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Social dimensions of shark–human interactions in a large remote marine protected area
No full textThe impact of shifting marine conservation policy, including marine protected area (MPA) designation, in shaping interactions between humans and imperilled species, such as sharks, remains understudied, despite its importance in determining the success of these interventions. We investigated perceptions of shark–human interactions (SHI) among the community in a remote, large-scale MPA (Ascension Island) where two recent shark attacks and perceived general increases in interactions (mostly with Galapagos and silky sharks), including depredation in recreational fisheries, have occurred. From 2023 to 2024, informal semistructured interviews (n = 34) were conducted with island residents and analysed using two theory-driven thematic frameworks to understand the level and drivers of conflict. We showed considerable social impact of SHI, including reduced human well-being and substantial lifestyle changes, with both depredation and human attacks driving dispute-level conflict. Strong social and familial connections on island resulted in narratives around attacks persisting and trauma resulting from attacks drove heightened perceived risk. Underlying conflict was further exacerbated by the perceived recurrent and unpredictable nature of negative SHI compounded with the interactions being perceived as abnormal with limited information on socio-ecological drivers. Some felt excessive chumming by historic recreational fisheries, mostly engaged in by non-residents, had also involuntarily exposed them to heightened risk by increasing SHI. There was also no consensus of what shark species were behind the increased interactions. Management resolutions were perceived as minimal but were not widely viewed as negative. However, divergent views on the use of lethal control and the need for conservation measures, such as banning shark exploitation, were evident. A key theme emerged around the need for wider community participation in the research and management processes. Policy implications. Our results highlight the critical importance of demystifying marine species, particularly in terms of understanding socio-ecological drivers of human–wildlife interactions, to combat escalation into human–wildlife conflict. This is particularly important to maintain support for large-scale MPAs and species-specific conservation. Read the free Plain Language Summary for this article on the Journal blog
Integrated irrigation of water and fertilizer with superior self-correcting fuzzy PID control system
No full textTo address the fixed-parameter limitations of traditional PID control (e.g., excessive overshoot, prolonged settling time, poor adaptability to nonlinearities) and the insufficient real-time adjustment capability of conventional fuzzy PID control, which relies on empirically predefined rule bases, this study proposes a self-correcting fuzzy PID control strategy for agricultural water-fertilizer integrated systems. Traditional PID control, due to its static parameters, suffers from reduced stability and error accumulation under dynamic variations (e.g., irrigation flow fluctuations, environmental disturbances) or nonlinear interactions (e.g., coupling effects of fertilizer concentration and pH). While conventional fuzzy PID control incorporates fuzzy reasoning, its offline-designed rule bases and membership functions lack online adaptive parameter correction, leading to degraded precision in complex operating conditions. To tackle challenges posed by uncertain variables (e.g., time-varying soil permeability) and nonlinear parameters resistant to precise mathematical modeling, this research integrates fuzzy logic with an online self-correcting mechanism, constructs a mathematical model for the integrated control system, designs real-time correction rules, and validates the model through simulations using Matlab/Simulink and a semi-physical PC platform. The results demonstrate that the self-correcting fuzzy PID control significantly optimizes key performance metrics: overshoot (reduced by 21.3%), settling time (shortened by 34.7%), and steady-rate error (decreased by 18.9%), outperforming both traditional PID and fuzzy PID methods in concentration and pH regulation. Its parameter self-adaptation capability effectively balances dynamic response and steady-state performance, resolving issues such as overshoot oscillation and lagging regulation in nonlinear dynamics. In practical applications, the system achieved an average plant height growth rate of 15.86%-21.73% and a 30.41% yield improvement compared to the control group, validating the enhanced synergistic control of water and fertilizer enabled by the variable universe fuzzy PID approach. This study provides a robust control solution with theoretical innovation and practical value for managing complex nonlinear systems in precision agriculture.NSFC (Award: 92475109
A student-focused curriculum for Asian Studies courses – a study of student needs and motivations
No full textAn Overview of Recent AI Applications in Combined Heat and Power Systems
No full textCombined heat and power (CHP) systems are among the important components for enhancing energy efficiency and sustainability by simultaneously generating electricity and useful thermal energy, reducing waste and costs. Consequently, the effective control of these systems is considered important. To that end, this paper provides a comprehensive review of the intelligent methodologies applied to CHP systems, emphasizing their prevalence in the USA and Europe through statistical insights. It outlines the mathematical foundations of CHP systems, analyzing the advancements in intelligent control methods for optimal planning, economic dispatch, and cost minimization. Artificial Intelligence (AI) models, such as Long Short-Term Memory (LSTM), Bidirectional LSTM (BiLSTM), and Random Forest, are described and applied to a simulated CHP system. The Key Performance Indicators (KPIs) derived from these models demonstrate their efficacy for optimizing CHP performance. This paper also highlights the impact of AI-driven models for enhancing CHP system efficiency, while identifying the challenges in AI-CHP integration and envisioning CHP systems as important components of future sustainable energy systems
Deuteration Effects on the Physical and Optoelectronic Properties of Donor–Acceptor Conjugated Polymers
