bluuebunny/crossref_metadata_2025 huggingface dataset:
Foundations of Ghost Stability
Authors: Errasti Díez Verónica , Gaset Rifà Jordi , Staudt Georgina
Published: January 2025

The authors present a new method to analytically prove global stability in ghost‐ridden dynamical systems. The proposal encompasses all prior results and consequentially extends them. In particular, it is shown that stability can follow from a conserved quantity that is unbounded from below, contrary to expectation. Novel examples illustrate all of the results. The findings take root on a careful examination of the literature, here comprehensively reviewed for the first time. This work lays the mathematical basis for ulterior extensions to field theory and quantization, and it constitutes a gateway for inter‐disciplinary research in dynamics and integrability.
Considering ensemble spread improves rainfall forecast post‐processing
Authors: Wang Quan J. , Huang Zeqing , Robertson David E. , Schepen Andrew , Bennett James C. , Song Yong
Published: January 2025

Post‐processing is an essential step in improving rainfall forecasts from numerical weather prediction (NWP) models for hydrological prediction. While NWP models provide informative ensemble forecasts, this paper concentrates on unravelling the role of ensemble spread in rainfall forecast post‐processing. The ensemble link functions (ELFs) post‐processing method is developed by employing the log‐sinh transformation to normalise the skewed and censored rainfall data and linking the predictive distribution to the mean and spread of ensemble forecasts. We apply the ELFs and Bayesian joint probability modelling approach (BJP) to calibrate ensemble precipitation forecasts from the European Centre for Medium‐range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS). We compare ELFs to BJP, which only takes the ensemble mean as an input. While both the ELFs and BJP can reduce bias and improve reliability, we show that ELFs tends to outperform the BJP in improving forecast skill in over 50% of the cases examined. It is found that the BJP tends to overestimate forecasts for extreme events, diminishing forecast skill and that the consideration of raw ensemble spread in the ELFs contributes to reliable forecasts. The most substantial skill improvement of the ELFs over BJP is observed for a moderate level of underlying skill in the raw forecasts, typically corresponding to lead times from three to seven days. Overall, ELFs effectively use information from both the ensemble mean and spread to calibrate NWP rainfall forecasts more effectively than can be achieved when ensemble spread is ignored.
Construction of Multiple Nonpolar SF6 Nano‐Traps by Highly Stable Pyrazole‐Based MOFs for SF6 Recovery
Authors: Fan Qichen , Yao Jinze , Zhao Siyao , Wu Xingbei , Huang Jiajin , Luo Haoyuan , Xia Qibin
Published: January 2025

Sulfur hexafluoride (SF6), widely used in electric power systems, is one of the most potent greenhouse gases. Efficient separation of SF6/N2 by adsorptive separation technology based on porous materials is of great significance in the industry yet remains a daunting challenge. Herein, a novel strategy is introduced to construct unique pore channels with multiple SF6 nano‐traps by precisely selecting bipyrazole ligands to design the nonpolar surface of microporous metal−organic frameworks (MOFs), which significantly enhances the material's affinity for SF6. A series of ultra‐stable bipyrazole‐based MOFs, M(BPZ) (M═Co, Ni, Zn), are synthesized and investigated. Among these three materials, Co(BPZ) and Zn(BPZ) show excellent SF6 uptakes of 2.47 and 2.39 mmol g−1 at 298 K and 0.1 bar while Co(BPZ) exhibits the highest SF6/N2 (10/90, v/v) IAST selectivity of 748. Breakthrough experiments reveal that SF6/N2 mixtures can be efficiently separated by Co(BPZ) with a high SF6 (≥99.5 %) productivity of 46.1 L kg−1. Theoretical calculations suggest that SF6 preferably adsorbs in the channels through multiple S−F···π (pyrazole rings) van der Waals interactions. This work provides a straightforward approach for exploring adsorbents in efficient SF6/N2 separation.
Multifunctional Siloxane Additive Enabling Ultrahigh‐Nickel Lithium Battery with Long Cycle Life at 30 and 60 °C
Authors: Chen Xilong , Yu Zhili , Li Xiangjie , Sun Zhaoyu , Ma Guozheng , Li Qiyun , Ou Yingchun , Liu Yuxuan , Hu Renzong
Published: January 2025

