In this paper, we present the Amsterdam Modeling Suite (AMS), a comprehensive software platform designed to support advanced molecular and materials simulations across a wide range of chemical and physical systems. AMS integrates cutting-edge quantum chemical methods, including Density Functional Theory (DFT) and time-dependent DFT, with molecular mechanics, fluid thermodynamics, machine learning techniques, and more, to enable multi-scale modeling of complex chemical systems. Its design philosophy allows for seamless coupling between components, facilitating simulations that range from small molecules to complex biomolecular and solid-state systems, making it a versatile tool for tackling interdisciplinary challenges, both in industry and in academia. The suite also emphasizes user accessibility, with an intuitive graphical interface, extensive scripting capabilities, and compatibility with high-performance computing environments.

The goal of the NEUROKIT2E project is to create an open-source Deep Learning framework for edge and embedded AI built around an established European value chain. This framework, called AIDGE, supports a wide range of application areas that operate independently and serve a global user community. It provides easy and fast full-stack solutions from Neural Network design and optimization to AI application development all the way down to hardware implementations while enabling code generation for application-specific targets. This platform provides flexibility for academic users in the AI domain to explore and innovate while allowing them the possibility to prototype systems, ensuring their work aligns well with industrial needs. This paper presents the results and achievements of the first part of this three-year project, along with its roadmap and expected outcomes.

Cardiac magnetic resonance imaging (MRI) provides detailed and quantitative evaluation of the heart’s structure, function, and tissue characteristics with high-resolution spatial–temporal imaging. However, its slow imaging speed and motion artifacts are notable limitations. Undersampling reconstruction, especially data-driven algorithms, has emerged as a promising solution to accelerate scans and enhance imaging performance using highly under-sampled data. Nevertheless, the scarcity of publicly available cardiac k-space datasets and evaluation platform hinder the development of data-driven reconstruction algorithms. To address this issue, we organized the Cardiac MRI Reconstruction Challenge (CMRxRecon) in 2023, in collaboration with the 26th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI). CMRxRecon presented an extensive k-space dataset comprising cine and mapping raw data, accompanied by detailed annotations of cardiac anatomical structures. With overwhelming participation, the challenge attracted more than 285 teams and over 600 participants. Among them, 22 teams successfully submitted Docker containers for the testing phase, with 7 teams submitted for both cine and mapping tasks. All teams use deep learning based approaches, indicating that deep learning has predominately become a promising solution for the problem. The first-place winner of both tasks utilizes the E2E-VarNet architecture as backbones. In contrast, U-Net is still the most popular backbone for both multi-coil and single-coil reconstructions. This paper provides a comprehensive overview of the challenge design, presents a summary of the submitted results, reviews the employed methods, and offers an in-depth discussion that aims to inspire future advancements in cardiac MRI reconstruction models. The summary emphasizes the effective strategies observed in Cardiac MRI reconstruction, including backbone architecture, loss function, pre-processing techniques, physical modeling, and model complexity, thereby providing valuable insights for further developments in this field.

Positive Energy Districts (PEDs) are integral to achieving sustainable urban development by enhancing energy self-sufficiency and reducing carbon emissions. This paper explores energy balance calculations in four diverse case study districts within different climatic conditions—Fiat Village in Settimo Torinese (Italy), Großschönau (Austria), Beursplain in Amsterdam (Netherlands), and Lunca Pomostului in Reşiţa (Romania)—as part of the SIMPLY Positive project. Each district faces unique challenges, such as outdated infrastructure or heritage protection, which we address through tailored strategies including building renovations and the integration of renewable energy systems. Additionally, we employ advanced simulation methodologies to assess energy performance. Simulation results highlight the significance of innovative technologies like photovoltaic-thermal (PVT) systems, application of demand-side actions, and flexible grid usage. Furthermore, mobility assessments and resident-driven initiatives demonstrate the critical role of community engagement in reducing carbon footprints. This study underscores the adaptability of PED frameworks across varied urban contexts and provides actionable insights for scaling similar strategies globally, supporting net-zero energy targets.

