Search Results (8,507)

The synthesis of monocyclic and bicyclic compounds plays a fundamental role in organic chemistry, and the need for novel synthetic methodologies is still under investigation. In particular, α,β-unsaturated (bis)enones have emerged as valuable precursors for the formation of cyclic (both mono and bicyclic) structures through single-electron transfer (SET) processes. Single-electron transfer (SET) is a redox process where one electron moves from a donor species to an acceptor, generating radical ions or neutral radicals that drive unique reaction pathways. Thanks to the advent of radical chemistry, it was possible to discover an entirely new reactivity of α,β-unsaturated (bis)enones, which, after a SET event, undergo the formation of cyclic molecules, both in intra and inter-molecular reactions, under several possible pathways, including formal [2+2] cycloaddition reaction (22CA) and 5-exo-trig cyclization, for ring closure. Today, the generation of radical species can be broadly classified into three main approaches: photochemical and photocatalytic, metal-driven and electrochemical processes. In this review, we summarize the progress achieved to date in the synthesis of cyclic molecules from α,β-unsaturated (bis)enones via single-electron transfer events under these three main classes of processes. Whenever possible, the reaction pathway and fate of the radical species generated through SET is discussed. Full article

Internal wall grinding of pipes constitutes a critical pretreatment procedure in the anti-corrosion repair operations of Prestressed Concrete Cylinder Pipes (PCCP). To address the limitations of low efficiency and poor safety associated with traditional manual internal wall grinding in PCCP anti-corrosion repair, this study presents the design of a support-wheel-type internal wall grinding robot for pipes. The robot’s structure comprises a walking support module and a grinding module: the walking module employs four sets of circumferentially equally spaced (90° apart) independent-support wheel groups. Through an active–passive collaborative adaptation mechanism regulated by pre-tensioned springs and lead screws, the robot can dynamically conform to the inner wall of the pipe, ensuring stable locomotion. The grinding module is connected to the walking module via a slewing bearing and is equipped with three roller-type steel brushes. During operation, the grinding module revolves around the pipe axis, while the roller brushes rotate simultaneously, generating a composite three-helix grinding trajectory. Mathematical models for the robot’s obstacle negotiation, bend traversal, and grinding motion were established, and multi-body dynamics simulations were conducted using ADAMS for verification. Additionally, a physical prototype was developed to perform basic functional tests. The results demonstrate that the robot’s motion characteristics are highly consistent with theoretical analyses, exhibiting stable and reliable operation, excellent pipe traversability, and robust driving capability, thus meeting the requirements for internal wall grinding of PCCP pipes. Full article

Background: In-hospital cardiac arrest (IHCA) constitutes a high-impact clinical event, associated with substantial mortality, frequent neurological and functional impairment. There is a pressing need for primary IHCA studies that evaluate risk predictors, given the inherent challenges of IHCA data collection, previously unharmonized reporting frameworks, and the predominant focus of prior investigations on other domains. Among potential contributors, the “off-hours effect” has consistently been linked to poorer IHCA outcomes. Accordingly, we sought to examine whether in-hospital mortality after IHCA varies according to the time and day of occurrence within a tertiary academic center in Northern Greece. Methods: We conducted a single-center observational cohort study using a prospectively maintained in-hospital resuscitation registry at AHEPA University General Hospital, Thessaloniki. All adults with an index IHCA between 2017 and 2019 were included, and definitions followed Utstein-style recommendations. Results: Multivariable logistic regression adjusted for organizational, patient, and process-of-care factors demonstrated that afternoon/night arrests, weekend arrests, heart failure comorbidity, and need for mechanical ventilation were independent predictors of higher in-hospital mortality. Conversely, arrhythmia as the cause of IHCA and arrests occurring in the intensive care unit or operating room were associated with improved survival. Subgroup analyses confirmed consistent off-hours differences, with weekend events showing reduced 30-day and 6-month survival and worse functional status at discharge. Afternoon/night arrests were more frequent, characterized by longer response intervals and lower survival at both time points. Conclusions: Organizational factors during nights and weekends, rather than patient case mix, drive poorer IHCA outcomes, underscoring the need for targeted system-level improvements. Full article

