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The SABYDOMA safety by process control framework for the production of functional, safe and sustainable nanomaterials
Get PDFThe production of nanomaterials (NMs) has gained significant attention due to their unique properties and versatile applications in fields such as medicine, energy, and electronics. However, ensuring the large-scale synthesis of safe and sustainable NMs while maintaining their functionality remains a critical challenge. This study introduces the Safety by Process Control (SbPC) framework, a novel methodology integrating dynamic first-principles modeling, Model Predictive Control (MPC), and real-time safety monitoring. The framework employs a physics-based population balance model with a Method Of Moments (MOM) approximation to predict the evolution of key NM properties. A toxicity inferential sensor, built on experimental data, is integrated to facilitate real-time hazard assessment. The efficiency of the proposed framework is demonstrated using a continuous silver nanoparticle (Ag NP) production system as a case study. The proposed approach ensures the production of high-quality, safe, and sustainable NMs, aligning with Safe and Sustainable by Design (SSbD) principles and addressing gaps in current NM manufacturing processes. The framework’s adaptability to other NM types highlights its potential as a transformative tool for sustainable nanotechnology
Feature-level fusion network for hyperspectral object tracking via mixed multi-head self-attention learning
Get PDFHyperspectral object tracking has emerged as a promising task in visual object tracking. The rich spectral information within hyperspectral images benefits the accurate tracking in challenging scenarios. The performances of existing hyperspectral object tracking networks are constrained by neglecting the interactive information among bands within hyperspectral images. Moreover, designing an accurate deep learning-based algorithm for hyperspectral object tracking poses challenges because of the substantial amount of training data required. In order to address these challenges, a new mixed multi-head attention-based feature fusion tracking (MMFT) algorithm for hyperspectral videos is proposed. Firstly, MMFT introduces a feature-level fusion module, mixed multi-head attention feature fusion (MMFF), which fuses false-color features and augments the fused feature with one mixed multi-head attention (MMA) block with interactive information, which increases the representational ability of the features for tracking. Specifically, MMA learns the interactive information across the bands in the false-color images and incorporates the learned interactive information into the fused feature, which is obtained by combining the features of the false-color images. Secondly, a new training procedure is introduced, in which the modules designed for hyperspectral object tracking are first pre-trained on a sufficient amount of modified RGB data to enhance generalization, and then fine-tuned on a limited amount of HS data for task adaption. Extensive experiments verify the effectiveness of MMFT, demonstrating its SOTA performance
Cost utility of specialist physiotherapy for functional motor disorder (Physio4FMD)
Get PDFBackground and Objectives
Functional motor disorder (FMD), a motor-dominant variant of functional neurologic disorder, is a disabling condition associated with high health and social care resource use and poor employment outcomes. Specialist physiotherapy presents a possible treatment option, but there is limited evidence for clinical effectiveness and cost-effectiveness. Physio4FMD is a multicenter randomized controlled trial of specialist physiotherapy for FMD compared with treatment as usual (TAU). The aim of the analysis was to conduct a randomized trial based on economic evaluation of specialist physiotherapy compared with TAU.
Methods
Eleven centers in England and Scotland randomized participants 1:1 to specialist physiotherapy or TAU (referral to community neurologic physiotherapy). Participants completed the EuroQoL EQ-5D-5L, Client Service Receipt Inventory, and Work Productivity and Activity Impairment Questionnaire at baseline, 6 months, and 12 months. The mean incremental cost per quality-adjusted life year (QALY) for specialist physiotherapy compared with TAU over 12 months was calculated from a health and social care and wider societal perspective. The probability of cost-effectiveness and 95% CIs were calculated using bootstrapping.
Results
The analysis included 247 participants (n = 141 for specialist physiotherapy, n = 106 for TAU). The mean cost per participant for specialist physiotherapy was £646 (SD 72) compared with £272 (SD 374) for TAU. Including the costs of treatment, the adjusted mean health and social care cost per participant at 12 months for specialist physiotherapy was £3,814 (95% CI £3,194–£4,433) compared with £3,670 (95% CI £2,931–£4,410) for TAU, with a mean incremental cost of £143 (95% CI £–825 to £1,112). There was no significant difference in QALYs over the 12-month duration of the trial (0.030, 95% CI –0.007 to 0.067). The mean incremental cost per QALY was £4,133 with an 86% probability of being cost-effective at a £20,000 threshold. When broader societal costs such as loss of productivity were taken into consideration, specialist physiotherapy was dominant (incremental cost: £−5,169, 95% CI £–15,394 to £5,056).