Plastic waste is a major environmental issue; converting it directly into valuable chemicals by using catalysts is a promising alternative to plastic recycling. Here, we report the selective catalytic cracking of polypropylene (PP), a typical commodity plastic, to high-value light olefins (C2–C5), below pyrolytic temperature (290 °C) and without external hydrogen supply, by using zeolite catalysts. Among the H+-form zeolites with different structures, HMFI showed the highest yields of light hydrocarbons (C2–C5), of which light olefins (C2–C5) were the major products. The HMFI-catalyzed PP conversion was applicable to the upcycling of a model PP waste, resulting in a 61.9% light hydrocarbon yield. The results of catalytic and in situ IR experiments using model HMFI catalysts with a small amount of external Brønsted acid sites suggested that the Brønsted acid sites on the external surface of HMFI are indispensable for the PP conversion and are posited to be the active sites for the cracking of PP into short-chain (oligomeric) hydrocarbon species as intermediate products. Density functional theory analyses were conducted to determine plausible reaction pathways by adopting 2,4-dimethylheptene as the shortest unit of the oligomeric species. The obtained results show that the β-scission of 2,4-dimethylheptene by Brønsted acid sites yields isobutene and propylene (or a propyl alkoxide group) via carbocation intermediates with an activation energy below 118 kJ mol–1. Operando UV–vis and IR experiments under the reaction conditions, combined with ex situ 1H NMR and 13C NMR analyses of the spent catalyst, show that some of the olefins are further converted to light or heavy aromatics (coke deposit), probably via carbenium ion species.

Personalised Environmental Control Systems (PECS) enable occupants to locally adjust environmental parameters without affecting others. Rooted in the fields of thermal and air quality management, this approach is key for enhancing satisfaction and well-being in the built environment by empowering occupants to control their immediate surroundings. Moreover, it offers energy-saving potential by optimizing conditions in targeted areas rather than across the entire environment. Within the framework of the IEA EBC Annex 87, the concept was explored for the first time in the acoustic domain. After defining Acoustic PECS, a systematic review according to PRISMA guidelines was conducted to unpack (1) technologies in the literature aligning with this concept; (2) their impact on occupants; and (3) current limitations. The literature search, conducted on Scopus, Web of Science, APA, and PubMed, included field or laboratory studies assessing systems enabling local acoustic control in settings that are relevant for office environments. Review papers, medical device studies, and reports without insights on occupant impact were excluded. Thirty-eight studies were selected, covering active and passive systems, building-attached, furniture-integrated, and wearable devices. The qualitative analysis highlighted potential positive effects in challenging acoustic environments, including reduced annoyance, improved work performance, masking or cancellation of intrusive noises, and enhancements in short-term memory, among other benefits, despite existing technological and methodological limitations. The evidence collected is constrained by the limited number of identified studies and methodological gaps stemming from the relatively wide focus of the studies where such devices were investigated. The definition of Acoustic PECS provides a foundation for future research, guiding the development of these systems and fostering high-quality and consistent evidence of their impacts.

Correction to: Nature Communicationshttps://doi.org/10.1038/ncomms16025, published online 06 July 2017 The original version of this Article included the authors Kun Zuo and Vincent Mourik who wish to be removed from authorship. Consequently, the author affiliations for these authors have been removed from the ‘Authors and Affiliations’ section. The original version of the ‘Contributions’ statement, which read “H.Z. and Ö.G. fabricated the devices, performed the measurements and analysed the data. S.C.-B. performed the TEM analysis. M.P.N. and M.W. performed the numerical simulations. K.Z., V.M., F.K.d.V., J.v.V., M.W.A.d.M., J.D.S.B., D.J.v.W., M.Q.-P., M.C.C. and S.G. contributed to the experiments. D.C., S.P. and E.P.A.M.B. grew the InSb nanowires. S.K. prepared the lamellae for the TEM analysis. K.W. and T.T. synthesized the h-BN crystals. L.P.K. supervised the project. All authors contributed to the writing of the manuscript”, has been amended to read “H.Z. and Ö.G. fabricated the devices, performed the measurements and analysed the data. S.C.-B. performed the TEM analysis. M.P.N. and M.W. performed the numerical simulations. F.K.d.V., J.v.V., M.W.A.d.M., J.D.S.B., D.J.v.W., M.Q.-P., M.C.C. and S.G. contributed to the experiments. D.C., S.P. and E.P.A.M.B. grew the InSb nanowires. S.K. prepared the lamellae for the TEM analysis. K.W. and T.T. synthesized the h-BN crystals. L.P.K. supervised the project. All authors contributed to the writing of the manuscript”. This has been corrected in both the PDF and HTML versions of the article.

