Tunability of functional properties in a continuous manner is desired but challenging to accomplish for organic solid-state materials. Herein, we describe a method for tuning optoelectronic properties of solid-state aggregates with narrow absorption bands. First, we systematically shift the absorption maxima of highly dipolar merocyanine dyes in solution by chemical alterations of their chromophore cores. This leaves their solid-state packing arrangements unchanged, affording similar J- and H-coupled aggregate absorption bands at different wavelengths. Next, mixing these isostructural dyes leads to a spectral fine-tuning of the mixed layers, which could be characterized as crystalline organic solid solutions and utilized in narrowband color-selective organic photodiodes. Finally, we devise a semiempirical model, which explains the observed spectral tuning in terms of the molecular exciton theory. Thus, we demonstrate narrowband absorbing solid-state aggregates spanning the wavelength range of 437–760 nm, whose absorption can be fine-tuned over 40% of the visible light range.

This chapter starts by introducing the fundamentals of power and efficiency measurements and then describes a power and performance benchmark methodology developed by the SPECpower committee for commodity servers. It is designed to characterize and rate the energy efficiency of a system under test for multiple load levels, showcasing load level differences in system behavior regarding energy efficiency. The methodology was first implemented in the SPECpower_ssj 2008 benchmark and later extended with more workloads, metrics, and other application areas for the SPEC Server Efficiency Rating Tool (SERT) suite. The SERT suite was developed to fill the need for a rating tool that can be utilized by government agencies in their regulatory programs, for example, the U.S. Environmental Protection Agency (EPA) for the use in their ENERGY STAR program for servers.

This chapter starts by introducing the fundamentals of power and efficiency measurements and then describes a power and performance benchmark methodology developed by the SPECpower committee for commodity servers. It is designed to characterize and rate the energy efficiency of a system under test for multiple load levels, showcasing load level differences in system behavior regarding energy efficiency. The methodology was first implemented in the SPECpower_ssj 2008 benchmark and later extended with more workloads, metrics, and other application areas for the SPEC Server Efficiency Rating Tool (SERT) suite. The SERT suite was developed to fill the need for a rating tool that can be utilized by government agencies in their regulatory programs, for example, the U.S. Environmental Protection Agency (EPA) for the use in their ENERGY STAR program for servers.

AI search tools are rapidly gaining in popularity, with nearly one in four Americans now saying they have used AI in place of traditional search engines. These tools derive their value from crawling the internet for up-to-date, relevant information—content that is often produced by news publishers.

This chapter starts by introducing the fundamentals of power and efficiency measurements and then describes a power and performance benchmark methodology developed by the SPECpower committee for commodity servers. It is designed to characterize and rate the energy efficiency of a system under test for multiple load levels, showcasing load level differences in system behavior regarding energy efficiency. The methodology was first implemented in the SPECpower_ssj 2008 benchmark and later extended with more workloads, metrics, and other application areas for the SPEC Server Efficiency Rating Tool (SERT) suite. The SERT suite was developed to fill the need for a rating tool that can be utilized by government agencies in their regulatory programs, for example, the U.S. Environmental Protection Agency (EPA) for the use in their ENERGY STAR program for servers.

Abstract A collapse of the Atlantic Meridional Overturning Circulation (AMOC) under a quasi-equilibrium freshwater forcing has now been found in a hierarchy of ocean-climate models and up to a fully-coupled climate model, the Community Earth System Model (CESM). However, the effects of eddies on the ocean flows are represented in a highly idealized way in the CESM and it is unknown how these affect AMOC stability. Here, we show results of the first quasi-equilibrium hosing simulation with a strongly eddying ocean-only model in which the AMOC collapses. By comparing these results to those of a companion non-eddying simulation with the same model, it is found that eddies are able to maintain a weak (∼ \\($\sim \$\)5 Sv) AMOC flow in the collapsed state. In addition, we find that the AMOC induced freshwater transport at 34° \\($^\circ\$\)S is a reliable physics-based early warning indicator for the onset of the AMOC collapse.