Ultrahigh‐nickel layered oxide cathodes (≥90% nickel) possess exceptionally high discharge capacities, which can significantly improve the energy density of lithium‐ion batteries and alleviate the driving range anxiety of electric vehicles. However, the high interfacial reactivity of ultrahigh‐nickel cathodes, especially the detrimental side reactions with harmful acidic species like HF in the electrolyte, can deteriorate the battery interface and reduce the cycle life, hindering their practical application. In this study, 3‐isocyanatopropyltrimethoxysilane (PTTS‐NCO) is introduced as the electrolyte additive, which can effectively scavenge the harmful acidic species in the electrolyte and form a protective surface layer at the electrode/electrolyte interface, thereby enhancing the electrochemical performance of the battery (NCM90/Li). Specifically, the most effective battery based on the PTTS‐NCO additive can maintain 70.3% of its capacity after 500 cycles at 30 °C. Even under a high cathode loading (3.0 mAh cm−2), it can retain 86.2% of its capacity after 300 cycles, far exceeding the base battery. Furthermore, it exhibits good performance under the harsh high‐temperature environment, maintaining over 70.3% capacity retention in the NCM90/Li battery up to 350 cycles at 60 °C. This work demonstrates the great potential of multifunctional siloxane additive in lithium batteries based on ultrahigh‐nickel cathode.
Deciphering the Role of Second Metal in M‐Ni (M = Fe, Ni, and Mn) Heterobimetallic Electrocatalysts in Controlling the HAT versus Hydride Transfer Mechanism for the Dehydrogenation of Alcohols
Authors: Chauhan Chetansinh , Gupta Tarisha , Mondal Biswajit
Published: January 2025

The second 3d‐transition metal incorporation in Ni‐(oxy)hydroxide has a drastic effect on alkaline OER and alcohol dehydrogenation reactivity. While Mn incorporation suppresses the alkaline OER, it greatly improves the alcohol dehydrogenation reactivity. A complete reversal of reactivity is obtained when Fe is incorporated, which shows better performance for alkaline OER with poor alcohol dehydrogenation reactivity. The role of the second 3d‐metal is elusive due to the lack of systematic mechanistic studies. In this report, we thoroughly analyzed a series of M─Ni (M = Fe, Ni, Mn) (oxy)hydroxides derived from electrochemical activation of M‐MOF grown on nickel foam for its electrochemical activity in alkaline OER and aliphatic, benzyl alcohol dehydrogenation. With the help of pH‐dependence and kinetic isotope effect studies, the potential‐determining step (PDS) and the rate‐determining step (RDS) have been elucidated. The Hammett analysis revealed critical information about the transition state and offered insight into the hydrogen atom transfer (HAT) versus hydride transfer (HT) for alcohol dehydrogenation operative in various heterobimetallic electrocatalysts. Further, the superior alcohol dehydrogenation reactivity of NiMn catalyst for PET hydrolysate electro‐oxidation is extended to afford valuable chemicals with concomitant production of hydrogen.
Acute kidney injury and iron metabolism: A narrative review focusing on pathophysiology and therapy
Authors: Tan Xinyu , Li Man , Chen Jing , Liu Gang , Lu Zhixiang
Published: January 2025

Acute kidney injury (AKI) represents a substantial challenge to public health and is characterized by elevated occurrence and fatality rates. In the last 3 decades, the disruption of iron homeostasis and the cytotoxic effects mediated by iron have been extensively acknowledged as contributors to, as well as outcomes of, renal damage. Therefore, iron metabolism has become the focus of novel therapeutic interventions for AKI, with targeted iron metabolism strategies showing great potential. In this review, we have explored the dysregulation of iron metabolism in AKI and the AKI caused by iron metabolism disorders. We have summarized the complex mechanisms of iron metabolism in the kidney and emphasized the potential role of iron metabolism‐related metabolic pathways in the treatment and prevention of AKI. Finally, we have reviewed various strategies targeting iron metabolism for the treatment of AKI, hoping to provide more effective treatment options for AKI patients in the future.
Tissue‐Adhesive and Stiffness‐Adaptive Neural Electrodes Fabricated Through Laser‐Based Direct Patterning
Authors: Kim Jaehyon , Kim Yewon , Kim Kyoungryong , Jung Hyunjin , Seong Duhwan , Shin Mikyung , Son Donghee
Published: January 2025