The fastest growth in electricity demand in the industrialized world will likely come from the broad adoption of artificial intelligence (AI)—accelerated by the rise of generative AI models such as OpenAI’s ChatGPT. The global “data center arms race” is driving up power demand and grid stress, which creates local and regional challenges because people in the area understand that the additional data center-related electricity demand is coming from faraway places, and they will have to support the additional infrastructure while not directly benefiting from it. So, there is an incentive for the data center operators to manage the fast and unpredictable power surges internally so that their loads appear like a constant baseload to the electricity grid. Such high-intensity and short-duration loads can be served by hybrid energy storage systems (HESSs) that combine multiple storage technologies operating across different timescales. This review presents an overview of energy storage technologies, their classifications, and recent performance data, with a focus on their applicability to AI-driven computing. Technical requirements of storage systems, such as fast response, long cycle life, low degradation under frequent micro-cycling, and high ramping capability—which are critical for sustainable and reliable data center operations—are discussed. Based on these requirements, this review identifies lithium titanate oxide (LTO) and lithium iron phosphate (LFP) batteries paired with supercapacitors, flywheels, or superconducting magnetic energy storage (SMES) as the most suitable HESS configurations for AI data centers. This review also proposes AI-specific evaluation criteria, defines key performance metrics, and provides semi-quantitative guidance on power–energy partitioning for HESSs in AI data centers. This review concludes by identifying key challenges, AI-specific research gaps, and future directions for integrating HESSs with on-site generation to optimally manage the high variability in the data center load and build sustainable, low-carbon, and intelligent AI data centers. Full article

Antimicrobial resistance (AMR) in hospital wastewater is a recognized public health concern, yet the dynamics of its emergence remain poorly understood. This study aimed to characterize the quantitative and qualitative changes in the microbial community of a newly built internal medicine intensive care hospital wing following the start of patient treatment. Wastewater samples were collected regularly from eight relevant sites, including seven patient-associated locations within the intensive care ward and the central sanitary sewer where all effluent converged. Culture-based analyses targeted the “ESCAPE-SO” bacterial and fungal groups (“Enterococci”, “Staphylococci”, “Candida”, “Acinetobacter”, “Pseudomonas”, “Enterobacteriaceae”, “Stenotrophomonas”, “Others”). Comparisons were made between a 12-month pre-operation period (only flushing every 72 h to prevent contamination of the drinking water system) and the first 12 months of patient treatment. The results showed a significant increase in mean bacterial concentrations from 53 [0–349] CFU/mL before patient treatment to 8423 [3054–79,490] CFU/mL during patient treatment (p = 0.0224) with a particular focus on Pseudomonas spp. as the dominant genus. Resistance against all four main antibiotic classes of the WHO AWaRe essential “watch” list (carbapenems, third-generation cephalosporins, broad-spectrum penicillin and ciprofloxacin) emerged within the first twelve months and depended on the amount of prescribed antibiotics and the number of patients treated. These findings indicate that hospital activity drives rapid development of antimicrobial resistance in wastewater microbial communities, highlighting the critical role of clinical antibiotic use in shaping environmental resistomes. This study provides quantitative evidence that resistance can emerge within months of hospital operation, emphasizing the need for early monitoring and targeted interventions to mitigate the spread of AMR from hospital effluents into broader environmental systems. Full article