Spatial computing is set to change the way we work. It will enable both focused work through a higher degree of immersion and collaborative work through enhanced integration of shared interaction spaces or interaction partners. With the Apple Vision Pro, the level of immersion can be adjusted seamlessly. So far, there have been no systematic studies on how this adjustability affects work performance when working alone or together. The present empirical study fills this research gap by varying the level of immersion across three stages (high, medium, low) while solving various tasks with the Apple Vision Pro. The results show that selective attention improves significantly with increasing immersion levels. In contrast, social presence decreases with increasing immersion. In general, participants performed better in the individual task than in the collaborative task. However, the degree of immersion did not influence the collaborative performance. In addition, we could not determine any adverse effects on depth perception or user experience after use. The present study provides initial contributions to the future of spatial computing in professional settings and highlights the importance of balancing immersion and social interaction in a world where digital and physical spaces seamlessly coexist

Urban vegetation plays a pivotal role in mitigating environmental challenges, yet its growth is influenced by both positive and negative impacts of urbanization. The spatio-temporal dynamics of these dual effects, particularly the indirect benefits, remain insufficiently explored. Taking Chengdu as a case study, we applied two complementary urban intensity gradients, a conceptual (local) and a physical (rural-urban) approach, to quantify urbanization's impacts on vegetation, as measured by net primary productivity (NPP), and to investigate temporal and spatial variations. Both approaches indicate that urbanization initially has a negative effect on vegetation, but transitions to positive impact as overall urban intensity increases. The conceptual gradient analysis demonstrates a marked temporal increase in positive indirect effect, rising from 0.99 % in 2000 to 49.51 % in 2010 and reaching 85.15 % in 2018, highlighting significant temporal variability in vegetation enhancement. Meanwhile, the physical gradient reveals pronounced spatial heterogeneity, with stable and prominent indirect compensation effects in suburban areas compared to urban cores. These findings deepen the understanding of urban vegetation dynamics and provide valuable guidance for targeted vegetation management and sustainable urban planning.

INTRODUCTION: Major electrocardiogram abnormalities (MECG) are common in middle-aged and older individuals and could be an important factor in predicting cardiovascular events. OBJECTIVE: To analyse the association between MECG (Minnesota classification) and CVE independently of classic cardiovascular risk factors (CVRF), and to assess whether they improve the prediction according to the Spanish Coronary Event Risk Function (FRESCO). METHOD: 1.752 participants included in three nodes of the PREDIMED study aged between 55 and 80 years with medium or high CVRF. Mean follow-up time was 5.1 years. Cumulative CVE incidence was estimated by sex with and without MECG, and hazard ratios by sex were estimated using multivariate Cox regressions adjusted for randomization group and CCRF (FRESCO). Harrel's C Indices, Nam d'Agostino, Net Reclassification Improvement, and Integrated Discrimination Improvement were calculated. RESULTS: At baseline, 25% of the participants shows major electrocardiogram abnormalities (AMECG). During follow-up, there were 112 cardiovascular events (16 cardiovascular deaths, 15 acute myocardial infarctions, 38 anginas, 43 strokes). MECG were significantly associated with the onset of CVE. In men, left ventricular hypertrophy (LVH) criteria were associated with T-wave inversion (HR: 17.88, 95% CI: 5.51-58.03, pvalor<.001) and QT interval prolongation (HR: 2.41, 95% CI: 1.38-4.21, pvalor=.002); in women, atrial fibrillation (HR: 5.7, 95% CI: 1.76-18.72, pvalor=.006) and ST-segment depression (HR: 3.24, 95% CI: 1.36-7.71, pvalor<.001) were associated. No significant improvement in MECG prediction compared to FRESCO was observed. CONCLUSIONS: MECG are independently associated with the occurrence of CVE, but do not improve risk prediction beyond traditional risk factors.

As augmented reality (AR) headsets become increasingly integrated into professional and social settings, a critical challenge emerges: how can users effectively manage and interact with the frequent notifications they receive? With adults receiving nearly 200 notifications daily on their smartphones, which serve as primary computing devices for many, translating this interaction to AR systems is paramount. Unlike traditional devices, AR systems augment the physical world, requiring interaction techniques that blend seamlessly with real-world behaviors. This study explores the complexities of multimodal interaction with notifications in AR. We investigated user preferences, usability, workload, and performance during a virtual cooking task, where participants managed customer orders while interacting with notifications. Various interaction techniques were tested: Point and Pinch, Gaze and Pinch, Point and Voice, Gaze and Voice, and Touch. Our findings reveal significant impacts on workload, performance, and usability based on the interaction method used. We identify key issues in multimodal interaction and offer guidance for optimizing these techniques in AR environments.

