The arbitration community has traditionally argued that arbitrators should be shielded from criminal liability for actions performed in their professional capacity. However, a global trend has emerged wherein criminal law is increasingly used to regulate arbitrators’ behavior. Central to the debate on the extent of arbitrators’ immunity from criminal prosecution are questions of whether such immunity is necessary to ensure the fairness of arbitral proceedings and the degree to which arbitrators can be trusted to fulfil their professional responsibilities. Although this topic has been extensively debated in legal scholarship, there has been a notable lack of empirical research on the implementation and effectiveness of these criminal provisions. This study addresses this gap by examining Mainland China’s use of criminal law to regulate arbitration. China is a particularly relevant case study due to its adoption of a controversial provision titled “Perversion of Law in Arbitration” in 2006. Critics have argued that the broadly defined language of this provision could be susceptible to abuse, potentially undermining the integrity of arbitral proceedings. By analyzing twenty-seven cases of criminal prosecution against arbitrators in China, this research evaluates whether the critics’ concerns have materialized in practice. The findings suggest that this provision has not been used in Mainland China to improperly influence arbitral decision‑making.

Permanent magnet synchronous motors (PMSMs) are the preferred choice for robot joint drives. Non-singular fast terminal sliding mode control (NFTSMC) can significantly enhance the robustness and control performance of PMSMs. Nevertheless, it requires the manual tuning of up to ten control parameters, and traditional tuning methods struggle to identify the optimal settings. Therefore, this paper proposes an NFTSMC optimization scheme for PMSM based on an improved gray wolf optimization (IGWO) algorithm. To ensure the GWO finds the optimal solution quickly in this application scenario, two enhancement strategies have been selected. In addition, a comprehensive evaluation indicator is proposed, which combines performance indicators such as response time and overshoot to guide the algorithm in achieving the desired control performance. Finally, an algorithm deployment scheme is proposed to achieve online performance optimization. The proposed approach has been experimentally validated using a fast-prototyping framework. The experimental results demonstrate that the proposed solution can quickly identify control parameters that meet the requirements under the guidance of the proposed evaluation indicator. Comparative experiments also confirm the superiority of the IGWO algorithm in this application.

The purpose of the seminar was to bring together scholars from within linguistics and disciplines such as psychology to explore what short-form social media is, how we might practically and ethically collect and analyse short-form social media data, and what analytic possibilities are on offer for a linguist interested in examining this type of data. The seminar, held at the University of Nottingham on 11th September 2024, was well-attended, with around twenty people joining in-person or online. It ran for a single day and was split into a morning of plenaries and lightning talks about personal research interests, and an afternoon of interactive sessions which sought synergies between those research interests.

Slotted blade technology is a passive flow control strategy that can effectively suppress the boundary layer separation within compressors. To reduce the iteration time of the traditional Design-Experiment-Design method, this study innovatively proposes a fast and universal three-dimensional design method for the slotted blade technology, enabling slot modeling completion within 1 s. Furthermore, combined with machine learning (ML), the mapping relationships between eight design parameters and two key aerodynamic performances – compressor design point efficiency ($\eta$DE) and stator total pressure recovery coefficient at the near-stall point ($\sigma ^{*}_{NS}$) – were pioneeringly established. In this study, the prediction performances of six models were compared: one-dimensional convolutional neural network (1D-CNN), random forest (RF), support vector regression (SVR), Gaussian process regression (GPR), multi-layer perceptron (MLP) and long short-term memory network (LSTM). The results indicate that 1D-CNN achieves the highest prediction accuracy: for the $\eta$DE, the mean absolute error (MAE) and coefficient of determination (R2) are 0.041 and 0.987, respectively; for the $\sigma ^{*}_{NS}$, the MAE and R² are 0.479 × 10−3 and 0.955, respectively. Notably, the computational time of the 1D-CNN model is 99.11% less than that of the computational fluid dynamics (CFD). The Shapley Additive exPlanations (SHAP) method was employed to reveal the effects of design parameters on the compressor aerodynamic performance. Notably, the slot outlet axial position (Zout) exerts the most significant influence on the $\eta$DE, while the slot outlet radial position close to the casing (R1_out) has the strongest impact on the $\sigma ^{*}_{NS}$. This study provides theoretical support and valuable references for the intelligent design of slotted blade technology.