Biological, biomimetic, and engineering systems make extensive use of hydraulic asymmetries to control flow inside tubular structures. Examples span physiological valves, the guided transport observed in shark intestines, and passive devices such as Tesla valves. Here we investigate the mechanisms that generate these asymmetries using the notion of diodicity, defined as the ratio between pressure drops required to drive the same flow in opposite directions. We first focus on 2D geometries, which allow us to identify and study the main contributions to hydraulic asymmetry: channel geometry and internal obstacles embedded within a channel with rigid walls. By considering both rigid and deformable obstacles, we model channels that always remain open in both directions and channels that can be completely blocked by valve-like structures. We then extend the analysis to 3D geometries, again considering rigid and elastic cases. As a general trend, we find that geometry alone establishes a baseline diodicity, while higher dimensionality and structural reconfiguration consistently amplify the effect. Full article

By addressing the challenges of management difficulties, insufficient integration of driver analysis, and single-dimensional analysis in the governance of illegal land use and illegal construction (collectively referred to as the “Two Illegalities”) under rapid urbanization, this study designs and implements a GIS-based governance system using Xiamen City as the study area. First, we propose a standardized data-processing workflow and construct a comprehensive management platform integrating multi-source data fusion, spatiotemporal visualization, intelligent analysis, and customized report generation, effectively lowering the barrier for non-professional users. Second, utilizing methods integrated into the platform, such as Moran’s I and centroid trajectory analysis, we deeply analyze the spatiotemporal evolution and driving mechanisms of “Two Illegalities” activities in Xiamen from 2018 to 2023. The results indicate that the distribution of “Two Illegalities” exhibits significant spatial clustering, with hotspots concentrated in urban–rural transition zones. The spatial morphology evolved from multi-core diffusion to the contraction of agglomeration belts. This evolution is essentially the result of the dynamic adaptation between regional economic development gradients, urbanization processes, and policy-enforcement synergy mechanisms. Through a modular, open technical architecture and a “Data-Technology-Enforcement” collaborative mechanism, the system significantly improves information management efficiency and the scientific basis of decision-making. It provides a replicable and scalable technical framework and practical paradigm for similar cities to transform “Two Illegalities” governance from passive disposal to active prevention and control. Full article

The increasing heterogeneity of wheeled mobile robot (WMR) architectures, including differential-drive, Ackermann, omnidirectional, and reconfigurable platforms, poses a major challenge for defining a unified, scalable kinematic representation. Most existing formulations are tailored to specific mechanical layouts, limiting analytical coherence, cross-platform interoperability, and the systematic reuse of modeling, odometry, and motion-related algorithms. This work introduces a generalized kinematic modeling framework that provides a mathematically consistent formulation applicable to arbitrary WMR configurations. Wheel–ground velocity relationships and non-holonomic constraints are expressed through a concise vector formulation that maps wheel motions to chassis velocities, ensuring consistency with established models while remaining independent of the underlying mechanical structure. A parameterized wheel descriptor encodes all relevant geometric and kinematic properties, enabling the modular assembly of complete robot models by aggregating wheel-level relations. The framework is evaluated through numerical simulations on four structurally distinct platforms: differential-drive, Ackermann, three-wheel omnidirectional (3,0), and 4WD. Results show that the proposed formulation accurately reproduces the expected kinematic behavior across these fundamentally different architectures and provides a coherent and consistent representation of their motion. The unified representation further provides a common kinematic backbone that is directly compatible with odometry, motion-control, and simulation pipelines, facilitating the systematic retargeting of algorithms across heterogeneous robot platforms without architecture-specific reformulation. Additional simulation studies under realistic physics-based conditions show that the proposed formulation preserves coherent kinematic behavior during complex trajectory execution and supports the explicit incorporation of geometric imperfections, such as wheel mounting misalignments, when such parameters are available. By consolidating traditionally separate derivations into a single coherent formulation, this work establishes a rigorous, scalable, and architecture-agnostic foundation for unified kinematic modeling of wheeled mobile robots, with particular relevance for modular, reconfigurable, and cross-architecture robotic systems. Full article

