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All-solid-state batteries with a Li anode and ceramic electrolyte have the potential to deliver a step change in performance compared with today’s Li-ion batteries 1 , 2 . However, Li dendrites (filaments) form on charging at practical rates and penetrate the ceramic electrolyte, leading to short circuit and cell failure 3 , 4 . Previous models of dendrite penetration have generally focused on a single process for dendrite initiation and propagation, with Li driving the crack at its tip 5 – 9 . Here we show that initiation and propagation are separate processes. Initiation arises from Li deposition into subsurface pores, by means of microcracks that connect the pores to the surface. Once filled, further charging builds pressure in the pores owing to the slow extrusion of Li (viscoplastic flow) back to the surface, leading to cracking. By contrast, dendrite propagation occurs by wedge opening, with Li driving the dry crack from the rear, not the tip. Whereas initiation is determined by the local (microscopic) fracture strength at the grain boundaries, the pore size, pore population density and current density, propagation depends on the (macroscopic) fracture toughness of the ceramic, the length of the Li dendrite (filament) that partially occupies the dry crack, current density, stack pressure and the charge capacity accessed during each cycle. Lower stack pressures suppress propagation, markedly extending the number of cycles before short circuit in cells in which dendrites have initiated. Analysis of dendrite initiation, owing to filling of pores with lithium by means of microcracks, and propagation, caused by wedge opening, shows that there are two separate processes during dendrite failure of lithium metal solid-state batteries.

Corrugated packaging is well known as a highly recyclable option, and more of it is recovered for recycling than any other packaging material. Digital preprint’s use of aqueous inks and coatings ensures that the paper recycling process produces quality fiber in high yields, while also meeting worldwide regulatory requirements that address a broad range of health and environmental considerations. Aqueous inks offer food-safe printing, do not contain hazardous air pollutants and emit low levels of volatile organic compounds (VOCs).

Appropriate inspection protocols and mitigation strategies are a critical component of effective biosecurity measures, enabling implementation of sound management decisions. Statistical models to analyze biosecurity surveillance data are integral to this decision-making process. Our research focuses on analyzing border interception biosecurity data collected from a Class A Nature Reserve, Barrow Island, in Western Australia and the associated covariates describing both spatial and temporal interception patterns. A clustering analysis approach was adopted using a generalization of the popular k-means algorithm appropriate for mixed-type data. The analysis approach compared the efficiency of clustering using only the numerical data, then subsequently including covariates to the clustering. Based on numerical data only, three clusters gave an acceptable fit and provided information about the underlying data characteristics. Incorporation of covariates into the model suggested four distinct clusters dominated by physical location and type of detection. Clustering increases interpretability of complex models and is useful in data mining to highlight patterns to describe underlying processes in biosecurity and other research areas. Availability of more relevant data would greatly improve the model. Based on outcomes from our research we recommend broader use of cluster models in biosecurity data, with testing of these models on more datasets to validate the model choice and identify important explanatory variables.

Introduction pathway studies generally describe the diverse routes by which non-indigenous species (NIS) can be introduced but rarely consider multiple introduction pathways occurring simultaneously. In this study, multiple pathways of NIS introduction were investigated during an industrial development on a remote island off the Australian coast. Fifteen introduction pathways were categorized in association with importing locality and the type of cargo they transported. The number and types of detection events for each introduction pathway were recorded during biosecurity inspections, cargo clearances, and surveillance conducted between 2009 and 2015. In total, more than 600,000 biosecurity inspections were completed, with 5,328 border detection events recorded constituting less than 1% of the biosecurity inspections. The border inspection events were classified as animals, plant material, soil, and organic matter, with 60% identified as dead or non-viable and 40% as alive. Of those detections, 2153 were classified as NIS, consisting of 659 identified species. Live NIS detected at the border constituted only 2% of the detections. Cargo vessel and inward-bound passenger numbers peaked during the major construction period and were associated with an increase in the number of live NIS detections. All introduction pathways have complexities, unique structural aspects, and niche areas that supported NIS in surviving the effects of treatment and evading detection during the mandatory compliance inspection. This study highlights that biosecurity incursions can be minimized if a systems approach is adopted to complement traditional and other biosecurity surveillance measures.