The reduction of anthropogenic methane emissions is a priority due to its potent global warming potential. Radiocarbon (14C) can distinguish between methane from natural biogenic and fossil fuel sources, however, the analysis of methane 14C by conventional accelerator mass spectrometry (AMS) techniques is demanding. At SUERC, a prototype positive ion mass spectrometer (PIMS) is set up to directly analyze 14C in methane with minimal sample preparation. Methane gas was mixed with a stoichiometric amount of oxygen in an open split and admitted directly into the source. A series of modern, blank and unknown methane samples were clearly distinguishable by their 14C/13C raw ratios. The collision cell gas flowrate was then increased to lower the limit of detection. We obtained a corrected 14C/13C raw ratio of less than 2 × 10–13 for blank fossil methane which corresponds to a radiocarbon age greater than 50 kyr. Modern biogenic methane had a measured 14C/13C raw ratio approaching 1 × 10–10 which is consistent with the nominal value of contemporary atmospheric methane. These first results indicate that PIMS has the potential to be a valuable new analytical technique for screening the 14C content of biogas and in climate research studies.

The Nerja Cave is a key archaeological site in the Southern Iberian Peninsula. It was inhabited by humans from the Upper Palaeolithic until recent Prehistory (30 and 3.7 ka cal BP). Various excavation campaigns performed in its external chambers (Vestíbulo, Mina and Torca) have recovered evidence of its use as habitat and burial site. Multiple studies on these matters have been published, but, until now, no Bayesian chronological modeling that utilized radiocarbon dates of the three chambers has been performed. To do so, all the available radiocarbon dates and stratigraphic and archaeological data have been compiled. These comprehend ample and diverse information about which, firstly, individual phase models based on the stratigraphic sequence of each one of the chambers have been created. After critically evaluating the results for each of the chambers, a general phase model for the prehistoric occupation of the external chambers has been created considering the cultural adscription of the samples. This has enabled the identification of 11 phases which correspond to the different technocomplexes of the Gravettian, Solutrean, Magdalenian, Epipalaeolithic, Mesolithic, Neolithic and Chalcolithic. Still pending are the refinement and improvement of the model for the Neolithic horizon among other phases of the sequence. The individual and the general models have evidenced important differences between the different archaeological phases in radiocarbon information as well as in the occupation of the three chambers.

This article offers a detailed analysis of a Kachchhi-Gujarati manuscript chart of the southern Red Sea and Gulf of Aden dating probably from the eighteenth or early nineteenth centuries and held at the Royal Geographical Society–Institute of British Geographers in London (mr Asia S.4.). The origins and possible dating of the manuscript are examined. Astronomical data inscribed on the chart, establishing latitude and providing sailing directions, are identified, interpreted, and projected. Its Devanagari toponyms are transcribed and identified with real-world locations. Coastal profiles and unnamed features representing significant navigational landmarks are individuated. Islamic buildings depicted on the chart are identified as specific regional mosque-shrines. The presence of Ottoman and other regional polities are inferred. The place of the chart within an early modern tradition of western-Indian navigational manuscripts and a wider Indian Ocean tradition is explored. Our analysis establishes the chart as a detailed and highly practical navigational work—countering earlier scholarly denigrations of its accuracy. In contrast, we show it to be one of the most detailed surviving indigenous navigational charts produced in an Indian Ocean tradition.

A database of ca. 970 radiocarbon dates on bones, teeth, and tusks of the woolly mammoth (Mammuthus primigenius Blum.) from Siberia was created in order to understand the spatiotemporal distribution of this species over the last 50,000 14C years (BP). Mammoths populated all parts of Siberia until ca. 12,000 BP. After that, a few refugia exited south of ca. 60°N at ca. 10,600–12,000 BP, and in the northern part of mainland Siberia mammoths survived until ca. 9700 BP. At ca. 9500–3700 BP, they existed only in today’s insular regions such as the New Siberian Islands and Wrangel Island in the High Arctic. The relationship between the dynamics of mammoth populations and climatic fluctuations is complicated. In the warmer intervals (interstadials), the number of mammoths in Siberia was generally slightly larger than in the colder times (stadials); however, the difference is often not significant. The connection between the dynamics of mammoth populations and climatic fluctuations in Siberia is therefore complicated and non-linear.