Unmanned aerial vehicles open new possibilities for developing technologies that support more sustainable and efficient agriculture. This paper presents a non-invasive method for repelling rodents from crop fields using ultrasound. The proposed system is implemented as a spherical-cap ultrasound loudspeaker array consisting of eight transducers, mounted on a drone that overflies the field while emitting sound in the 20–70 kHz range. The hardware design includes both the loudspeaker array and a custom printed circuit board hosting power amplifiers and a signal generator tailored to drive multiple ultrasonic transducers. In parallel, a genetic algorithm is used to compute flight paths that maximize coverage and increase the probability of driving rodents away from the protected area. As part of the validation phase, artificial intelligence models for rodent detection using a thermal camera are developed to provide quantitative feedback on system performance. The complete prototype is evaluated through a series of experiments conducted both in controlled laboratory conditions and in the field. Field trials highlight which parts of the concept are already effective and identify open challenges that need to be addressed in future work to move from a research prototype toward a deployable product. Full article

The micromechanisms “slip transfer, slip irreversibility, microplasticity, and fatigue cracking” in titanium alloys are reviewed, with a special emphasis on near-α and α + β alloys. As the interplay between slip activity, microplasticity, and fatigue cracking governs both the microscale and macroscale mechanical response, we reveal how the slip irreversibility and localized dislocation activity at the grain boundaries (GBs) and α/β interfaces generate dislocation pile-ups and strain localization, subsequently driving fatigue crack initiation and propagation. The review highlights the favorable crack initiation along basal planes and the roles of α grain orientations, slip transfer barriers, and the β phase in governing fatigue cracking, while addressing unresolved questions about localized interactions and texture effects. It also explores the complex interactions that govern the effects of microstructures, textures, and defects on fatigue cracking. Ultimately, the review provides a unified framework for linking slip events to microplasticity and to fatigue failure, offering actionable insights for alloy design and fatigue prediction. Full article

Community public sport facilities are core carriers of the national fitness public service system, with their supply–demand alignment directly linked to megacity governance efficiency and residents’ well-being. To address structural issues, such as “human–land imbalance” in facility layout, this study uses the 2010–2024 panel data from Shanghai’s 16 districts, applies supply–demand equilibrium theory, and integrates quantitative methods to analyze spatio-temporal supply–demand coupling and identify key influencing factors. The study yields four key findings: (1) The spatial distribution of facilities and population demonstrates a differentiated evolutionary trajectory marked by “central dispersion and suburban stability”. (2) Supply–demand alignment has continuously improved, as evidenced by the increase in coordinated administrative districts from six to thirteen. Nonetheless, the distance between sports facilities and population centers widened, suggesting that spatial adaptation remains incomplete. (3) Urban population growth exerts a significant positive impact on facility supply. Elasticity coefficients are generally high in suburban areas, while negative elasticity is detected in some central urban areas due to population outflow. (4) Facility construction intensity and residential activity intensity are core driving factors, with economic conditions, transportation infrastructure, and housing prices acting as key supporting factors. This study overcomes traditional aggregate-quantity research limitations, reveals megacity facility supply–demand “spatial mismatch” dynamics, and provides a scientific basis for targeted public sports facility layout and refined governance. Full article

Bacteriophages, or phages, are viruses that specifically infect and lyse bacterial cells. Since their discovery 110 years ago, they have held a unique place in microbiology, medicine, and agriculture as both scientific tools and potential therapeutic agents. The concept of employing phages to combat bacterial infections, known as phage therapy, predates the antibiotic era and has undergone cycles of enthusiasm, neglect, and revival. Initially explored in the early 20th century, phage therapy offered a targeted biological approach to bacterial disease control. However, the widespread adoption of antibiotics led to a significant reduction in phage research, which only regained momentum in recent decades owing to the global rise of antibiotic-resistant bacteria and increasing demand for environmentally sustainable disease management strategies. This review traces the complete timeline of this history, highlighting key milestones in phage discovery, molecular microbiology, the antibiotic era, and the resulting critical events that spurred the modern phage renaissance in plant disease management. Finally, the significance of cutting-edge integration of synthetic biology, advanced phage delivery systems, and artificial intelligence (AI), which could drive the development of next-generation biopesticides, is also discussed. Full article

