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Influence of process parameters and common printing problems on tensile behaviour of DED-Arc
No full textWire-arc directed energy deposition (DED-Arc), also known as wire arc additive manufacturing (WAAM), brings about new opportunities for construction decarbonisation and automation. Overall, the mechanical behaviour of DED-Arc steel is largely comparable to conventionally produced structural steel; however, the performance under tensile loading has been shown to be more variable and susceptible to printing defects. Therefore, an experimental study has been conducted to offer deeper insights into the tensile behaviour of DED-Arc steel elements, with a particular focus on the influence of the process parameters and the consequences of common printing problems. Two groups of DED-Arc steel members with I-section profiles were examined. The first group was designed with different wall thicknesses ranging from 3.5 to 8 mm, achieved by varying key printing parameters and toolpaths, as well as with passive or active cooling. The second group featured the same process parameters but with common printing problems intentionally introduced, including layer shifts, unstable shield gas,
wire feed issues, inclusions, lack of preheating and inconsistent stick out. The test specimens were laser scanned to examine their dimensional properties and surface texture, and then loaded to fracture under axial tension. The influence of wall thickness, toolpath and cooling method on the strength and ductility was highlighted. The common printing problems were shown to slightly deteriorate the strength but significantly reduce the ductility, with unstable shield gas and wire feed issues being the most detrimental. These findings mark a crucial step towards the safe use of DED-Arc for load-bearing applications in construction
Reuse of consumable pipette tips for large-scale trace analysis of contaminants of emerging concern in wastewater
No full textScientific laboratories generate substantial plastic waste, particularly from single-use pipette tips, especially in high-throughput analysis. This study explores the feasibility of reusing pipette tips through green solvent washing within a large-scale environmental monitoring program analysing >100 contaminants of emerging concern (CECs) in water, including complex matrices like wastewater. Eleven cleaning solvents were screened for their ability to reduce chemical carryover, with four selected for further evaluation based on analytical performance and environmental impact using AGREEprep scores (i.e., acetonitrile (MeCN), acetone, ethanol:water (EtOH:H2O, 50:50 v/v) and 1 % nitric acid (NA) aq)). Solvent effectiveness varied with analyte hydrophobicity and tip material. A four-wash protocol (W4) was required to achieve >98 % reduction in carryover. Tests using wastewater and up to 40 reuse cycles (i.e., W160) confirmed additional challenges due to matrix complexity but showed consistent solvent performance trends. Tip integrity was assessed through scanning electron microscopy (SEM) and gravimetric analysis; some solvent-tip combinations (e.g., 1 % NA (aq) with capillary piston tips) showed some degradation. Life cycle assessment (LCA) indicated that although MeCN provided high cleaning efficacy, its high global warming potential (GWP) limited its sustainability in repeated use. EtOH:H2O (50:50 v/v) offered the best overall balance of cleaning performance, low GWP, and minimal tip damage. A compound-specific removal profile and a practical selection tool were developed to guide solvent choice and reuse strategies. This is the first comprehensive study demonstrating solvent-based pipette tip reuse as a viable, environmentally sustainable approach for trace-level chemical analysis in complex environmental monitoring workflows
Effects of M. tuberculosis and HIV-1 infection on in vitro blood-brain barrier function
No full textBackground
Tuberculous meningitis is the most severe form of tuberculosis and HIV-1 co-infection worsens the already poor prognosis. However, how Mycobacterium tuberculosis crosses the blood-brain barrier and how HIV-1 influences tuberculous meningitis pathogenesis remains unclear.
