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2D Vanadium Carbide/Oxide Heterostructure‐Based Artificial Sensory Neuron for Multi‐Color Near‐Infrared Object Recognition
No full textNear‐infrared (NIR) photon detection and object recognition are crucial technologies for all‐weather target identification in autonomous navigation, nighttime surveillance, and tactical reconnaissance. However, conventional NIR detection systems, which rely on photodetectors and von Neumann computing algorithms, are plagued by energy inefficiency and signal transmission bottlenecks. Herein, a vanadium carbide/oxide (V2C/V2O5‐x) heterostructure is designed and synthesized by a topochemical conversion method. The V2C/V2O5‐x heterostructure‐based memristor exhibits stable threshold‐type resistance switching (RS) behavior with low coefficient of variation in transition voltages (1.62% and 1.7%) over thousands of cycles, and maintains stable performance even after storage for 90 days. Benefiting from the NIR responsivity of V2C and the volatile RS enabled by vacancy‐enriched V2O5‐x, devices exhibit a linear variation in threshold voltage in response to NIR light power density and wavelength. Based on the multi‐color NIR modulable RS characteristics and the YOLOv7 algorithm model, an artificial neural network (ANN) architecture achieves average recognition accuracies of 89.6% for cars and 85.9% for persons on the FLIR dataset. This work reveals a heterostructure with versatile functionalities for neuromorphic devices and establishes a memristor‐based ANN platform for multi‐color object detection and recognition in complex real‐world scenarios
Does explaining the meaning of likelihood ratios improve lay understanding?
Get PDFMost previous research exploring the understanding of likelihood ratios by laypersons has not provided participants with an explanation of the meaning of likelihood ratios. Although triers of fact in common-law jurisdictions usually receive oral testimony, most previous research has presented experiments in written format. The research reported in this paper presented participants with videoed testimony and tested the effect of the expert witness providing participants with an explanation of the meaning of likelihood ratios. Analysis included comparing each participant’s effective likelihood ratio (the posterior odds elicited from the participant divided by the prior odd elicited from the participant) with the presented likelihood ratio. The percentage of participants whose effective likelihood ratios equalled the presented likelihood ratios was higher for participants who were provided with the explanation of the meaning of likelihood ratios than for participants who were not provided with the explanation. The difference was, however, small. The percentage of participants whose posterior odds were consistent with them having committed the prosecutor’s fallacy was not lower for participants who were provided with the explanation of the meaning of likelihood ratios than for participants who were not provided with the explanation. The full set of results do not constitute convincing evidence that presenting the explanation of the meaning of likelihood ratios resulted in better understanding of likelihood ratios. We discuss whether there are factors other than participants not understanding the meaning of likelihood ratios that could have contributed to the results
Healthcare Consultations for People with Chronic Conditions and Disabilities: Managing Cyber-Victimisation Impact and Training Needs
Get PDFBackground: Cyber-victimisation is a growing public health challenge, particularly for people with long-term conditions and disabilities. These individuals face complex challenges in managing health, compounded by experiences of discrimination and insufficient access to appropriate support. Aim: This study examines healthcare professionals’ encounters with patients who have long-term conditions or disabilities and reported cyber-victimisation. It focuses on the scope of these experiences in healthcare, impact on patients, healthcare professionals’ awareness, and perceived training needs. Method: A mixed-methods survey was conducted with UK-based healthcare professionals, recruited through the Modality Super GP partnership, social media, and contacting relevant organisations. Results: The participant sample comprised 118 healthcare professionals, with a mean of 20.72 years of professional experience (SD = 13.72). Among them, 33.90% encountered patients affected by cyber-victimisation, and of these, 82.50% indicated that such experiences had a detrimental impact on their patients’ health. Reported impacts were on mental health, social relationships, lifestyle, physical complications, missing routine appointments, changes to medications, and lab tests. Qualitative themes included mental health consequences, worsening of chronic conditions, increased vulnerability due to certain conditions, trust and stigma, and varied professional awareness. Among those asked about training (n = 77), 58.44% supported research-informed programmes, with preferred formats being interactive media, workshops, and printed materials. Conclusion: Findings confirm that cyber-victimisation of this group is prevalent in healthcare, yet support and awareness remain limited. Training is needed to equip professionals to assist affected patients. Future research should explore interdisciplinary strategies to strengthen healthcare responses and embed cyber-victimisation awareness into public health policy
Poppers, the Politics of Exemption and the Characteristics of Poppers Users in the annual English Festival Study, 2014–23