Discussion
FMD was associated with high health and social care costs. There is a high probability that specialist physiotherapy is cost-effective compared with TAU particularly when wider societal costs are taken into account
Validation of a machine-learning clinical decision aid for the differential diagnosis of transient loss of consciousness
Get PDFBackground and Objectives
The aim of this study was to develop and validate a machine-learning classifier based on patient and witness questionnaires to support differential diagnosis of transient loss of consciousness (TLOC) at first presentation.
Methods
We prospectively recruited patients newly presenting with TLOC to an emergency department, an acute medical unit, and a first seizure or syncope clinic. We invited participants to complete an online questionnaire, either at home or at time of initial assessment. Two expert raters determined the cause of participants' TLOC after 6-month follow-up. We used independent development and validation samples to train a random forest classifier to predict diagnosis from participants' questionnaire responses and validate classifier performance. We compared classifier performance against penalized linear regression and referrer diagnosis.
Results
We included 178 participants in the final analysis, of whom 46 identified a witness able to complete an additional witness questionnaire. Given low witness recruitment, we developed a classifier based on patient answers only. A classifier trained on 9 items correctly identified 63 of 78 diagnoses (80.8%) (95% CI 70.0–88.5), an increase over the accuracy of initial assessing clinicians who were only able to diagnose 70.5% correctly. Within this, 96% (87.0%–99.4%) of those expertly rated as having syncope were correctly classified by the classifier (classifier sensitivity); 40% (20%–63.6%) of those expertly rated after follow-up as having either epilepsy or functional/dissociative seizures were similarly classified as being nonsyncope (classifier specificity).
Discussion
A machine-learning classifier for differential diagnosis of TLOC has comparable performance in differentiating between 3 main causes of primary TLOC as the current standard of care but is insufficiently accurate in its current form to warrant incorporation into routine care. A system including information from witnesses might improve classification performance
Critical Imagination for Transformative Agency: Pedagogies for Science Teacher Education
Get PDFThis paper theorizes transformative agency and its potential to promote justice-oriented science teacher education. We argue that science education often acts as a disimagination machine, constraining possibilities for envisioning and enacting transformative change. To contest this reality, we draw on critical perspectives in science education, specifically Paulo Freire's and Simone Weil's philosophies to theorize transformative agency as encompassing three dimensions: a) reading the world to identify injustices, b) imagining untested feasibilities, and c) writing the world anew. In doing so, we act upon the belief that inherited practices of science education that negate collective joy must be challenged. We expand current conceptualizations of transformative agency by proposing critical imagination as one of its core components, enabling the envisioning of possibilities for change. We propose three pedagogical approaches for cultivating critical imagination: a) facilitating practices that move beyond the self to recognize multiple human and nonhuman others; b) adopting a planet-centred orientation to education transcending human-centered approaches; and c) troubling dominant spatial and temporal scales of thinking. We argue for the need to develop liberatory pedagogies that bring critical scientific questions to justice issues while nurturing critical imagination. This entails conceiving agency as more than responsive classroom practices but rather as achieving justice-oriented commitments, agendas and visions that center the world and its necessities
Prescriptive analytics for freeway traffic state estimation by multi-source data fusion
Get PDFIn the context of freeway traffic state estimation, this study introduces prescriptive analytics—also known as “predict-then-optimize”—for integrating data from Electronic Toll Collection (ETC) systems and traffic sensors. Traditional single-method data fusion techniques are constrained by inherent limitations. For instance, optimization-based methods are generally predicated on prior assumptions that may induce systematic biases, whereas machine learning approaches are frequently criticized for their lack of interpretability and their inability to elucidate underlying traffic mechanisms. To address these limitations, a novel “retrieval and matching” algorithm is proposed that integrates machine learning with optimization. First, the concept of the “state gene” is introduced to encapsulate traffic structural knowledge representing frequently occurring traffic patterns. In the retrieval phase, a heterogeneous graph conventional network is employed to predict potential state genes for a given scenario. In the matching phase, the predicted state genes are utilized to minimize the discrepancy with the current traffic state. This integration not only enhances the interpretability of the estimation process but also endows the optimization component with reverse inference capability through the incorporation of machine learning. Validation using real-world data from the G92 Freeway in Zhejiang, China, demonstrates high accuracy, yielding Mean Absolute Percentage Errors (MAPE) of 1.12 − 1.65 % during peak periods and 1.28 − 1.67 % during off-peak periods
Toward an ecological systems approach to doctoral student resilience: qualitative evidence from the Covid-19 pandemic
Get PDFPurpose
This study aims to contribute to the growing body of literature documenting responses to short- and long-term impacts of the COVID-19 pandemic on doctoral students. This study examines support practices at different levels of the education system in which doctoral students are embedded, drawing on Bronfenbrenner’s ecological systems model to better understand how these contribute to doctoral students’ degree of resilience under stress.