In an era focused on value-based healthcare, the quality of healthcare and resource allocation should be underpinned by empirical evidence. Pragmatic clinical trials (pRCTs) are essential in this endeavor, providing randomized controlled trial (RCT) insights that encapsulate real-world effects of interventions. The rising popularity of pRCTs can be attributed to their ability to mirror real-world practices, accommodate larger sample sizes, and provide cost advantages over traditional RCTs. By harmonizing efficacy with effectiveness, pRCTs assist decision-makers in prioritizing interventions that have a substantial public health impact and align with the tenets of value-based health care. An international network for pRCT provides several advantages, including larger and diverse patient populations, access to a broader range of healthcare settings, sharing knowledge and expertise, and overcoming ethical and regulatory barriers. The hypothesis and study design of pRCT answers the decision-maker’s questions. pRCT compares clinically relevant alternative interventions, recruits participants from diverse practice settings, and collects data on various health outcomes. They are scarce because the medical products industry typically does not fund pRCT. Prioritizing these studies by expanding the infrastructure to conduct clinical research within the healthcare delivery system and increasing public and private funding for these studies will be necessary to facilitate pRCTs. These changes require more clinical and health policy decision-makers in clinical research priority setting, infrastructure development, and funding. This paper presents a comprehensive overview of pRCTs, emphasizing their importance in evidence-based medicine and the advantages of an international collaborative network for their execution. It details the development of PRIME-9, an international initiative across nine countries to advance pRCTs, and explores various statistical approaches for these trials. The paper underscores the need to overcome current challenges, such as funding limitations and infrastructural constraints, to leverage the full potential of pRCTs in optimizing healthcare quality and resource utilization.

Background Psoriasis is an immune-mediated disease characterised by chronically elevated pro-inflammatory cytokine levels, leading to aberrant keratinocyte proliferation and differentiation. Although certain clinical phenotypes, such as plaque psoriasis, are well defined, it is currently unclear whether there are molecular subtypes that might impact on prognosis or treatment outcomes. Results We present a pipeline for patient stratification through a comprehensive analysis of gene expression in paired lesional and non-lesional psoriatic tissue samples, compared with controls, to establish differences in RNA expression patterns across all tissue types. Ensembles of decision tree predictors were employed to cluster psoriatic samples on the basis of gene expression patterns and reveal gene expression signatures that best discriminate molecular disease subtypes. This multi-stage procedure was applied to several published psoriasis studies and a comparison of gene expression patterns across datasets was performed. Conclusion Overall, classification of psoriasis gene expression patterns revealed distinct molecular sub-groups within the clinical phenotype of plaque psoriasis. Enrichment for TGFb and ErbB signaling pathways, noted in one of the two psoriasis subgroups, suggested that this group may be more amenable to therapies targeting these pathways. Our study highlights the potential biological relevance of using ensemble decision tree predictors to determine molecular disease subtypes, in what may initially appear to be a homogenous clinical group. The R code used in this paper is available upon request.

The design of post-quantum cryptography (PQC) hardware is a complex and hierarchical process with many challenges. A primary bottleneck is the conversion of PQC reference codes from C to high-level synthesis (HLS) specifications, which requires extensive manual refactoring. Another bottleneck is the scalability of synthesis for complex PQC primitives, including number theoretic transform (NTT) accelerators and wide memory interfaces. While large language models (LLMs) have shown remarkable results for coding in general-purpose languages like Python, coding for hardware design is more challenging; feedback-driven and agentic integration are key principles of successful state-of-the-art approaches. Here, we propose LLM4PQC, an LLM-based framework that refactors high-level PQC specifications and reference C codes into HLS-ready and synthesizable C code. Our framework generates and verifies the resulting RTL code. For correctness, we leverage a hierarchy of checks, covering fast C compilation and simulation as well as RTL simulation. Case studies on NIST PQC reference designs demonstrate a reduction in manual effort and accelerated design-space exploration compared to traditional flows. Overall, LLM4PQC provides a powerful and efficient pathway for synthesizing complex hardware accelerators.

Microfluidics has emerged as a powerful enabling technology in plant science, offering unprecedented control over microscale environments for the cultivation, manipulation, and analysis of plant cells, tissues, and organs. This review provides a comprehensive overview of the development and application of microfluidic systems in plant physiology and development studies. We categorize the platforms based on their structural designs and biological targets—from single-cell trapping devices and droplet-based screening systems to organ-on-a-chip and root–microbe interaction modules. Key applications include live-cell imaging, real-time monitoring of stress responses, microenvironment simulation, and high-throughput phenotyping. Particular attention is given to microfluidic investigations of plant mechanobiology, chemotropism, and cell-to-cell communication, as well as their integration with biosensors, electrophysiological tools, and environmental control systems. We also examine current limitations related to material compatibility, device scalability, and biological complexity, and highlight emerging solutions such as modular design, interdisciplinary integration, and soil-on-a-chip systems. By addressing both fundamental research needs and practical agricultural challenges, microfluidic technologies offer a transformative path toward precision plant science and sustainable crop innovation.