Get PDFThis paper explores the relationship between socio-demographic characteristics, self-reported alkyl nitrite (‘poppers’) use and sexual behaviours against a backdrop of UK policy change and ambiguity surrounding legal status. In 2024, the Advisory Council on the Misuse of Drugs recommended a unique, government-initiated, legal exemption from the Psychoactive Substances Act 2016 for poppers, because of its use by gay and bisexual men to reduce the risk of injury during anal sexual intercourse. Data from the annual convenience sample English Festival Study 2014–23 (n = 11,566) were used for Bayesian regression analyses of self-reported poppers use in three-time frames: lifetime, past year and past month use. Gay men were significantly more likely to report poppers use and particularly those reporting past-year participation in anal sex. Providing a critical analysis of recent trends in UK drug policy, the authors highlight how differential discrimination occurs within drug control where targeted exemption meets the politics of protected characteristics in UK law. This paper argues that poppers, therefore, provide a unique example in UK drug policy of how an apparent liberalization of legislative control could bolster the overarching drug prohibition regime while maintaining the appearance of rationality and fairness
Modified charge inversion and extraction switching strategies for a strongly coupled piezoelectric vibration energy harvester
Get PDFThe objective of this study is to enhance the output power of a high-electromechanical-coupling piezoelectric vibration energy harvester, incorporating a synchronous inversion and charge extraction (SICE) circuit. The SICE circuit employs charge inversion and charge extraction switches to boost the voltage of the piezoelectric transducer and to extract electrical energy. In cases of weak electromechanical coupling, the SICE circuit is preferred over the synchronized electric charge extraction circuit. However, when a strongly coupled transducer is used within the SICE circuit, harvesting efficiency can decrease. In this study, two novel methods for controlling the SICE circuit were introduced: short-duration switching and phase-shifted switching. An analytical model was developed to examine the relationship between the phase shift required for switching and the output power. The voltage generator model of the piezoelectric transducer was used to illustrate the temporal variation in the piezoelectric charge. The analysis revealed that the piezoelectric charge in the voltage generator model remains constant during the intervals between switching operations. This characteristic is beneficial for the theoretical computation of solutions to the equations of motion. The numerical simulations and experimental results confirmed the effectiveness of the proposed methods, which achieved a 48% improvement in the output power of the SICE circuit, particularly for strongly coupled energy harvesters
From Margins to Extremes: Economic Factors, Social Integration and the Radicalisation of European Youth
Get PDFThis paper explores the relationship between economic variables, social integration and susceptibility to extremism in Norway, Denmark, the Netherlands and the United Kingdom. By analysing 415 interviews conducted with young people, activists and practitioners between 2021 and 2023, we have discerned patterns in the influence of economic conditions on radicalisation. We found that nationalist ideologies are associated with economic concerns, particularly those related to globalisation and migration, and that perceived relative deprivation, rather than absolute conditions, mediate the influence of these factors. Comparable economic grievances foster conditions for both right-wing and Islamist radicalisation, indicating shared mechanisms. Nevertheless, national contexts–including welfare models and integration policies–affect the manifestations of these economic factors in actual radicalisation processes. This study elucidates the intricate relationship between economic conditions and extremist ideologies among European youth
Location and allocation of primary and backup shelters in transboundary disasters
Get PDFThere are records of people being unable to find shelter after a disaster or reaching facilities operating over capacity because of facility failure. Natural hazards do not respect geographical or political boundaries and often surpass the capacity of single jurisdictions operating with limited resources. Coordination between jurisdictions can become a solution, but it has been neglected in the literature. This article is the first to investigate the use of backup facilities as a strategy facilitated by transboundary coordination. It proposes a novel solution incorporating collaboration between multiple jurisdictions to establish a shelter location-allocation approach to protect people affected by disasters considering facility failure. The article presents a stochastic bi-objective formulation for transboundary coordination, incorporating the responsibility, priorities, and resources of each jurisdiction whilst considering the possibility of facility failure during disaster management. The objective of the model is to provide shelter to beneficiaries of all the jurisdictions by pooling resources whilst reducing the travel distance and minimizing the maximum cost for each jurisdiction. The contribution of the article is to introduce the formulation, assess the impact of transboundary coordination, and analyze the value of backup facilities in the service provided to people affected by disasters. The model has been applied to a set of numerical examples and a real case of volcanic eruptions in Mexico. The results show the influence of cross-jurisdictional coordination on the support provided to disaster victims, the value of backup facilities, and the capacity of the model design to provide relevant alternatives in practice