Recently, implantable devices for treating peripheral nerve disorders have demonstrated significant potential as neuroprosthetics for diagnostics and electrical stimulation. However, the mechanical mismatch between these devices and nerves frequently results in tissue damage and performance degradation. Although advances are made in stretchable electrodes, challenges, including complex patterning techniques and unstable performance, persist. Herein, an efficient method for developing a tissue‐adhesive, stiffness‐adaptive peripheral neural interface (TA‐SA‐PNI) is presented employing mechanically and electrically stable ultrathin conductive micro/nanomembrane bilayer (UC‐MNB) electrodes. A direct laser‐patterning technique is utilized to anchor the UC‐MNB, comprising a conductive Cu micromembrane encapsulated by a biocompatible Au nanomembrane, onto a tough self‐healing polymer (T‐SHP) substrate using the thermoplastic properties of T‐SHP. The UC‐MNB with a wavy structure exhibited strain‐insensitive performance under strains of up to 60%. Furthermore, its dynamic stress‐relaxation properties enable stiffness adaptation, potentially minimizing chronic nerve compression. Finally, the phenylboronic acid‐conjugated alginate (Alg‐BA) adhesive layer offers stable tissue adhesion and ionic conductivity, optimizing the TA‐SA‐PNI for seamless integration into neural applications. Leveraging these advantages, in vivo demonstrations of bidirectional neural pathways are successfully conducted, featuring stable measurements of sensory neural signals and feedback electrical stimulation of the sciatic nerves of rats.
Tunable NiSe‐Ni3Se2 Heterojunction for Energy‐Efficient Hydrogen Production by Coupling Urea Degradation
Authors: Yin Ruilian , Wang Zhiwei , Zhang Jin , Liu Wenxian , He Jia , Hu Guangzhi , Liu Xijun
Published: January 2025

Urea‐assisted water splitting is a promising energy‐saving hydrogen (H2) production technology. However, its practical application is hindered by the lack of high‐performance bifunctional catalysts for urea oxidation reaction (UOR) and hydrogen evolution reaction (HER). Herein, a heterostructured catalyst comprising highly active NiSe and Ni3Se2, along with a conductive graphene‐coated nickel foam skeleton (NiSe‐Ni3Se2/GNF) is reported. The heterostructured NiSe‐Ni3Se2 originates from the in situ selenization of graphene‐coated nickel foam, allowing for careful regulation of the NiSe to Ni3Se2 ratio by simply adjusting the calcination temperature. Theoretical calculations of the charge transfer between NiSe and Ni3Se2 components can optimize the reaction pathways and reduce the corresponding energy barriers. Accordingly, the designed catalyst exhibits excellent UOR and HER activity and stability. Furthermore, the NiSe‐Ni3Se2/GNF‐based UOR‐HER electrolyzer requires only 1.54 V to achieve a current density of 50 mA cm−2, which is lower than many recent reports and much lower than 1.83 V of NiSe‐Ni3Se2/GNF‐based OER‐HER electrolyzers. Moreover, the UOR‐HER electrolyzer exhibited negligible cell voltage variation during a 28‐h stability test, indicating satisfactory stability, which provides a new viable paradigm for energy‐saving H2 production.
3D‐Printed Hemispherical Capillaries for Solar Water Evaporation
Authors: Liu Xinzhe , Liu Qingyuan , Liu Zheng , Liu Guohua
Published: January 2025

Solar interfacial evaporation offers a sustainable method to extract fresh water from seawater, but is often constrained by salt accumulation. A 3D‐printed hemispherical solar evaporator with integrated open capillary grooves on its surface is introduced to enhance water transport and evaporation. This design creates a vertically nonuniform liquid film, initiating Marangoni flow to facilitate continuous desalination. The evaporator achieves high evaporation rates of 2.768 kg m−2 h−1 for pure water and 2.646 kg m−2 h−1 for 25 wt% saline water upon one‐sun solar irradiation. This high performance is attributed to the microporous structure of the capillaries, which supports cluster‐based water evaporation and benefits from the lower evaporation enthalpy of seawater. After 15 h of operation, the hemispherical capillary design promotes localized salt crystallization at low concentrations and forms a thin salt film at higher concentrations, surprisingly increasing the evaporation rate. Moreover, the structure effectively removes pollutants, including heavy metals and organic contaminants from wastewater and seawater. This new evaporator could significantly impact wastewater treatment, desalination, and other evaporative applications.
Hybrid Neural Network Methods for the Detection of Credit Card Fraud
Authors: Al‐Khasawneh Mahmoud Ahmad , Faheem Muhammad , Alsekait Deema Mohammed , Abubakar Adamu , Issa Ghassan F.
Published: January 2025

