{"title":"Towards inclusive risk-informed infrastructure development in expanding cities.","authors":"Fabrizio Nocera, Yahya Gamal, Chenbo Wang, Gemma Cremen","doi":"10.1038/s44172-025-00494-3","DOIUrl":"10.1038/s44172-025-00494-3","url":null,"abstract":"<p><p>Conventional natural-hazard risk-modeling approaches do not consider possible unintended negative socioeconomic consequences of designing infrastructure expansions in a risk-informed way. Here, we propose a people-centered decision-making framework for urban infrastructure development that addresses this issue. The framework integrates a bespoke agent-based model that accounts for implications of variations in infrastructure expansion on dynamic land values and related residential location decision making. This means that the model captures macro-scale socioeconomic effects resulting from infrastructure development that are not explicitly related to natural-hazard events. The underlying algorithm balances these considerations with the successful operation of the infrastructure itself and the potential infrastructure performance losses that accompany a natural-hazard event. We demonstrate the framework by optimizing the expansion of transportation in a virtual urban testbed that imitates a typical expanding urban context in the Global South. This work can be used to guide inclusive risk-sensitive infrastructure planning in hazardous, rapidly growing cities.</p>","PeriodicalId":72644,"journal":{"name":"Communications engineering","volume":"4 1","pages":"161"},"PeriodicalIF":0.0,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12405530/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144980903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Information-distilled physics informed deep learning for high order differential inverse problems with extreme discontinuities.","authors":"Mingsheng Peng, Hesheng Tang","doi":"10.1038/s44172-025-00476-5","DOIUrl":"10.1038/s44172-025-00476-5","url":null,"abstract":"<p><p>Standard physics informed deep learning and their enhanced variants encounter challenges in addressing inverse problems characterized by extreme discontinuities and high-order parameterized differential equations due to the use of globally smooth activation functions, especially when the unknown parameters exhibit spatially distributed characteristics. Phenomena such as discontinuous loads, boundary truncations, and abrupt changes in material properties introduce singularities in the derivatives, which in turn lead to ill-conditioned information in the gradient flow. To address these limitations, here we propose an information-distilled physics-informed deep-learning framework that combines reduced-order modeling, multi-level domain decomposition, and an ill-conditioning-suppression mechanism. The framework captures rapid variations in variables within highly localized regions induced by discontinuities. Through an information propagation mechanism and information distillation, the ill-conditioned information in the gradient flow of the system is suppressed. Even in scenarios where specific subnetworks fail, the framework preserves the accuracy of the majority of subnetworks.</p>","PeriodicalId":72644,"journal":{"name":"Communications engineering","volume":"4 1","pages":"150"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12402147/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144980852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Communicating with two vehicles immediately ahead boosts traffic capacity sixfold in connected autonomous vehicle platoons.","authors":"Shi-Teng Zheng, Rui Jiang, Xiqun Michael Chen, Junfang Tian, Xiao Han, Ruidong Yan, Bin Jia, Xiaobo Qu, Zhen-Hua Li, Lan-Da Gao, Fang Zhang, De-Zhao Zhang, Ziyou Gao","doi":"10.1038/s44172-025-00500-8","DOIUrl":"https://doi.org/10.1038/s44172-025-00500-8","url":null,"abstract":"<p><p>Addressing urban congestion through enhanced traffic capacity has emerged as a critical objective for connected autonomous driving technologies. An irredundant communication connectivity topology is essential for ensuring the high efficiency and stability of the traffic system, which has not been fully validated due to the scarcity of real-world tests. Motivated by this fact, this paper deploys a connected autonomous vehicle platoon without relying on the information of a platoon leader to preserve the possibility of extending the platoon in future practical applications. The study is supported by both real-world experiments and simulations, where the following vehicles communicate with the two vehicles immediately ahead. The simulation extends the experimental results to several typical scenarios. The results demonstrate that such a communication structure largely enhances traffic capacity and stability, highlighting the effectiveness of connected autonomous vehicles in managing complex traffic environments. This work gains valuable insights into the sixfold traffic capacity improvement through connected autonomous driving.