No full textThe significant differences in scattering cross sections between deuterium and protium are unique to neutron scattering techniques and have been a long-standing area of interest within the neutron scattering community. Researchers have explored selective deuteration to manipulate scattering contrast in soft matter systems, leading to the widespread use of deuterium labeling in materials development. As deuteration changes the atomic mass, it alters physical properties such as molecular volume, polarizability, and polarity, which in turn may affect noncovalent interactions and crystal ordering. Despite previous studies, there remains a limited understanding of how deuteration impacts donor-acceptor (DA) conjugated polymers. To address this, we synthesized deuterated DPP polymers and systematically investigated the effects of side-chain deuteration on their thermal stability, crystal packing, morphology, and optoelectronic properties. We found that deuteration increased the melting and crystallization temperatures of DPP polymers, although it did not significantly alter their morphology, molecular packing, or charge mobility. These properties were assessed by using atomic force microscopy (AFM), X-ray scattering, and thin-film transistor device measurements, respectively, for DPP polymers. Our work shows that deuterium labeling could be a powerful method for controlling scattering length density, enabling neutrons to study the structure and dynamics of conjugated polymers without impacting their electronic performance.Basic Energy Sciences (Award: DE-SC0022050)Natural Sciences and Engineering Research Council of Canada (Award: RGPIN-2022-04428)Government of Ontari
Anticoagulant management of cancer-associated thrombosis and thrombocytopenia: a retrospective chart review
No full textBackground: Patients with cancer-associated thrombosis (CAT) are at an increased risk of recurrent thrombosis and bleeding, especially if there is treatment- or disease-related thrombocytopenia. While direct oral anticoagulants (DOACs) are used in the management of CAT, low molecular weight heparin (LMWH) continues to be recommended for CAT with thrombocytopenia. Objectives: This study aimed to identify the rates of recurrent venous thromboembolism (VTE) and bleeding in patients with CAT and thrombocytopenia treated with DOACs compared with LMWH. Methods: A retrospective review of patients with CAT and thrombocytopenia (platelet count <100,000/μL) was conducted. Primary outcomes included rates of recurrent VTE and major bleeding over 90 days. Results: Forty-two patients met the inclusion criteria; 20 (47.6%) had a solid organ malignancy while 22 (52.4%) had a hematologic malignancy. Within the first 7 days of VTE, 3 (7.1%) patients had a platelet count <25,000/μL, 9 (21.4%) had 25,000 to 50,000/μL, and 19 (45.2%) had 50,000 to 100,000/μL. Sixteen patients (38.1%) received a DOAC for initial treatment, while 19 (45.2%) received LMWH. Among patients treated with DOACs, there were no recurrent VTEs, 2 clinically relevant nonmajor bleeding events (12.5%) within the first 2 weeks, and 1 minor bleed (6.3%) in the second month, while those treated with LMWH had 1 recurrent VTE (5.3%) in the second month and 2 clinically relevant nonmajor bleeding events (10.5%) within the first 2 months. Conclusion: Rates of thrombosis and major bleeding were similar among thrombocytopenic patients with CAT treated with DOACs and LMWH, although differences in baseline patient characteristics can be confounders. Further prospective research on the optimal anticoagulant management of CAT with thrombocytopenia is needed
PolyLLM: polypharmacy side effect prediction via LLM-based SMILES encodings
No full textPolypharmacy, the concurrent use of multiple drugs, is a common approach to treating patients with complex diseases or multiple conditions. Although consuming a combination of drugs can be beneficial in some cases, it can lead to unintended drug-drug interactions (DDI) and increase the risk of adverse side effects. Predicting these adverse side effects using state-of-the-art models like Large Language Models (LLMs) can greatly assist clinicians. In this study, we assess the impact of using different LLMs to predict polypharmacy. First, the chemical structure of drugs is vectorized using several LLMs such as ChemBERTa, GPT, etc., and are then combined to obtain a single representation for each drug pair. The drug pair representation is then fed into two separate models including a Multilayer Perceptron (MLP) and a Graph Neural Network (GNN) to predict the side effects. Our experimental evaluations show that integrating the embeddings of Deepchem ChemBERTa with the GNN architecture yields more effective results than other methods. Additionally, we demonstrated that utilizing complex models like LLMs to predict polypharmacy side effects using only chemical structures of drugs can be highly effective, even without incorporating other entities such as proteins or cell lines, which is particularly advantageous in scenarios where these entities are not available.Natural Sciences and Engineering Research Council of Canada (Award: RGPIN-2024-04547
Commentary on: J. Fields and F. Kauffeld’s “The Presumption of Veracity in Testimony and Gossip”
No full textDeinfluencing TikTok During the Cost-of-Living Crisis: Neoliberal Logics of (Over)Consumption Across Popular Media
No full textFollowing the economic recession of 2008, media texts blamed individual consumers and their reckless and wasteful consumption of designer goods and extravagant homes for contributing to the financial crisis. Within the current context of the aftermath of the COVID-19 pandemic, the cost-of-living crisis has led to increases in the cost of everyday necessities. At the same time, social media influencers promote excessive consumption of expensive viral products that are often discarded upon purchase. Responding to these socio-cultural events, deinfluencing became a viral trend on TikTok, where users post videos encouraging viewers to purchase certain products rather than other more expensive options. Positioning deinfluencing as an example of cultural responses to financial crises, this article highlights the parallels between deinfluencing and previous discursive articulations that emerged during the 2008 global financial crisis. Deinfluencing reproduces longstanding cultural formations of consumer citizenship while also reacting to the overconsumption promoted by the digital economy