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Corresponding with matters of pedagogy: Bauhaus, Black Mountain and beyond.
Full text linkThis chapter explores the relationship between the modern art school approach to un-learning and anthropology; with specific reference to Bauhaus, Black Mountain and its global resonance and continuum. As Tim Ingold reminds us, the artist-educator Paul Klee repeatedly insisted, and demonstrated by example, that the processes of genesis and growth that give rise to forms in the world we inhabit are more important than the forms themselves. As Klee wrote in his notebook, ‘Form-giving is movement, action. Form-giving is life’ (Klee). This, in turn, lay at the heart of his celebrated ‘Creative Credo’ of 1920: ‘Art does not reproduce the visible but makes visible’ (Klee). It does not, in other words, seek to replicate finished forms that are already settled, whether as images in the mind or as objects in the world. It seeks, rather, to join with those very forces that bring the form into being (Ingold). Using this statement as a trigger the text will explore how Paul Klee’s pedagogic approach played a significant part in the formation of the art school ecology and how that relates to the way we live our lives and shape and form our futures
Longitudinal analysis of explosive physical performance outcomes of professional athletes across multiple football codes: an investigation of systematic change and relative variation.
No full textThe aims of this study were to: 1) investigate the within and across season changes in explosive physical performance outcomes including jump height (JH), relative peak power, and maximum sprinting velocity for different football codes; 2) estimate associations between time-lagged training load variables and JH; and 3) quantify levels of within athlete variability and differences between codes. Retrospective physical performance, on-field, and strength and conditioning (S&C) data were collected from 61 athletes across two professional sports teams (Australian Rules Football: n=27; Rugby Union: n=34). Linear mixed models with fixed effects of time (e.g. season and component of season stage), code, and position combined with random effects (e.g. intercepts and slopes for athlete) were used to model changes over time. Additionally, athlete level linear regressions were conducted to describe individual variability. Regression coefficients describing systematic change were small with the largest coefficient identified for within season JH (β = 0.27 [95% CI: 0.08 to 0.46 cm]). Moderate to large negative correlations (r = -0.41 to -0.66) were obtained between random intercepts and slopes for all outcomes. Analysis of within athlete variability identified larger variation for Rugby Union athletes and for latter stages of the season. Collectively, the findings show limited systematic changes in physical performance variables of professional football code athletes and any improvements may be dependent on baseline capacity
Ascertaining the reasons for escalation of disagreements over extension of time assessments from construction delay claims into disputes.
Full text linkDisputes over delay assessments are costly, persistent, prevalent worldwide, often funded by taxpayers, and negatively impact productivity in the construction sector. The identified academic literature argues that the main causes of the escalation of disagreements over delay assessments from contract claims into disputes (or factors) are objective factors, particularly unavailability and/or inadequacy of relevant project data. However, those findings are not based on comprehensive investigations of all factors involved, employing research methodologies that rely upon real-life project data. This article contributes to the fulfilment of the aforementioned knowledge gap. Published literature and twenty-one case studies were evaluated to identify the factors. The research findings revealed that although data-related issues were often important factors, they were not the main and/or most frequently identified ones. Subjective factors, including manipulation of programme activity completion dates, reliance on biased assumptions when data is unavailable, misinterpretation of material records, and self-serving delay analysis, were the main factors. The findings suggest that the root cause of this issue is the exploitation of systemic flaws, including the unavailability of good/best practice guidance on assessing the impact of delays, deficient contract provisions, inadequate impartiality, divergent priority of interests, unexploited technologies, and the confidential nature of dispute resolution methods
Adjunctive multicomponent crystals of two anti-tubercular drugs with pyridoxine.
Full text linkCocrystallisation is a well-established path for altering the physicochemical properties and bioavailability of active pharmaceutical ingredients (APIs). A common side effect of anti-tubercular medicines is the depletion of group B vitamin reserves in TB patients. Co-administration of supplements such as pyridoxine (vitamin B6) during TB therapy may be used to ameliorate the harmful side effects of vitamin B6 deficiency. Mechanochemical grinding and solvent evaporation experiments using pyridoxine (PN) with 4-aminosalicylic acid (PAS) and separately with pyrazinecarboxylic acid (PCBA) were conducted. The bulk powder and crystal analysis was performed using FTIR, PXRD, DSC, TGA and SCXRD. The isolation and characterization of two multicomponent salts containing pyridoxine, i.e., PN-PAS·H2O and PN-PCBA, were completed. Mechanochemistry is an efficient method for the preparation of cocrystals. The drug–vitamin combinations may be useful for the development of new treatment regimens with potentially improved therapeutic outcomes and reduced adverse effects
Ensemble of regressors for gross error identification: an optimisation approach.
Full text linkAccurate measurement is essential for reliable process monitoring and control in the chemical industry. However, measurement systems are often affected by gross errors caused by sensor faults, leaks, or transmission issues. These errors can severely degrade data reconciliation and decision-making, making robust detection methods critical for industrial reliability. In this paper, we present a new approach to gross error detection using an ensemble of machine learning regressors. The method combines predictions from a diverse set of 51 regression models and selects the most effective subset using optimisation algorithms. We explore three nature-inspired optimisers - Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Differential Evolution (DE) - to find the best combination of models. The selected ensemble is then used to predict the magnitude of gross errors in process measurements. We evaluate the approach using ten benchmark datasets with artificially injected errors. Our results show that the proposed method outperforms traditional techniques and individual regressors when using optimisation for ensemble selection. These findings highlight the practical potential of optimised heterogeneous ensembles for improving gross error detection in industrial applications
Revolution or riddle? Decoding the Moveable Transactions (Scotland) Act 2023.