Design/methodology/approach
Using online group interviews, this study explores the experiences of 21 doctoral students from seven universities across Europe, Africa and Asia.
Findings
The analysis revealed that the quality of supervisor support at the microsystem level was the most crucial factor determining how severely the doctoral students experienced negative impacts from the pandemic. However, broader institutional and systemic challenges – including inadequate online infrastructure and lack of incentives for additional mentoring – limited the support options available to students. In settings with fewer institutional resources, students exhibited adaptive resilience by actively seeking alternative sources of support at the mesosystem level, particularly through peer networks and external mentors.
Originality/value
This study extends the literature on resilience in higher education settings. This study applies Bronfenbrenner’s ecological systems model to understand doctoral students’ experiences during the COVID-19 pandemic. It illustrates how the model can help understand the sources of individual resilience that are facilitated at different levels of the support systems. This study uses a sample of doctoral students with diverse characteristics in personal situations. Based on the findings, the study provides policy recommendations and identifies venues for further research needed in the field to understand the longer-term impact of the pandemic across different regional settings
Regusted with life: the therapeutic value of humour in J.-K. Huysmans’s À rebours [Against Nature]
Get PDFAlthough J.-K. Huysmans’s Decadent novel À rebours [Against Nature] is not known primarily as a comic novel, it has amused readers for different reasons since its publication in 1884. Henri Bergson identifies the body as a source of comedy, which is why tragic heroes do not drink, eat, or warm themselves up. I develop Bergson’s premise here to read Against Nature as a tragicomedy where the protagonist’s attempts to live an artificial existence are subverted by the functions of the body: eating, drinking, excreting, and copulating. But the humour is not limited to these bodily functions: we can also discern it in the structure of the novel, the narrator’s deadpan tone, and the protagonist’s hybrid status as both dandy and clown. Building on an insight by André Breton, I argue that the comedy in Against Nature has a therapeutic value in the etymological sense of therapia as healing. I link this to Freud’s view that the mechanism of the joke can be aligned with the functions of the grammatical person. As the first person of the joke, Huysmans through his narrator provides this therapy for his protagonist, the second person or subject of the joke. As for us, the readers or third persons of the joke, the therapy resides in the solitary or collective reception of this cautionary tale: if we find ourselves raging against other people or the demands of our bodies, we need to remember the importance of laughter, healthy living, and sociability. Des Esseintes, the protagonist of Against Nature, is disgusted with life; I conclude that he needs to become regusted in order to regain his taste for life and to stay alive. Reading Against Nature as both a comic novel and a therapeutic process enables us to see literary Decadence in a new light and to think more broadly about the therapeutic effects of comedy
Wild and domesticated animal abundance is associated with greater late-Holocene alpine plant diversity
Get PDFIn the face of human land use and climate dynamics, it is essential to know the key drivers of plant species diversity in montane regions. However, the relative roles of climate and ungulates in alpine ecosystem change is an open question. Neither observational data nor traditional palaeoecological data have the power to resolve this issue over decadal to centennial timescales, but sedimentary ancient DNA (sedaDNA) does. Here we record 603 plant taxa, as well as 5 wild, and 6 domesticated mammals from 14 lake sediment records over the last 14,000 years in the European Alps. Sheep were the first domesticated animals detected (at 5.8 ka), with cattle appearing at the early Bronze Age (4.2 ka) and goats arriving later (3.5 ka). While sheep had an impact similar to wild ungulates, cattle have been associated with increased plant diversity over the last 2 ka by promoting the diversity of forbs and graminoids. Modelling of the sedaDNA data revealed a significantly larger effect of cattle and wild ungulates than temperature on plant diversity. Our findings highlight the significant alteration of alpine vegetation and the entire ecosystem in the Alps by wild and domesticated herbivores. This study has immediate implications for the maintenance and management of high plant species diversity in the face of ongoing anthropogenic changes in the land use of montane regions
Recent Advances of Guided Mode Resonant Sensors Applied to Cancer Biomarker Detection
Get PDFGuided mode resonance (GMR)-based sensors have emerged as a promising technology for the early screening of cancer, offering advantages such as sensitivity, specificity, low cost, non-invasiveness, and portability. This review article provides a comprehensive overview of the latest advancements in GMR technology and its applications in biosensing, with a specific focus on cancer. The current state of cancer diagnosis and the critical need for point-of-care (POC) devices to address these challenges are discussed in detail. Furthermore, the review systematically explores various strategies employed in GMR-based cancer detection including design principles and the integration of advanced technologies. Additionally, it aims to provide researchers valuable insights for developing GMR sensors capable of detecting cancer biomarkers outside the laboratory environment
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