</p>","PeriodicalId":72644,"journal":{"name":"Communications engineering","volume":"4 1","pages":"160"},"PeriodicalIF":0.0,"publicationDate":"2025-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12398532/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144980909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mark Tingey, Andrew Ruba, Samuel L Junod, Coby Rush, Jason Saredy, William E Brew, Weidong Yang
{"title":"Paired-objectives photon enhancement (POPE) microscopy: enhanced photon collection for fluorescence imaging.","authors":"Mark Tingey, Andrew Ruba, Samuel L Junod, Coby Rush, Jason Saredy, William E Brew, Weidong Yang","doi":"10.1038/s44172-025-00491-6","DOIUrl":"https://doi.org/10.1038/s44172-025-00491-6","url":null,"abstract":"<p><p>Fluorescence microscopy is indispensable for visualizing biological structures and dynamics, yet its efficiency is limited-over half of emitted photons fall outside the objective's numerical aperture and go undetected. Here, we introduce Paired-Objectives Photon Enhancement (POPE) microscopy, which increases photon collection efficiency by up to two-fold using a single excitation source, single detector, and dual objectives. By integrating a 4f optical system with a reflective mirror positioned opposite the objective in an inverted microscope, POPE redirects a substantial portion of otherwise lost photons into the detection pathway. Compatible with super-resolution, confocal, epifluorescence, and autofluorescence modalities, POPE improves spatial resolution, acquisition speed, and signal-to-noise ratio, particularly under photon-limited conditions. It has been validated across fluorophore solutions, subcellular structures, live cells, and thick tissues, consistently enhancing imaging performance. As a modular and cost-effective upgrade for standard inverted microscopes, POPE extends access to high-sensitivity fluorescence imaging and enables new applications in cell biology, biophysics, and biomedical research.</p>","PeriodicalId":72644,"journal":{"name":"Communications engineering","volume":"4 1","pages":"159"},"PeriodicalIF":0.0,"publicationDate":"2025-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12391377/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144980847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hong Wang, Boran Wu, Hongbo Han, Qun Gu, Xiaohu Dai
{"title":"Pilot-scale integration of micron-sized powder carriers and a hydrocyclone separator enhances nutrient removal in wastewater treatment.","authors":"Hong Wang, Boran Wu, Hongbo Han, Qun Gu, Xiaohu Dai","doi":"10.1038/s44172-025-00496-1","DOIUrl":"https://doi.org/10.1038/s44172-025-00496-1","url":null,"abstract":"<p><p>Activity, abundance, and synergy of functional microorganisms are pivotal for wastewater treatment. Here, we developed a micron-medium biofilm composite sludge system, integrating powder carriers and a hydrocyclone separator to enhance functional bacterial enrichment and micro-granule formation. Powder carriers acted as bridges between zoogloea, facilitating coexistence of micro-granules (~115.8 μm) and suspended flocs, thereby improving microbial synergy. The pilot-scale system doubled treatment capacity without expansion or downtime, achieving effluent total nitrogen <5 mg L<sup>-1</sup> and total phosphorus <0.3 mg L<sup>-1</sup> at a hydraulic retention time of 4.85 h. Micro-granules enhanced sludge settleability, mass transfer, and endogenous carbon metabolism, including polyhydroxyalkanoate and glycogen synthesis, which provided essential electron donors for nutrient removal. Denitrifying and phosphorus-accumulating bacteria were enriched in micro-granules (4.46%), whereas nitrifying bacteria (1.25%) were concentrated in flocs. Differentiated spatial distribution balanced the sludge age conflict among functional bacteria. This work provided an efficient and low-carbon strategy for municipal wastewater treatment.</p>","PeriodicalId":72644,"journal":{"name":"Communications engineering","volume":"4 1","pages":"158"},"PeriodicalIF":0.0,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12381278/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144980884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Anibal Tafur, Sotirios A Argyroudis, Stergios A Mitoulis, Jamie E Padgett