Artificial light at night has increased significantly in recent decades, profoundly impacting moths, which are key contributors to pollination networks. The global shift to light-emitting diode (LED) streetlights has further transformed the nocturnal light environment, especially because of their high variability in spectrum and intensity. However, the impact on moths' mating success remains poorly understood, highlighting the urgent need to investigate their behavioural responses. We recorded the flight behaviour of male moths (Sphinx ligustri L.) using a symmetrical flight tunnel. Two different light environments, homogeneous and heterogeneous, with a female positioned on one side of the tunnel, were used to test in different combinations the effect of LEDs (Amber, Warm white and Neutral white) and intensities (0.05, 150, 370 and 590 lux) on arrival location, flight duration and direction changes of males. In a homogeneous light environment, all tested LEDs significantly reduced the arrival frequency of males at the females compared with a dim light condition, demonstrating that streetlight negatively affects encounter rates. However, neither flight duration nor direction changes were significantly affected. In a heterogeneous light environment, the highest proportion of males was able to reach the females in the presence of Warm white (2200 K), indicating that Amber (1800 K) may not be a universal solution for mitigating the negative effects of artificial light. Both flight duration and direction changes were significantly reduced for Neutral white (3900 K) compared with Warm white, concluding that this LED type induced fast and directed flights towards the light source. Interestingly, light intensity did not significantly affect any of the analysed parameters. Statement of significance: The presence of light drastically reduced the probability of males reaching the females. Furthermore, LEDs with the lowest correlated colour temperature (CCT) were not the ones leading to the highest promise of mating success, indicating that the spectrum of an LED might have an optimum. As LED efficiency decreases with lower CCT values this finding is of crucial importance when considering the indirect effects of light pollution, such as the CO2 footprint, when developing lighting strategies as minimally disruptive as possible.

Agile methodologies have transformed organizational management by prioritizing team autonomy and iterative learning cycles. However, these approaches often lack structured mechanisms for knowledge retention and interoperability, leading to fragmented decision-making, information silos, and strategic misalignment. This study proposes an alternative approach to knowledge management in Agile environments by integrating Ikujiro Nonaka and Hirotaka Takeuchi’s theory of knowledge creation— specifically the concept of Ba, a shared space where knowledge is created and validated—with Jürgen Habermas’s Theory of Communicative Action, which emphasizes deliberation as the foundation for trust and legitimacy in organizational decision-making. To operationalize this integration, we propose the Deliberative Permeability Metric (DPM), a diagnostic tool that evaluates knowledge flow and the deliberative foundation of organizational decisions, and the Communicative Rationality Cycle (CRC), a structured feedback model that extends the DPM, ensuring long-term adaptability and data governance. This model was applied at Livelo, a Brazilian loyalty program company, demonstrating that structured deliberation improves operational efficiency and reduces knowledge fragmentation. The findings indicate that institutionalizing deliberative processes strengthens knowledge interoperability, fostering a more resilient and adaptive approach to data governance in complex organizations.

This paper presents a novel, formal language semantics and an abstraction layer for developing application code focussed on running on agents or nodes of a multi-node distributed system aimed at providing any IoT service, automation, control or monitoring in the physical environment. The proposed semantics are rigorously validated by K-Framework alongside a simulation with code produced using the said semantics. Furthermore, the paper proposes a clocking strategy for systems built on the framework, potential conflict resolution designs and their trade-offs, adherence to CAP Theorem and verification of the atomic semantic using Fischer’s Protocol. A negative test-case experiment is also included to verify the correctness of the atomic semantic.

In times of rapid urban expansion, urgent demand for housing and simultaneously efforts to minimise the use of urban land are competing objectives. The concept of large housing estates (LHE) has therefore regained interest. This resurgence raises questions about the living conditions within these historically stigmatised complexes. While liveability studies often rely on surveys, we present a globally applicable quantitative approach to assess liveability along the dimensions of walkability, accessibility and built-up morphology. Using geospatial data and a delineation framework based on walking distances, we identify disparities in liveability. We identified three different planning paradigms for LHEs in Germany: the ‘structured and low-dense’ type, the ‘urbanity by density’ type in Western Germany and the ‘socialistic city’ type in Eastern Germany. Our analysis reveals significant differences in accessibility and morphology, that can be attributed to the historical guiding principles. Walkability, in contrast, seems to be influenced more by environmental elements (rivers, forests) and artificial barriers (railway lines, motorways) than by planning paradigms. The ‘structured’ type is characterised by monofunctionality, limited access to urban infrastructure, low building density, but a high proportion of green spaces. The ‘urbanity by density’ type has significantly higher building densities, better accessibility, but less urban green. The ‘socialistic’ urban type could not be clearly categorised, but seems to be a mixture of the other two types. In our analysis, the ‘urbanity by density’ typology predominantly performed the best and, as such, emerges as the most liveable typology, potentially serving as a guiding model for future construction projects.

