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Seawater pretreatment for thermal plant by pressure stimuli-responsive forward osmosis membrane
Get PDFScale formation and deposition on the heat exchanger of thermal desalination have serious consequences on the plant performance and energy consumption. This study presented a patented method for diluting the brine from the multi-stage flash (MSF) plant with seawater using nanofiltration (NF) membranes of specific characteristics in the forward osmosis (FO) process. Three flat-sheet NF membranes of < 200 µm structure parameter were tested as pressure stimuli-responsive (PSR) membranes in the FO process. The NF membranes are designed to reject divalent ions, such as sulfate, magnesium, and calcium, which are the main reason for scale formation and deposition in the MSF plant. In this study, the performance of cellulose triacetate (CTA) and thin film-composite (TFC) FO membrane was compared with the PSR NF membranes for seawater pretreatment using an MSF brine draw solution at 40 °C. The water flux in the PSR NF membrane was insignificant at 0 bar pressure but increased several times when the feed pressure increased to 2 and 4 bar pressure. For the FO tests at 4 bar pressure, the average water flux in the PSR membranes was up to 2.6 times more than that in the CTA and TFC FO membranes, all without increasing the energy requirements of the FO process. In the tight NF membrane, the MSF brine dilution occurred by the permeation flow, but in the loose NF membrane, it was by permeation flow and ions' reverse diffusion from the draw solution to the feed solution. Notably, the PSR NF membranes achieved a substantial cost reduction that is ten times cheaper than the FO membrane, which has excellent potential to reduce the cost of the FO process
Decentring the human in online spaces: moving beyond analysis to Merleau-Ponty's wild Being
Get PDFPurpose Increasingly our lives are being mediated through online tools and spaces that shape our experiences of living and learning in ways that are only recently being examined. Developing suitable methodologies to examine these online spaces has proven challenging, while there is validity to the use of network analytics and statistical interpretations of networks and more recently, digital ethnographies and “netnographies”, these approaches are limited. Design/methodology/approach This article offers an alternative by looking closely at a particular online space, which is first analysed via social network theory, connectivism, and social learning spaces. We then work with Merleau–Ponty's notion of “wild Being” to decentre the human and move beyond analysis – bringing to light how online spaces are lived as a collective unfolding in which our embodied selves, other selves, things and non-things are involved in a complex and fluid interplay. Findings We see this account as demonstrating the value of analytical approaches whilst also highlighting the importance of remaining mindful of their limitations. Doing so can create inroads and open possibilities for more complex understandings of online spaces and associated technologies in generative and innovative ways. Originality/value This article fulfils an identified need to explore the challenges and opportunities of decentring the human in qualitative research methodologies in educational research
An approximate hybrid approach for computing low-frequency outdoor sound propagation
Get PDFAccurate and fast outdoor sound models are essential for assessing noise from infrastructure like wind turbines, highways, and industrial facilities. This paper presents an approximate hybrid method for solving long-range acoustic problems by coupling a normal-mode approach with the numerical solution of the linearized Euler equations (LEEs). The method computes a discrete mode spectrum using a weak Galerkin method from an aeroacoustic eigenequation that accounts for meteorological profiles, atmospheric absorption, gravity, and impedance ground conditions. A pressure field modal decomposition scheme then maps the mode spectrum to the LEE solution, which incorporates detailed geometry, meteorology, and diverse acoustic sources. The acoustic far field is then efficiently computed through an algebraic operation. We validate the method with long-range propagation problems from the infrasound community and a wind turbine model, showing excellent agreement with direct numerical methods while significantly reducing computational resources. This approach offers a practical tool for noise prediction in applications like wind park and highway noise mapping
Advanced Non-linear Analysis of Composite Cold-Formed Steel and Reinforced Concrete Floor Systems
No full textThis study presents an advanced non-linear finite element analysis (FEA) of composite flooring systems comprising cold-formed steel (CFS) joists and reinforced concrete slabs, aiming to address the limited representation of such hybrid systems in current design standards. The research develops a validated 3D ANSYS model incorporating multi-linear material behaviour, contact interactions, and large deformation effects under static and cyclic loading. Key phenomena—including bolt slip, plastic hinge formation, and strain redistribution—were captured, with validation against benchmark experiments yielding a mean absolute error (MAE) of 23.75 kN and root mean squared error (RMSE) of 33.72 kN. Fatigue performance was assessed using both stress-life (S–N) and strain-life (ε–N) methods, with results showing a critically low life of 0.85 cycles at the upper slab in stress-based analysis and 75.45 cycles at support zones in strain-based analysis, validating the latter's applicability for brittle concrete fatigue modelling. Crack sensitivity was investigated using a J-Integral fracture approach applied to a 25 mm notch at mid-span, revealing high stress intensity prior to arrest by reinforcement. A targeted numerical investigation of different reinforcement layouts indicated that reducing rebar spacing by 10 mm produced an average 8% decrease in peak J-Integral, underscoring the importance of layout configuration in fracture control. The stud
Epigenetic Regulation in Horticultural Crops
Get PDFEpigenetics is defined as “the study of changes in gene function that are mitotically and/or meiotically heritable and do not involve a change in DNA sequence”. Epigenetic modifications include post-translational modifications of histones and DNA methylation. Changes in DNA methylation have been observed in response to environmental factors, with some epimutations being heritable across generations. Such epimutations may lead to alterations in plant traits and could be involved in natural selection or domestication. Furthermore, epigenetic transcriptional regulation serves as a crucial strategy for responding to various environmental conditions, including abiotic and biotic stress. In horticultural crops, this regulation is implicated in diverse biological processes, including agronomic traits such as hybrid vigor/heterosis, flowering time, bud dormancy, sex determination, fruit ripening, and anthocyanin accumulation. Recent advances in methods for analyzing epigenetic states, along with advances in sequencing technology, have enabled high-resolution and genome-wide studies in various horticultural crops. This review highlights the critical role of epigenetic transcriptional regulation in biological processes in horticultural crops and discusses the potential for artificially inducing epigenetic variation to enhance phenotypic diversity in horticultural crop breeding
Dignity Is Distinct From Respect: How Treating Others With Dignity Entails Accounting for Their Self-Conscious Emotions.