{"title":"Climate-resilient railway networks: a resource-aware framework.","authors":"Anibal Tafur, Sotirios A Argyroudis, Stergios A Mitoulis, Jamie E Padgett","doi":"10.1038/s44172-025-00493-4","DOIUrl":"10.1038/s44172-025-00493-4","url":null,"abstract":"<p><p>Coastal hazards and climate change significantly threaten the resilience of railway systems, increasing stresses on global freight transportation, supply chains and economic stability. When it comes to system resilience, resource availability and allocation have been proven to be leading contributors to downtime and losses, alongside the physical vulnerability to extreme loads. To support the quantification and pursuit of system resilience, here we present a probabilistic framework that addresses gaps in resilience modeling of railway systems. Specifically, it systematically integrates tailored structural damage and restoration models across an infrastructure portfolio, while comparatively assessing network-level functionality over time with alternative approaches to recovery resource allocation. Applied to the railway network in Mobile and Baldwin Counties, Alabama, the framework estimates damage states, restoration costs and times, modeling drop and recovery of network functionality. Findings indicate that sea-level rise considerably affects service reinstatement, reducing resilience index up to 80% when combined with hurricanes. Resource allocation strategies also impact resilience, with variations resulting in up to 75% differences in resilience estimates. These results underscore the need to consider resource constraints and sea-level rise in resilience planning, offering nuanced resilience quantification to support decision-making for mitigation and response strategies, benefiting policymakers, infrastructure managers, insurers, and agencies.</p>","PeriodicalId":72644,"journal":{"name":"Communications engineering","volume":"4 1","pages":"157"},"PeriodicalIF":0.0,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12371024/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144980860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Freeze-thaw recycling for fiber-resin separation in retired wind blades.","authors":"Khalil Ahmed, Xu Jiang, Ghazala Ashraf, Xuhong Qiang","doi":"10.1038/s44172-025-00490-7","DOIUrl":"10.1038/s44172-025-00490-7","url":null,"abstract":"<p><p>The disposal of decommissioned wind turbine blades represents a growing economic loss and environmental concern due to the non-recovery of durable glass fiber-reinforced epoxy composites. Existing thermal and chemical recycling methods often require high temperatures and toxic chemicals, causing material degradation. Here, we present a novel freeze-thaw-based method for fiber-resin separation as an alternative. The process uses only water at human-safe temperatures, leveraging ice-induced expansion to disrupt the glass fiber-epoxy interface. Microscopic imaging and weight analysis revealed visible interface separation, with three-dimensional imaging showing a ~ 65% increase in crack volume and a ~ 32% rise in connected porosity after freeze-thaw treatment. Glass fibers retained up to 96% of their original mechanical properties, demonstrating minimal structural damage. Microplastics were easily removed through filtration, and the effluent water remained near-neutral with low organic carbon levels, meeting global water safety standards. These findings highlight freeze-thaw cycling as a sustainable route for efficient fiber-resin separation with minimal environmental impact.</p>","PeriodicalId":72644,"journal":{"name":"Communications engineering","volume":"4 1","pages":"153"},"PeriodicalIF":0.0,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12354729/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144857148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mayar Ariss, Bryan German Pantoja-Rosero, Fabio Duarte, Mikita Klimenka, Carlo Ratti