The development of materials toward ppb-level nitric oxide (NO) sensing at room temperature remains in high demand for the monitoring of respiratory inflammatory diseases. In order to find an iron-containing molecule without steric hindrance to combine with graphene for room temperature NO gas sensing, here a supramolecular assembly of ferrocene (Fc) and reduced graphene oxide (rGO) was designed and prepared for NO sensing. The assembly of Fc/rGO was characterized using FT-IR, TEM, and XPS measurements. The Fc/rGO-based sensors exhibited superior NO sensing properties at room temperature including high response (R_a/R_g = 1.73, 1 ppm), high selectivity against other exhaled gases, reliable repeatability and stability (less than 4 % decrease after 40 days). A practical limit of detection (LOD) of 200 ppb was achieved. The theoretical simulation demonstrates that ferrocene is assembled via π-π interaction with rGO in edge-to-face configuration which provides relatively lower energy than face-to-face configuration does for the whole assembly. It was first verified that the enhanced adsorption capacity and the charge transfer between NO and Fc/rGO would result in improvement of the assembly's sensitivity toward NO after ferrocene was assembled with graphene. This work provides a fresh approach of anchoring iron on graphene for gas sensing via supramolecular methods.

Purpose
Prostate-specific membrane antigen (PSMA) expression has been observed in a subset of soft tissue sarcomas, mainly in the neovascular endothelial cells. This feasibility study aimed to evaluate PSMA expression and PSMA PET/CT imaging in metastatic soft tissue sarcoma, providing important insights for potential future exploration of PSMA-targeted radioligand therapy.

Methods
This prospective single-center study included adult patients with metastatic soft tissue sarcoma, with measurable disease (lesion diameter > 1 cm), available biopsy/resection material, ECOG/WHO performance status of 0–2 and either no prior systemic treatment, progressive disease during/after treatment, or stable disease/partial response with the last dose > 8 weeks prior. Immunohistochemical PSMA staining was performed on previously obtained biopsy or resection material. In case of high PSMA expression, a [18F]-JK-PSMA-7 PET/CT scan evaluated tracer uptake, with adequate uptake defined as SUVmax > 8.

Results
Of 25 included patients, 11 (44%) had high PSMA expression: 4/11 leiomyosarcomas, 3/4 dedifferentiated liposarcomas, 2/5 undifferentiated pleomorphic sarcomas, 1/2 myxofibrosarcomas and 1/1 malignant peripheral nerve sheath tumour. Five of 11 patients agreed to a [18F]-JK-PSMA-7 PET/CT, of which 3 had lesions that showed adequate tracer uptake (SUVmax 10.7–16.7). However, uptake across all metastatic lesions was highly heterogeneous (median SUVmax = 3.8; range 0.5–16.7), indicating that these patients are unlikely to benefit sufficiently from PSMA-targeted therapy. The study was therefore terminated prematurely.

Conclusion
PSMA expression and PSMA tracer uptake in metastatic soft tissue sarcoma were highly heterogeneous. A deeper understanding of PSMA biology and improved patient selection criteria are essential for future application of PSMA-targeted radioligand therapy in this disease.

