and significant improvement in overall system cost compared with baselines, e.g., Deep Deterministic Policy Gradient (DDPG) and Deep Q-Network (DQN).

The development of critical thinking skills has become one of the primary goals of modern education, particularly in English language teaching (ELT). In the twenty-first century, language learners are…

The development of critical thinking skills has become one of the primary goals of modern education, particularly in English language teaching (ELT). In the twenty-first century, language learners are expected not only to acquire linguistic competence but also to analyse information, solve problems, make informed decisions, and communicate effectively. Project-Based Learning (PBL) and other modern teaching approaches have emerged as effective methods for promoting critical thinking while improving students' language proficiency. This paper discusses the role of PBL and contemporary instructional strategies in developing critical thinking skills among English language learners.

Fe-N-C catalysts are the most promising non-precious alternatives to platinum group metals (PGMs) for the acidic oxygen reduction reaction (ORR) in proton-exchange membrane fuel cells (PEMFCs). Howeve…

Fe-N-C catalysts are the most promising non-precious alternatives to platinum group metals (PGMs) for the acidic oxygen reduction reaction (ORR) in proton-exchange membrane fuel cells (PEMFCs). However, their practical application is significantly limited by the intrinsic trade-off between activity and stability. Herein, we propose an advanced integrated framework combining AI-based large language models (LLMs) with operational DFT calculations to elucidate the factors controlling the ORR activity-stability trade-off in Fe-N-C catalysts under acidic conditions. Results show that Fe single atoms coordinated with asymmetric N atoms at a moderate oxidation state lead to a moderate-strength Fe-N bond. This configuration significantly reduces Fe dissolution, improves the adsorption energetics of key ORR intermediates, and ultimately breaks the activity-stability trade-off. Leveraging this computational guidance, we experimentally synthesize a FeN4 site coordinated with a mixture of asymmetric pyrrolic and pyridinic N atoms in Fe-N-C catalysts. This catalyst intrinsically maintains a moderate Fe oxidation state that facilitates an optimal Fe-N bond strength, thereby delivering a high acidic ORR cycle stability (<4% activity loss after 30,000 cycles) while maintaining high activity (half-wave potential (E1/2) of 0.825VRHE), significantly breaking the activity-stability trade-off. This work unveils the atomic-scale mechanisms controlling the trade-off between ORR activity and stability in Fe-N-C catalysts under acidic conditions, paving the way for accelerating the discovery of more active and stable Fe-N-C catalysts.