Fuel consumption in heavy-duty off-road machinery depends on a wide range of interacting factors related to the operating environment, the technical characteristics and condition of the machine, and the behaviour, experience and state of the operator. Existing studies typically address only fragments of this relationship, focusing on vehicle parameters, selected environmental factors or individual aspects of driving style. The method proposed in this work provides a general and transferable framework for assessing fuel consumption in any type of machine or vehicle. The Integrated Fuel Consumption Assessment Model (IFCAM) combines environmental, vehicle and human domains into a coherent structured formula that can be used across different operational contexts. The model was developed using continuous short-term measurements and long-term operational data collected during real industrial work. Its universal structure makes it applicable not only to mining equipment, but also to construction machinery and transport vehicles, as well as conventional passenger cars, where it offers a systematic procedure for estimating fuel demand under variable operating conditions. The results demonstrate that integrating multi-domain data improves predictive accuracy and opens new possibilities for analysing operator influence and overall energy efficiency. Full article

Under the pressing imperative of achieving “dual carbon” goals and advancing urban low-carbon transitions, understanding how neighborhood spatial environments influence carbon emissions has become a critical challenge for enabling refined governance and precise planning in urban carbon reduction. Taking the central urban area of Xining as a case study, this research establishes a high-precision estimation framework by integrating Semantic Segmentation of Street View Images and Point of Interest data. This study employs a Geographically Weighted XGBoost model to capture the spatial non-stationarity of emission drivers, achieving a median R² of 0.819. The results indicate the following: (1) Socioeconomic functional attributes, specifically POI Density and POI Mixture, exert a more dominant influence on carbon emissions than purely visual features. (2) Lane Marking General shows a strong positive correlation by reflecting traffic pressure, Sidewalks exhibit a clear negative correlation by promoting active travel, and Building features display a distinct asymmetric impact, where the driving effect of high density is notably less pronounced than the negative association observed in low-density areas. (3) The development of low-carbon neighborhoods should prioritize optimizing functional mixing and enhancing pedestrian systems to construct resilient and low-carbon urban spaces. This study reveals the non-linear relationship between street visual features and neighborhood carbon emissions, providing an empirical basis and strategic references for neighborhood planning and design oriented toward low-carbon goals, with valuable guidance for practices in urban planning, design, and management. Full article

To accurately investigate the loss characteristics of fuel cell vehicles (FCVs) under actual operating conditions and enhance their power performance and economic efficiency, this study establishes a numerical model of the proton exchange membrane fuel cell (PEMFC) stack based on real-world data from the second-generation Mirai. The stack model incorporates leakage current losses and imposes a limit on maximum current density. Besides, this study analyzes the effects of operating parameters (PEM water content, hydrogen partial pressure, current density, oxygen partial pressure, and operating temperature) on stack power output, efficiency, and eco-performance coefficient (ECOP). Furthermore, Non-Dominated Sequential Genetic Algorithm (NSGA-II) is employed to optimize the PEMFC stack performance, yielding the optimal operating parameter set for FCV operation. Further simulations are conducted on dynamic performance characteristics of the second-generation Mirai under two typical driving cycles, evaluating the power performance and economy of the FCV before and after optimization. Results demonstrate that the established PEMFC stack model accurately analyzes the output performance of an actual FCV when compared with real-world performance test data from the second-generation Mirai. Through optimization, output power increases by 7.4%, efficiency improves by 1.95%, and ECOP rises by 3.84%, providing guidance for enhancing vehicle power performance and improving overall vehicle economy. This study provides a practical framework for enhancing the power performance and overall energy sustainability of fuel cell vehicles, contributing to the advancement of sustainable transportation. Full article