Full text linkThis paper examines the Moveable Transactions (Scotland) Act 2023 to assess whether it represents a genuine revolution in Scots property law or an interpretative riddle for commercial practice. In force from 1 April 2025, the Act replaces historic publicity mechanisms with a registration-based system centred on the Register of Assignations and the Register of Statutory Pledges. It introduces registration as an alternative to intimation for assignations and creates the statutory pledge, thereby removing the possession requirement for fixed security and expanding the collateral base to include intellectual property and financial instruments. Adopting a doctrinal and comparative approach, the paper situates the reform within its historical context and against international notice filing models. It argues that the Act delivers structural modernisation through digital publicity, broader asset coverage, and clearer ranking rules. However, significant interpretative and operational questions remain, including consent-based extinction under section 52, insolvency cut offs for future assets under section 50(3), and the transfer of accessory security under section 16, as highlighted in McKinlay v Avellierie Ltd [2025] SAC (Civ) 6. The Act is therefore revolutionary in design, yet riddled in execution
Rapid and energy-efficient synthesis of nickel borate via solution combustion method for esterification reactions.
No full textIn this study, nanostructured nickel borate (Ni3(BO3)2) catalysts were synthesized via the solution combustion method using six different fuels: glycine, carbohydrazide, citric acid, oxalyldihydrazide, urea, and hexamethylenetetramine. The influence of fuel type on the structural properties of the resulting materials was systematically evaluated, and glycine was identified as the most suitable fuel. The glycine-assisted catalyst exhibited a surface area of 14.67 m²/g along with mesoporosity. Its catalytic performance was evaluated in the esterification of acetic acid with benzyl alcohol. Under optimized conditions (120 °C, 20 mg catalyst, 300 min, alcohol/acid molar ratio of 1:30), complete conversion with 100% selectivity was achieved. Furthermore, the catalyst demonstrated excellent thermal stability and reusability over multiple cycles with minimal activity loss. This work presents a green, cost-effective, and scalable strategy for the synthesis of nickel borate catalysts and underscores their potential for application in sustainable liquid-phase organic transformations, particularly esterification reactions
Evaluating cross-domain sentiment analysis using convolutional neural network for Amazon dataset.
Full text linkSentiment Analysis (SA) has garnered extensive research attention over the past decades as a means to comprehend users' attitudes and opinions in various domains. With the proliferation of online communities and the rapid generation of social media content, understanding sentiments has become crucial for decision-makers and stakeholders. Cross-Domain Sentiment Analysis (CSDA) is the process of analysing and interpreting sentiments in text data across different subject areas or contexts, accounting for the varying nuances and contextual differences in sentiment expression. The problem of CDSA poses a significant challenge in the field of Natural Language Processing (NLP), as the sentiment polarity of words and expressions can vary drastically across different domains. For instance, a word like "unpredictable" can convey positive sentiment in the context of a movie review but may signify negative sentiment when referring to the performance of a computer system. Deep Learning (DL), a subfield of machine learning, has shown promising results in various domains since its emergence in 2006, especially in complex problem-solving involving vast datasets. This paper aims to evaluate CDSA performance using Convolutional Neural Network (CNN) on the Amazon dataset. The study builds upon our previous research that highlighted the limitations of classical Machine Learning (ML) approaches for CDSA. The result demonstrates that the DL model is the state-of-the-art in machine learning classification tasks even though with a limited features engineering task. In conclusion, understanding people's opinions across different subjects on the internet is crucial but complex and using advanced Deep Learning methods like the Convolutional Neural Network can help address these challenges effectively
Interface issues of inorganic solid‐state electrolytes in secondary magnesium batteries.
Full text linkSolid-state magnesium batteries (SSMBs) have gained significant attention as promising candidates for next-generation safe energy storage systems because of the abundance of magnesium (Mg) in the earth's crust, superior energy density, and inherent nonflammability. However, the development of inorganic solid-state electrolytes (ISSEs), which are critical for SSMBs, is hindered by two major challenges: the limited diffusivity of Mg2+ and inefficient interfacial charge transfer kinetics between the electrodes and electrolytes. Recent advancements in material design and interfacial engineering have addressed these challenges with remarkable progress. Therefore, this review systematically discusses the mechanisms for optimizing the performance of ISSEs, focusing on ion transport kinetics, mechanical strength, and electrochemical stability. A crystal-structure-based classification framework is employed to critically analyze three major ISSE categories, including boride, oxide, and chalcogenide electrolytes. In addition, current engineering strategies for interfacial optimization in magnesium batteries are summarized. Finally, this review also highlights current challenges and possible directions for improving interfacial contacts in future practical applications. This comprehensive analysis aims to provide theoretical guidance for the development of high-energy-density SSMBs
Aerobic exercise training and VO2max: a scoping review of study populations and protocols.
No full textMaximal aerobic capacity (VO2max) is a well-established predictor of cardiovascular health, morbidity, and all-cause mortality. While many systematic reviews and meta-analyses have characterized the effects of aerobic exercise training on VO2max, they fail to capture the state of the literature as a whole. This scoping review aims to summarize the populations and training protocols used in the current literature and highlight gaps in our current understanding of the VO2max response to aerobic training. 617 studies were selected and analyzed in this review. The majority of exercise protocols used were moderate intensity continuous training (MICT; n = 363). Few studies employed high intensity interval training (HIIT; n = 102), sprint interval training (SIT; n = 70), or a combination of exercise modalities (n = 82). A large number of studies only included male participants (n = 264) while few studies only included female participants (n = 83). The majority of training interventions were shorter than three months (n = 399). Many studies failed to report information regarding participant health (n = 169) and physical activity status (n = 290). Exercise modality, sex representation, the effects of long-term training, and reporting practices represent key gaps within the literature that should be further explored in the future
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