Background and ObjectivesIdentifying genetic causes of dementia in patients visiting memory clinics is important for patient care and family planning. Traditional clinical selection criteria for genetic testing may miss carriers of pathogenic variants in dementia-related genes. This study aimed identify how many carriers we are missing and to optimize criteria for selecting patients for genetic counseling in memory clinics.MethodsIn this clinical cohort study, we retrospectively genetically tested patients during 2.5 years (2010-2012) visiting the Alzheimer Center Amsterdam, a specialized memory clinic. Genetic tests consisted of a 54-gene dementia panel, focusing on Class IV/V variants per American College of Medical Genetics and Genomics guidelines, including APP duplications and the C9ORF72 repeat expansion. We determined the prevalence of pathogenic variants and propose new eligibility criteria for genetic testing in memory clinics. The eligibility criteria were prospectively applied for 1 year (2021-2022), and results were compared with the retrospective cohort.ResultsGenetic tests were retrospectively performed in in 1,022 of 1,138 patients (90%) who consecutively visited the memory clinic. Among these, 1,022 patients analyzed (mean age 62.1 ± 8.9 years; 40.4% were female), 34 pathogenic variant carriers were identified (3.3%), with 24 being symptomatic. Previous clinical criteria would have identified only 15 carriers (44% of all carriers, 65% of symptomatic carriers). The proposed criteria increased identification to 22 carriers (62.5% of all carriers, 91% of symptomatic carriers). In the prospective cohort, 148 (28.7%) of 515 patients were eligible for testing under the new criteria. Of the 90 eligible patients who consented to testing, 13 pathogenic carriers were identified, representing a 73% increase compared with the previous criteria.DiscussionWe found that patients who visit a memory clinic and carry a pathogenic genetic variant are often not eligible for genetic testing. The proposed new criteria improve the identification of patients with a genetic cause for their cognitive complaints. In systems without practical or financial barriers to genetic testing, the new criteria can enhance personalized care. In other countries where the health care systems differs and in other genetic ancestry groups, the performance of the criteria may be different.

This article presents a 4096-element ultrasound probe for high volume-rate (HVR) cardiovascular imaging. The probe consists of two application-specific integrated circuits (ASICs), each of which interfaces with a 2048-element monolithically-integrated capacitive micro-machined ultrasound transducer (CMUT) array. The probe can image a 60° × 60° × 10-cm volume at 2000 volumes/s, the highest volume-rate with in-probe channel-count reduction reported to date. It uses 2 × 2 delay-and-sum micro-beamforming (μBF) and 2× time-division multiplexing (TDM) to achieve an 8× receive (RX) channel-count reduction. Equalization, trained using a pseudorandom bit-sequence generated on the chip, reduces TDM-induced crosstalk by 10 dB, enabling power-efficient scaling of the cable drivers. The ASICs also implement a novel transmit (TX) beamformer (BF) that operates as a programmable digital pipeline, which enables steering of arbitrary pulse-density modulated (PDM) waveforms. The TX BF drives element-level 65 V unipolar pulsers, which in turn drive the CMUT array. Both the TX BF and RX μBF are programmed with shift-registers (SRs) that can either be programmed in a row-column fashion for fast upload times, or daisy-chain fashion for a higher flexibility. The layout of the ASICs is matched to the 365-μm-pitch monolithically-integrated CMUT array. While operating, the RX and logic power consumption per element is 0.85 and 0.10 mW, respectively. TX power consumption is highly waveform dependent, but is nominally 0.34 mW. Compared to the prior art, the probe has the highest volume rate, and features among the largest imaging arrays (both in terms of element-count and aperture) with a high flexibility in defining the TX waveform. These properties make it a suitable option for applications requiring HVR imaging of a large region of interest.

In recent years, numerous flood events have caused loss of life, widespread disruption, and damage across the globe. These devastating impacts highlight the importance of a better understanding of flood generating processes, their impacts, and their variability under climate and landscape changes. Here, we argue that the ability to better model flooding is underpinned by the grand challenge of understanding flood generation mechanisms and potential impacts. To address this challenge, the World Meteorological Organization-Global Energy and Water Exchanges (GEWEX) Hydrometeorology Panel (GHP) aims to establish a Global Flood Crosscutting project to propagate flood modeling and research knowledge across regions and to synthesize results at the global scale. This paper outlines a framework for understanding the dynamics and impacts of runoff generation processes and a rationale for the role of a Global Flood Crosscutting project to address these challenges. Within this Global Flood Crosscutting project, we will establish a common terminology and methods to enable the global research community to exchange knowledge and experiences, and to design experiments toward developing actionable recommendations for more effective flood management practices and policies for improved resilience. This harmonization of rich perspectives across disciplines will foster the co-production of knowledge primed to advance flood research, particularly in the current period of heightened climate variability and rapid change. It will create a new transdisciplinary paradigm for flood science, wherein different dimensions of mechanistic understanding and processes are rigorously considered alongside socioeconomic impacts, early warning communications, and longer-term adaptation to alleviate flood risks in society.