Methods
Using human pericytes, astrocytes, endothelial cells, and microglia alone and combined in an in vitro blood-brain barrier model, we investigated the effect of Mycobacterium tuberculosis +/- HIV-1 co-infection on central nervous system cell entry and function. Cells and the blood-brain barrier model were infected with Mycobacterium tuberculosis and/or HIV-1 and we evaluated the effects of both infection on (i) cells susceptibility to Mycobacterium tuberculosis and its growth in cells by flow cytometry; (ii) modulation of blood-brain barrier permeability and Mycobacterium tuberculosis passage through it; (iii) viral and bacterial cytopathogenicity using the xCELLigence system; (iv) cell metabolic activity and ROS release using colorimetric assays; (v) extracellular glutamate concentration by fluorometric assay; (vi) the inflammatory response by Luminex; and (vii) endoplasmic reticulum stress by quantitative PCR.
Results
We demonstrated that Mycobacterium tuberculosis infects and multiplies in all cell types with HIV-1 increasing entry to astrocytes and pericytes, and growth in HIV-1 positive pericytes and endothelial cells. Mycobacterium tuberculosis also induces an increase of the blood-brain barrier permeability resulting in translocation of bacilli across it. Cytopathic effects include (i) increased markers of cellular stress (mitochondrial metabolic activity, unfolded protein response); (ii) ROS release; (iii) the induction of neurotoxic astrocytes; (iv) and the secretion of the excitotoxic neurotransmitter glutamate. Lastly, we observed distinct cell-type specific production of inflammatory and effector mediators.
Conclusion
These results indicate that Mycobacterium tuberculosis can translocate the blood-brain barrier directly to initiate meningitis
The importance of non-ideality of protons and water in the open circuit potential modelling of redox flow battery aqueous electrolytes
No full textThe non-ideality of electrolytes is commonly neglected in redox flow battery (RFB) modelling work. The neglect of activity coefficients introduces a discrepancy of up to 100 mV between the experimental open circuit potential (OCP) and model predicted reversible Nernstian potential, which propagates into inaccurate state of charge estimation and misinterpretation of thermodynamic efficiency. Due to the complex chemistry and the lack of thermodynamic data, activity coefficients of individual species in highly non-ideal electrolytes are often difficult to determine. In this work, proton and water activity values were calculated using geochemical numerical codes implementing the Pitzer theory, a semi-empirical thermodynamic model that accounts for the non-ideal behavior of ions in electrolyte solutions. The completed Nernst equation with corrected activity values has been elaborated for OCP comparison. An in-operando approach was proposed to measure the proton and water activities of strongly acidic electrolytes. The cell OCP of Hydrogen-Vanadium RFB (H2-V RFB) and Hydrogen-Manganese RFB (H2-Mn RFB) was measured and calculated to assess the electrochemical significance of proton and water non-ideality to the RFB model. With the measured activity data, the error between the experimental and calculated OCP values was reduced from 88-100 mV to 17–50 mV
Sedimentology of plastics: state of the art and future directions
No full textPlastic waste is now a ubiquitous sedimentary material, from the polar ice caps to the deep ocean. Determining the physical and chemical properties, transport pathways and accumulation sites of plastic particles is essential to characterize and mitigate the harmful effects of waste plastic on ecosystems and human health. This requires experimental, modelling and observational approaches across disciplines, including sedimentology, hydrology, chemistry, biology, materials science and many others. Plastic pollution is a deeply complex challenge, and this issue compiles how we may view solutions and understandings through a sedimentological lens. We cover a range of environments, from oceans to rivers and urban stormwater ponds, as well as global questions that consider plastic degradation amid climate change. In this preface, we outline key topics of the papers in this issue and the challenges and opportunities associated with each topic. The special issue illustrates the inherent value and strength of sedimentology as a tool to meaningfully advance our understanding of the transport, accumulation and degradation of plastic waste in the environment.
This article is part of the Theo Murphy meeting issue ‘Sedimentology of plastics: state of the art and future directions’
Correction: Cosma et al. Leishmaniasis in humans and animals: a one health approach for surveillance, prevention and control in a changing world. Trop. Med. Infect. Dis. 2024, 9, 258
No full textError in Figure
In the original publication [1], there was a mistake in Figure 1 as published. The description of Figure 1 is correct, but two arrows between phases 4 and 5 and between phases 5 and 6 are reversed. In the correct paper, the proper Figure 1 is uploaded.