Blockages in sewers and drains often result in overflows and flooding that cause significant environmental pollution and public health risks, particularly in hospitals, where the consequences can be catastrophic. Due to their low “visibility”, sewers and drains are inherently difficult to monitor and maintain, resulting in a reactive management approach whereby maintenance or repair is carried out only after a system failure has occurred. This paper investigates the feasibility of applying the reflected wave technique, a unique sonar-like monitoring approach capable of identifying changes in the geometry of closed-pipe conduits, as a means of proactive system monitoring. The technique uses a 10 Hz sinusoidal air pressure wave which is transmitted into the drainpipe. When the pressure wave encounters a system boundary, a reflection is generated which alters the measured test pressure response. Analysis of the reflections generated by a changed system boundary, such as the formation of a blockage, can provide information related to the location of that boundary within the system. An experimental setup was developed to simulate a horizontal drain using standard pipework of 100 mm diameter and 70 m length. The technique was able to detect applied blockages with cross-sectional coverage of 30% and 75%, and lengths ranging from 30 mm to 3000 mm. Accuracy was improved when the pressure sensor was positioned closer to the blockage. When the sensor was 3.4 m from the blockage, location estimates were very accurate (−2% to 3% error). At a 14 m distance from the blockage, the error increased to between 4% and 33%. The accuracy of blockage detection and location improved with increasing blockage cross-sectional area and length. Overall, the reflected wave technique could provide a potentially continuous monitoring solution for blockage detection in sewers and drains.

This paper presents a physics-informed deep learning approach for predicting the replicator equation, allowing accurate forecasting of population dynamics. This methodological innovation allows us to derive governing differential or difference equations for systems that lack explicit mathematical models. We used the SINDy model first introduced by Fasel, Kaiser, Kutz, Brunton, and Brunt 2016a to get the replicator equation, which will significantly advance our understanding of evolutionary biology, economic systems, and social dynamics. By refining predictive models across multiple disciplines, including ecology, social structures, and moral behaviours, our work offers new insights into the complex interplay of variables shaping evolutionary outcomes in dynamic systems

Abstract Extremely high land surface temperatures affect soil ecological processes, alter land-atmosphere interactions, and may limit some forms of life. Extreme surface temperature hotspots are presently identified using satellite observations or deduced from complex Earth system models. We introduce a simple, yet physically based analytical approach that incorporates salient land characteristics and atmospheric conditions to globally identify locations of extreme surface temperatures and their upper bounds. We then provide a predictive tool for delineating the spatial extent of land hotspots at the limits to biological adaptability. The model is in good agreement with satellite observations showing that temperature hotspots are associated with high radiation and low wind speed and occur primarily in Middle East and North Africa, with maximum temperatures exceeding 85°C during the study period from 2005 to 2020. We observed an increasing trend in maximum surface temperatures at a rate of 0.17°C/decade. The model allows quantifying how upper bounds of extreme temperatures can increase in a warming climate in the future for which we do not have satellite observations and offers new insights on potential impacts of future warming on limits to plant growth and biological adaptability.

Ist die Kategorie Organisation tatsächlich so unproblematisch, wie der organisationstheoretische Mainstream meint? Gibt es die Gebilde überhaupt, die mit diesem Begriff beschrieben werden sollen? Oder handelt es sich im Gegenteil um Erfindungen, in die Welt gesetzt von denjenigen, die Organisationstheorie betreiben? Eine andere Position lautet: Organisationen sind reale soziale Formationen, die sich allerdings der performativen Wirkung von Fiktionen und insbesondere Mythen verdanken. Ausgehend von einem Begriff des Mythos, der diesen nicht auf eine rational leicht zu entlarvende Lüge reduziert, geht der vorliegende Band den Mythen des Organisierens und der Organisationen nach.

High-quality data on the investigated area is crucial for modelling urban building energy demands, but its availability is often insufficient. We present an approach to acquire (i) building geometries, (ii) their ages, and (iii) their retrofit states. It consists of creating a 3D model from aerial imagery, determining building ages through machine learning, generating a simulation model based on open-source tools, and assessing retrofit states by comparing simulated temperatures with infrared thermography (IRT) measurements. The demonstration on a case study quarter in Berlin shows that heat demand results are comparable to other tools. Using machine learning is already wellsuited to close knowledge gaps regarding building ages. However, retrofit state assessment using IRT was unsatisfactory due to insufficient measurement accuracy and is envisaged for improvement in future research, along with a validation of the approach.