{"title":"Seismic assessment of unreinforced masonry façades from images using macroelement-based modeling.","authors":"Mayar Ariss, Bryan German Pantoja-Rosero, Fabio Duarte, Mikita Klimenka, Carlo Ratti","doi":"10.1038/s44172-025-00487-2","DOIUrl":"10.1038/s44172-025-00487-2","url":null,"abstract":"<p><p>Despite the variability of urban infrastructure, unreinforced masonry buildings remain globally prevalent. Constructed from brick, hollow concrete blocks, stone, or other masonry materials, these structures account for a significant proportion of fatalities during seismic events-particularly in regions with limited access to early warning systems. Due to the complex behavior of masonry, accurately assessing structural vulnerabilities is highly dependent on the chosen modeling strategy. Yet, scalable, cost-effective approaches based on simple RGB imagery can still offer valuable insights. In this context, building on a previously developed digitalization methodology, this study proposes an automated, image-based framework for the rapid, non-invasive seismic evaluation of façades, addressing important research gaps in disaster resilience. The framework links image data with structural simulation by extracting visual and geometric features and translating them into consistent macroelement models using computer vision techniques, enabling nonlinear analyses under in-plane cyclic loading. The adopted numerical strategy has been extensively validated in prior work, with predictions closely aligning with experimental results. While the outcomes are predictive rather than diagnostic, future integration with publicly accessible urban imagery may enable the development of real-time, cross-border seismic risk maps.</p>","PeriodicalId":72644,"journal":{"name":"Communications engineering","volume":"4 1","pages":"155"},"PeriodicalIF":0.0,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12354861/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144857149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sayeed Shafayet Chowdhury, Deepika Sharma, Adarsh Kosta, Kaushik Roy
{"title":"Neuromorphic computing for robotic vision: algorithms to hardware advances.","authors":"Sayeed Shafayet Chowdhury, Deepika Sharma, Adarsh Kosta, Kaushik Roy","doi":"10.1038/s44172-025-00492-5","DOIUrl":"10.1038/s44172-025-00492-5","url":null,"abstract":"<p><p>Neuromorphic computing offers transformative potential for AI in resource-constrained environments by mimicking biological neural efficiency. This perspective article analyzes recent advances and future directions, advocating a system design approach that integrates specialized sensing (e.g., event-based cameras), brain-inspired algorithms (SNNs and SNN-ANN hybrids), and dedicated neuromorphic hardware. Using vision-based drone navigation (VDN) as an exemplar-drawing parallels with biological systems like Drosophila-we demonstrate how these components enable event-driven processing and overcome von Neumann architecture limitations through near-/in-memory computing. Key challenges include large-scale integration, benchmarking standardization, and algorithm-hardware co-design for emerging applications, which we discuss alongside current and future research directions.</p>","PeriodicalId":72644,"journal":{"name":"Communications engineering","volume":"4 1","pages":"152"},"PeriodicalIF":0.0,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12350809/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144849957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Efficient estimating and clustering lithium-ion batteries with a deep-learning approach.","authors":"Jie Wu, Zhongxian Sun, Dingquan Li, Weilin He, Dongchen Yang, Zhenguo Wu, Xin Geng, Hui Yang, Hailong Wang, Linyu Hu, Haiyan Tu, Xin He","doi":"10.1038/s44172-025-00488-1","DOIUrl":"10.1038/s44172-025-00488-1","url":null,"abstract":"<p><p>Growing energy storage demand has solidified the dominance of lithium-ion batteries (LIBs) in modern societies but intensifies recycling pressures. Precise state-of-health (SOH) assessment is crucial to grouping retired batteries from an unknown state for secondary utilization. However, batteries in the pack exhibit distinct capacity fading behaviors due to their service scenarios and working conditions. We develop a deep-learning framework for rapid, transferable SOH estimation and battery classification. This framework integrates deep neural networks with interconnected electrochemical, mechanical, and thermal features. Our model delivers optimal accuracy with a mean absolute error (MAE) of 0.822% and a root mean square error (RMSE) of 1.048% using combined features. It demonstrates robust performance across various conditions and enables SOH prediction with data from merely one previous cycle. Moreover, the well-trained model could adapt to other electrode systems with a minimal number of additional samples. This work highlights critical features for SOH estimation and enables efficient battery classification toward sustainable recycling.</p>","PeriodicalId":72644,"journal":{"name":"Communications engineering","volume":"4 1","pages":"151"},"PeriodicalIF":0.0,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12344010/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144838725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}