The high thermal stability of a thermoelectric material, which maintains a stable conversion efficiency under prolonged heat exposure, is essential for sustainable thermoelectric applications. Despite the well-known relationship between thermal degradation and microstructural evolution, their underlying interplay remains unclear, with contradictory findings reported in the literature owing to the complex dependence of microstructural changes on the material composition. Herein, the effect of Sb doping on the thermal stability of NbCoSn half-Heusler compounds is investigated in detail by comprehensively analyzing their microstructural evolution. The results reveal that introducing 3.3 at.% Sb into NbCoSn markedly enhances the thermal stability, by preserving the lattice thermal conductivity after heat exposure. Advanced techniques, including atom probe tomography, scanning transmission electron microscopy, and neutron diffraction, show that this improvement is driven by the evolution of Sb-induced complementary point defects. Although heat exposure significantly reduces lattice disorder in intrinsic NbCoSn, NbCoSn_0.9Sb_0.1 retains its lattice disorder by forming alternative point defects, thereby maintaining its lattice thermal conductivity. This detailed experimental work, corroborated by ab initio calculations, highlights the pivotal role of the point defect dynamics in achieving robust thermoelectric performances in half-Heusler compounds for high-temperature applications.

Advances in Earth observation capabilities mean that there is now a multitude of spatially resolved data sets available that can support the quantification of water and carbon pools and fluxes at the land surface. However, such quantification ideally requires efficient synergistic exploitation of those data, which in turn requires carbon and water land-surface models with the capability to simultaneously assimilate several such data streams. The present article discusses the requirements for such a model and presents one such model based on the combination of the existing Data Assimilation Linked Ecosystem Carbon (DALEC) land vegetation carbon cycle model with the Biosphere Energy-Transfer HYdrology (BETHY) land-surface and terrestrial vegetation scheme. The resulting D&B model, made available as a community model, is presented together with a comprehensive evaluation for two selected study sites of widely varying climate. We then demonstrate the concept of land-surface modelling aided by data streams that are available from satellite remote sensing. Here we present D&B with four observation operators that translate model-derived variables into measurements available from such data streams, namely fraction of photosynthetically active radiation (FAPAR), solar-induced chlorophyll fluorescence (SIF), vegetation optical depth (VOD) at microwave frequencies and near-surface soil moisture (also available from microwave measurements). As a first step, we evaluate the combined model system using local observations and finally discuss the potential of the system presented for multi-stream data assimilation in the context of Earth observation systems.

Coastal boulder deposits hold the potential to aid in the reconstruction of past extreme wave events. However, commonly used hydrodynamic equations for calculating wave heights from transported boulders can be inaccurate. New and alternative methods need to be explored in an interdisciplinary way to ensure a more complete picture of the phenomenon of boulder transport is achieved. Through the use of a physical experiment, this study aims to investigate the influence of different tsunami wave types, wave parameters and boulder shapes on boulder transport distance. The experimental results also allow for a novel application of dimensional analysis to enable comparisons with other experiments as well as a field case study. In the experiment an elongate irregularly shaped boulder showed transport distances up to 1 m farther than a cuboid shaped boulder under the influence of the same waves. The irregularly shaped boulder had a predominant transport mode of rolling, whereas the cuboid shaped boulder predominantly underwent sliding transport. Tsunami wave type also influenced boulder transport distances, with N-waves frequently showing greater transport than E-waves of a comparable wave steepness. Key offshore wave and boulder parameters were then compared through dimensional analysis using Buckingham's Pi Theorem, enabling comparisons to other datasets to be made. Data from another published experimental study and a field study in Settai, Japan, showed reasonable agreement, particularly for the shorter period field data. These findings emphasize the importance of incorporating boulder shape, wave type, and dimensional analysis into future studies, providing a foundation for more accurate reconstructions of past tsunami events.