A meta-analysis of predictive accuracies and errors of biomass estimation models in Sub-Saharan Africa
Get PDFAccurate biomass estimation is essential for forest monitoring, energy planning and carbon accounting in Sub-Saharan Africa (SSA), where destructive sampling is often impractical. Biomass estimation models (BEMs) offer scalable alternatives, but their predictive accuracy varies across forest types, species and data sources. This study conducted a systematic meta-analysis of 39 BEMs from 22 peer-reviewed studies conducted in SSA, evaluating their model performance using standardised metrics of coefficient of determination (R2) and root mean square error (RMSE). Data were sourced from Global Allometric Tree database, Scopus and Web of Science, following PRISMA guidelines. Both destructive and non-destructive models based on field and remote sensing (RS) data were included. Meta-analytic computations incorporated Fisher's Z-transformation and random-effects modelling to account for heterogeneity. Results indicate high predictive accuracy (mean R2 = 0.82), but substantial variation in error (mean RMSE = 108.9 Mg/ha, SD = 511.6), reflecting methodological and ecological diversity (I2 = 99.87 %). Locally calibrated allometric models achieved the highest accuracy, while RS-based models using optical data alone exhibited higher error rates. Hybrid models integrating LiDAR, radar and optical data demonstrated superior performance when combined with machine learning techniques. Key predictors such as diameter at breast height, tree height and wood density consistently improved model accuracy. Emerging evidence underscores the significance of trees outside forests in national carbon inventories. This study recommends adopting hybrid BEMs tailored to local ecological conditions and incorporating multi-sensor RS data. The findings inform biomass monitoring strategies for forest conservation, REDD+ MRV systems and sustainable energy planning in SSA
Uncertainty-Aware Self-Attention Model for Time Series Prediction with Missing Values
Get PDFMissing values in time series data present a significant challenge, often degrading the performance of downstream tasks such as classification and forecasting. Traditional approaches address this issue by first imputing the missing values and then independently solving the predictive tasks. Recent methods have leveraged self-attention models to enhance imputation quality and accelerate inference. These models, however, predict values based on all input observations—including the missing values—thereby potentially compromising the fidelity of the imputed data. In this paper, we propose the Uncertainty-Aware Self-Attention (UASA) model to overcome these limitations. Our approach introduces two novel techniques: (i) A self-attention mechanism with a partially observed diagonal that effectively captures complex non-local dependencies in time series data—a characteristic also observed in fractional-order systems. This approach draws inspiration from fractional calculus, where non-integer-order derivatives better characterize complex dynamical systems with long-memory effects, providing a more comprehensive mathematical framework for handling temporal data. And (ii) uncertainty quantification in data imputation to better inform downstream tasks. The UASA model comprises an upstream component for data imputation and a downstream component for time series prediction, trained jointly in an end-to-end fashion to optimize both imputation accuracy and task-specific objectives simultaneously. For classification tasks, the UASA model demonstrates remarkable performance even under high missing data rates, achieving a ROC-AUC of (Formula presented.), a PR-AUC of (Formula presented.), and an F1-SCORE of (Formula presented.). For forecasting tasks on the AUST-Gait dataset, the UASA model achieves a Mean Squared Error (MSE) of 0.72 under (Formula presented.) missing data conditions (i.e., complete data input). Under the end-to-end training strategy evaluated across all missing data rates, the model achieves an average MSE of 0.74, showcasing its adaptability and robustness across diverse missing data scenarios
From students to refugees::students’(im) mobility in the wake of the Russian invasion of Ukraine
Get PDFResearch on the migratory experiences of people affected by the Russo-Ukraine conflict has mainly focused on Ukrainians, overlooking non-Ukrainians who were also displaced. This article examines how the war shaped the mobility experiences of displaced African students who took refuge in Germany. Using the critical theory of migration control and nativism, the study employs reflexive thematic analysis of qualitative data from 23 African students in Cologne (August 2022). The findings suggest that the students experienced intersecting forms of discrimination, including systemic racism and the double standards of European Union border practices, which hindered their mobility aspirations. The study highlights how micro-level biases rooted in nativism reinforce systemic barriers to mobility and can undermine macro-level measures aimed at alleviating them. Grounded in empirical insights, it synthesises ideas from nativism, ‘migration controls as global apartheid,’ and intersectionality to explore both interpersonal and structural forms of exclusion. This article also contributes to the discourse on international student mobility during violent conflicts
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