Despite substantial digital investment and stakeholder initiatives, billions in the Global South remain excluded from digital participation. This systematic literature review synthesizes 122 empirical studies published between 2003 and 2024 in Asia, Africa, Latin America, and Oceania to analyze key stakeholders, their challenges, and the strategies employed to foster sustainable digital inclusion. Drawing on stakeholder theory and digital ecosystems theory, the study identifies ecosystem fragmentation as a central bottleneck. We advance stakeholder theory by introducing the concept of Ecosystem Coordination Stakeholders (ECS), a role-based stakeholder group whose salience derives from coordination capability alongside power, legitimacy, and urgency. The findings highlight the need for policy frameworks that develop and strengthen institutional capacity for coordination, extend ecosystems theory by recognizing coordination as an architectural developmental need, and highlight the importance of design strategies responsive to specific fragmentation patterns in diverse regional contexts. Our study also reveals that work remains concentrated in Asia and Africa, with continued Global North–Global South inequities in authorship and journal visibility. This study offers management and policy insights on digital poverty that may also apply to other complex challenges requiring effective and sustained multi-stakeholder collaboration.

This article investigates how China’s national vision of ecological development integrates digital technology through the narrative of “digital ecological civilization.” Employing the framework of sociotechnical imaginaries, it explores how this narrative emerges nationally and is localized in Guizhou, a burgeoning data centre hub. Nationally, “Digital China” and “ecological civilization” converge into “digital ecological civilization,” portraying digital technology as a transformative force for human–nature harmony, distinct from Maoist ideals of dominating nature. In Guizhou, local discourse highlights the province’s “natural” advantages – climate, resources and karst landscape – framing its digital growth as natural and inevitable. Yet, this narrative obscures extensive state interventions, mythicizing technology’s role while sidelining historical complexities and socialist-era legacies. It legitimizes state-led infrastructural investments and projects a unified future vision. The study illuminates how a “techno-eco unity” sociotechnical imaginary shapes China’s developmental path, revealing the intricate interplay of technology, ecology and modernity in crafting an alternative modernization narrative.

Sea cucumber fisheries have continued to expand during the past decade at a fast rate, despite the predictable drop during the COVID-19 period. The exploitations are now qualified as ‘serial’ and ‘contagious’. The most recent trends are shown through the analysis of Food and Agriculture Organization’s capture data, collected from different countries and territories. The mean captures per year, in fresh weight, are over 90.103 tonnes. The mean trade data for years 2019–2021 are given by category of commodities, which complicates the trade analysis. The imports, in quantity and value, show the usual importance of China and Hong Kong, and now of Saudi Arabia. The exports show the importance of the frozen products from Canada. The statistics from Hong Kong in quantities and values (for imports and re-exports) are analysed for the past decade. Globally, catches have increased in comparison to previous studies, with new countries and territories developing export fisheries, new species targeted from new regions, and new products traded. The continued growth and expansion of the global sea cucumber trade is alarming as the sustainability of many species-specific fisheries remains of great concern. Stronger conservation measures, and their implementation, at national, regional, and international levels, are required to effectively protect biodiversity, promote sustainable resource use, and address the escalating impacts of the increasing exploitation efforts.

By centering the experiences of minoritized community members, this study explores how Good Samaritan laws (GSLs) impact health behaviors related to opioid overdose response. Most states have GSLs that address overdose response. However, their scope can perpetuate structural racism by extending inequitable protection through rigid requirements and exclusions. In this paper, we look at Indiana’s GSL, Aaron’s Law, and consider how its limitations impact Black Indianapolis residents. We analyzed 50 semi-structured one-on-one interviews with Black residents of four urban Indianapolis zip code areas. We engaged the Health Belief Model using directed qualitative content analysis to consider participants’ evaluation of perceived benefits and barriers as they relate to calling 911 following an opioid overdose. We explore participants’ feelings about calling 911 and interacting with law enforcement, and their understanding of Aaron’s Law and its practical application in their neighborhoods. We demonstrate structural racism’s presence in the impressions and applications of policies and highlight how addressing them can improve health outcomes in minoritized communities. Finally, we make recommendations for GSLs nationwide that address the impact of structural racism on overdose fatalities and strengthen their protections, making laypeople more likely to call 911 after an overdose.