The corrected Figure 1 appears below. The authors state that the scientific conclusions are unaffected. This correction was approved by the Academic Editor. The original publication has also been updated
How HIV infection management in pregnancy has advanced: retrospective singlecentre study
No full textSequential calibration of soil parameters using a two-step surrogate for high-dimensional geotechnical outputs
No full textThe observational method enables engineers to update uncertain soil parameters as new monitoring data become available. This process heavily relies on the model’s ability to deliver prompt and reliable results, enabling inverse analysis in geotechnical applications. Surrogate models are commonly used to approximate computationally costly simulations and accelerate calibration. However, the high-dimensional spatial nature of geotechnical outputs complicates the use of traditional surrogate models. To address this challenge for model calibration, this study adopts a type of reduced-order modeling (ROM) approach for high-dimensional outputs. Specifically, a two-step approach is used: (1) dimensionality reduction to extract features from geotechnical outputs and map the original output space into a lower-dimensional space, and (2) constructing a surrogate model directly within the reduced space. This approach improves surrogate model accuracy while maintaining the computational efficiency required. Combined with sequential Bayesian inference, the method is then evaluated for a laterally loaded pile problem. Results demonstrate the method’s effectiveness in handling high-dimensional geotechnical outputs during model calibration
On diffusion posterior sampling via sequential Monte Carlo for zero-shot scaffolding of protein motifs
No full textWith the advent of diffusion models, new proteins can be generated at an unprecedented rate. The motif scaffolding problem requires steering this generative process to yield proteins with a desirable functional substructure called a motif. While models have been trained to take the motif as conditional input, recent techniques in diffusion posterior sampling can be leveraged as zero-shot alternatives whose approximations can be corrected with sequential Monte Carlo (SMC) algorithms. In this work, we introduce a new set of guidance potentials for describing scaffolding tasks and solve them by adapting SMC-aided diffusion posterior samplers with an unconditional model, Genie, as a prior. In single motif problems, we find that (i) the proposed potentials perform comparably, if not better, than the conventional masking approach, (ii) samplers based on reconstruction guidance outperform their replacement method counterparts, and (iii) measurement tilted proposals and twisted targets improve performance substantially. Furthermore, as a demonstration, we provide solutions to two multi-motif problems by pairing reconstruction guidance with an SE(3)-invariant potential. We also produce designable internally symmetric monomers with a guidance potential for point symmetry constraints. Our code is available at: https://github.com/matsagad/mres-project
Design of surfactant molecules under performance constraints
No full textThe industrial applications of surfactant solutions are both numerous and extremely diverse, demonstrating the importance of these systems in everyday life and driving the need for a systematic approach to designing sustainable surfactant molecules adapted to the specific requirements of each application. Given the very large space of possible molecules, the identification of candidate surfactants that achieve a balance between the optimal physicochemical properties of the product and minimal environmental and health impacts is extremely challenging. In this work, a formulation and solution framework based on Computer-Aided Molecular Design is proposed for surfactant design. A novel multistage methodology is developed based on the initial generation of promising candidates for the two constituents of a surfactant, the hydrophilic head and the hydrophobic tail, followed by the multiobjective optimization of surfactant molecules. This decomposition results in an effective solution strategy. In addition to constraints that ensure the generation of feasible molecules, specific structural constraints can be incorporated in the formulation, accelerating the discovery and optimization process. Data-driven predictive models for the most relevant surfactant properties, such as critical micelle concentration, Krafft point, surface tension, toxicity, and biodegradability, are developed and implemented in the optimization formulation. Two case studies are tackled, successfully generating novel surfactant molecules. The proposed framework could be extended to more complex structures, such as two-headed or Gemini surfactants