Tropical forests and woodlands are key components of the global carbon and water cycles. Yet, how climate change affects these biogeochemical cycles is poorly understood because of scarce long-term observations of tropical tree growth. The recent rise in tropical tree-ring studies may help to fill this gap, but a large-scale quantitative analysis of their potential in global change research is missing. We compiled a list of all tropical tree species known to form annual tree rings and built a network encompassing 492 tropical ring-width chronologies to evaluate the potential to generate insights on climate sensitivity of woody productivity and to build centuries-long reconstructions of climate variability. We assess chronology quality, length, and climatic representativeness and explore how these change along climatic gradients. Finally, we applied species-distribution modeling to identify regions with potential for tree-ring studies in ecological and climatic studies. The number of tropical chronologies has rapidly increased, with ∼400 added over the past two decades. Yet, tree-ring studies are biased towards high-elevation locations, with gaps in warmer and wetter climates, on the African continent, and for angiosperm species. The longest chronologies with strongest climate signals (i.e., synchronous growth variations among trees) are from cool regions. In wet regions, climate signals and precipitation sensitivity decrease. Most tropical regions harbor 5–15 (and up to 80) species with proven potential to generate chronologies. The potential for long climate reconstructions is particularly high in drier high elevation sites. Our findings support strategies to effectively expand tree-ring research in the tropics, by targeting specific species and regions. Tropical dendrochronology can importantly contribute to global change research by generating historical context of climate extremes, quantifying climate sensitivity of woody productivity and benchmarking vegetation models.

In the collaborative effort towards standardisation of out-of-plane permeability measurement, an international benchmarking exercise was carried out whereby 19 participants worldwide were instructed to measure the out-of-plane permeability following a number of strict guidelines, informed by the outcomes of the first international benchmarking exercise completed in 2021. This paper presents the results of the exercise and an assessment of the reproducibility of the data and the suitability of the proposed test method. The data returned were subjected to a number of statistical analysis methods, which showed that adherence to the test guidelines resulted in a high likelihood of a participant not being an outlier and therefore providing evidence that the test method proposed in this paper is a suitable way forward for a standardised test method.

Objective
To explore the experiences of patients with advanced cancer regarding the timing of ACP.

Methods
This secondary analysis used data from the ACTION cluster-randomized clinical trial. 288 patients with advanced lung or colorectal cancer, WHO performance status 0–3, and with a minimum life expectancy of 3 months were included in this analysis.

Results
The mean time between patients’ cancer diagnosis and the first ACP conversation was 15.3 months (SD:19.4). The average duration from current cancer stage diagnosis to the first conversation was 8.9 months (SD:10.7). The timing of the conversation was perceived as “just right” by 217 (75.3 %) of the patients. Patients who perceived the timing as “too early” were more recently diagnosed with cancer (9.1 months) or with their current cancer stage (5.7 months) than those who did not. Patients perceiving the timing as “too late” had shorter estimated survival times.

Conclusion
Patients with advanced cancer may benefit from earlier ACP than what is currently typically initiated in clinical practice.

Practice implications
When initiating ACP conversations, several aspects should be considered, including patients’ gender, their socio-cultural environment, and their ability to perform daily activities, with or without limitations.

This Roadmap surveys the diversity of different approaches for characterising, modelling and designing metamaterials. It contains articles covering the wide range of physical settings in which metamaterials have been realised, from acoustics and electromagnetics to water waves and mechanical systems. In doing so, we highlight synergies between the many different physical domains and identify commonality between the main challenges. The articles also survey a variety of different strategies and philosophies, from analytic methods such as classical homogenisation to numerical optimisation and data-driven approaches. We highlight how the challenging and many-degree-of-freedom nature of metamaterial design problems call for techniques to be used in partnership, such that physical modelling and intuition can be combined with the computational might of modern optimisation and machine learning to facilitate future breakthroughs in the field.