Urban energy consumption is expected to continuously increase alongside rapid urbanization. The building sector represents a key area for curbing the consumption trend and reducing energy-related emissions by adopting energy efficiency strategies. Building age acts as a proxy for building insulation properties and is an important parameter for energy models that facilitate decision making. The present study explores the potential of predicting residential building age at a large geographical scale from open spatial data sources in eight municipalities in the German federal state of North-Rhine Westphalia. The proposed framework combines building attributes with street and block metrics as classification features in a Random Forest model. Results show that the addition of urban fabric metrics improves the accuracy of building age prediction in specific training scenarios. Furthermore, the findings highlight the way in which the spatial disposition of training and test samples influences classification accuracy. Additionally, the paper investigates the impact of age misclassification on residential building heat demand estimation. The age classification model leads to reasonable errors in energy estimates, in various scenarios of training, which suggests that the proposed method is a promising addition to the urban energy modelling toolkit.

The report is a joined achievement of the European Blockchain Center at the IT University of Copenhagen, Fraunhofer Institute for Industrial Engineering, Confederation of Danish Industry, Statistics Denmark, and the Danish Industry Foundation and focuses on the application of blockchain technologies in different industry sectors in Denmark. The report provides a general introduction into blockchain, an analysis of clusters, a review of the comprehensive empirical study, a comparison with selected countries, scenario analyses, and finally recommendations in the conclusion.

The study of intertextuality, or how authors make artistic use of other texts in their works, has a long tradition, and has in recent years benefited from a variety of applications of digital methods. This article describes an approach for detecting the sorts of intertexts that literary scholars have found most meaningful, as embodied in the free Tesserae website http://tesserae.caset.buffalo.edu/. Tests of Tesserae Versions 1 and 2 showed that word-level n-gram matching could recall a majority of parallels identified by scholarly commentators in a benchmark set. But these versions lacked precision, so that the meaningful parallels could be found only among long lists of those that were not meaningful. The Version 3 search described here adds a second stage scoring system that sorts the found parallels by a formula accounting for word frequency and phrase density. Testing against a benchmark set of intertexts in Latin epic poetry shows that the scoring system overall succeeds in ranking parallels of greater significance more highly, allowing site users to find meaningful parallels more quickly. Users can also choose to adjust both recall and precision by focusing only on results above given score levels. As a theoretical matter, these tests establish that lemma identity, word frequency, and phrase density are important constituents of what make a phrase parallel a meaningful intertext.

The digital era promises, as did many other technological developments before it, the transformation of society: with the computer, we can transcend time, space, and politics-as-usual. In The Digital Sublime, Vincent Mosco goes beyond the usual stories of technological breakthrough and economic meltdown to explore the myths constructed around the new digital technology and why we feel compelled to believe in them. He tells us that what kept enthusiastic investors in the dotcom era bidding up stocks even after the crash had begun was not willful ignorance of the laws of economics but belief in the myth that cyberspace was opening up a new world.

A scientist friend asked Bruno Latour point-blank: “Do you believe in reality?” Taken aback by this strange query, Latour offers his meticulous response in Pandora’s Hope. It is a remarkable argument for understanding the reality of science in practical terms.

Flows of incompressible, time-independent purely viscous power-law fluids through pressure nozzle with combined axial and tangential entry are analysed. Theoretical predictions of coefficient of discharge and spray cone angle are made through an approximate analytical solution of hydrodynamics of flow inside the nozzle. In the converging section of the nozzle, the boundary layer equations have been derived with modified order approximation [O(\($\delta$\)/R)≈1, O(\($\delta$\)2/R2)≪1] of Navier-Stokes equations for a better accuracy. Smoother attainment of the free-stream condition at the edge of the boundary layer is ensured by requiring the appropriate shear rate terms, compatible with the above order analysis, to be zero. The pertinent independent input parameters which govern the flow field are the generalized Reynolds number at inlet to the nozzle based on the tangential velocity of injection \\($\$\)backslashoperatornameRe _G_i \\($\$\), the ratio of the axial-to-tangential velocity at the inlet to the nozzle VR, the flow behaviour index of the fluid n, the length-to-diameter ratio of the swirl chamber L1/D1, the spin chamber angle 2\($\alpha$\) and the orifice-to-swirl-chamber-diameter ratio D2/D1. Experiments reported in the paper corroborate the qualitative trends of analytical results.