No full textDignity is prominently endorsed in health care, organizations, and law. However, humanities research casts doubt over the utility of this concept, disputing that "dignity" captures any unique ethical value distinguishable from "respect". Here, we test a recent proposal that dignity entails special regard for humiliation. We created a set of vignettes describing a "perpetrator" making offensive remarks or gestures to a "victim", and asked lay participants to rate how well each offense corresponds to a dignity violation as opposed to a respect violation. We manipulated the victims' resulting emotions within-subject, across "humiliation", "anger", and "baseline" conditions, while controlling for other factors (e.g., victim's gender, vulnerability). We found substantial evidence (BF = 4.11) for our preregistered hypothesis that humiliation increased dignity-relatedness ratings as compared with the baseline condition, and very strong evidence when compared with the anger condition (BF = 84.75). These findings provide empirical backing to dignitarian ethics with applications in health care, organizations, and law
B14 Integrative Analysis and Experimental Validation Unveil TNFSF10 as a Key PANoptosis Inducer Driving Preeclampsia Pathogenesis
No full textNanotechnology-Driven Treatment Strategies for Breast Cancer: Recent Advances and Innovations
No full textClimate change amplifies mangrove hypercapnic hypoxia and threatens fish habitats
Get PDFMangroves provide habitats for many marine species and support fisheries in developing tropical countries. However, mangrove habitats are increasingly threatened by climate change. Here, we show how global warming and rising atmospheric CO2 will reduce dissolved oxygen and increase CO2 in mangrove waters, making them less suitable as fish refugia. Global observations from 23 mangroves revealed that most sites already experience mild (on average, 34–43% of the time) or severe (6–32%) hypercapnic hypoxia, i.e., low oxygen and high CO2 conditions. Hypercapnic hypoxia mostly occurs during low tide and in tropical mangroves. Climate projections indicate that oxygen will decrease by 5–35% and CO2 will increase by 8–60% by 2100. Therefore, hypercapnic hypoxia events will occur more frequently, last longer, and become more severe. These shifts will reduce mangrove biodiversity and decrease habitat quality for commercially valuable fish, likely reducing fishing yields in tropical developing countries
Generative Dynamic Graph Representation Learning for Conspiracy Spoofing Detection
No full textSpoofing detection in financial trading is crucial, especially for identifying complex behaviors such as conspiracy spoofing. Traditional machine-learning approaches primarily focus on isolated node features, often overlooking the broader context of interconnected nodes. Graph-based techniques, particularly Graph Neural Networks (GNNs), have advanced the field by leveraging relational information effectively. However, in real-world spoofing detection datasets, trading behaviors exhibit dynamic, irregular patterns. Existing spoofing detection methods, though effective in some scenarios, struggle to capture the complexity of dynamic and diverse, evolving inter-node relationships. To address these challenges, we propose a novel framework called the Generative Dynamic Graph Model (GDGM), which models dynamic trading behaviors and the relationships among nodes to learn representations for conspiracy spoofing detection. Specifically, our approach incorporates the generative dynamic latent space to capture the temporal patterns and evolving market conditions. Raw trading data is first converted into time-stamped sequences. Then we model trading behaviors using the neural ordinary differential equations and gated recurrent units, to generate the representation incorporating temporal dynamics of spoofing patterns. Furthermore, pseudo-label generation and heterogeneous aggregation techniques are employed to gather relevant information and enhance the detection performance for conspiratorial spoofing behaviors. Experiments conducted on spoofing detection datasets demonstrate that our approach outperforms state-of-the-art models in detection accuracy. Additionally, our spoofing detection system has been successfully deployed in one of the largest global trading markets, further validating the practical applicability and performance of the proposed method
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