The purpose of research on fraud detection is to discover methods that are superior and more effective in detecting fraudulent activity. Because of the difficulties that are associated with single models, this research proposes a hybrid model neural network be utilized in order to overcome such difficulties. A very effective binary classification system is produced as a result of the multimodal neural network (MNN) model, which combines continuous and categorical data channels. The hybrid model neural network model demonstrates some extraordinary effectiveness in detecting cases of credit card fraud, according to the results of experimental investigation. The findings on accuracy, precision, recall, and area under the curve (AUC) give evidence of its robustness and reliability in identifying fraudulent transactions while simultaneously reducing the number of false positives and false negatives. In particular, it proved that the performance of the model is exceptional, with a test accuracy of 99.47%, precision of 99.82%, recall of 97.87%, and an AUC of 98.99%. Furthermore, these findings provide evidence of a robust model that is capable of effectively detecting fraudulent transactions with a high degree of accuracy, while simultaneously lowering the occurrence of both false positives and false negatives. Consequently, this guarantees a fraud detection system that is dependable and effective.
Evaluation of Degradation Degree on Silicone Rubber by Using Surface Discharge
Authors: Khaing May Thin , Hirose Nonoka , Miyake Takuma , Sakoda Tatsuya , Goto Shigehiko , Anjiki Tomikazu , Chiba Tomoki
Published: January 2025

Silicone rubber (SiR) insulators in outdoor may be degraded owing to multiple environmental stresses such as ultraviolet (UV) rays, high temperature and pollution adhesion. Evaluation of the degradation degree of SiR can contribute to the long‐term maintenance of SiR insulators. We proposed a novel technique to grasp the degradation degree of SiR. The surface discharge (SD) on the SiR surface temporarily decreased the surface hydrophobicity, and then the hydrophobicity recovery time was evaluated. The SD treatments were performed on SiR specimens cut out from unused, 10 and 20‐year‐aged SiR insulators, and the treatment time was from 5 to 25 s. After each SD treatment, the contact angle was evaluated at intervals of 10 min. As a result, it was found that the contact angle recovery time increases with the increase of SD treatment time. Also, the contact angle recovery times on 10 and 20‐year‐aged SiR specimens were longer than that on an unused SiR specimen, i.e. the contact angle recovery time after the SD treatment is useful for investigating the degradation degree. © 2025 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.
Benzene tricarboxylic acid for synthesis of the ZrO2:Er3+,Yb3+ nanoparticles in cubic phase
Authors: Giang Lam Thi Kieu , Vu Nguyen , Chinh Vu Duc , Linh Pham Hoai , Nghiem Vu Thi , Agnieszka Opalińska , Piotrowski Wojciech M. , Marciniak Łukasz
Published: January 2025

The cubic structure of nanocrystalline ZrO2 co‐doped with Er3+,Yb3+ ions was synthesized using the zirconium metal‐organic framework (Zr‐BTC:Er3+,Yb3+) as a precursor after an annealing process at temperatures ranging from 400 to 1000 °C for 1 h. The morphology characterization confirmed 700 °C as the optimal temperature for calcination. XRD, HRTEM and SAED techniques unambiguously confirmed the formation of a cubic structure of ZrO2. The average grain size of the obtained ZrO2:Er3+,Yb3+ upconversion nanoparticles was estimated at 12 ± 1 nm using Scherrer's equation, TEM and HRTEM images. Moreover, spectroscopic measurements confirmed the stabilization of Yb3+ and Er3+ ions in the crystal structure of ZrO2, presenting a dominant red emission band at 665 nm and a less intense green band at 550 nm associated with 4F9/2→4I15/2 and 2H11/2, 4S3/2→4I15/2 electronic transitions of Er3+ ions, respectively.
Impacts of rapid urbanization on long‐term water quality of the peripheral River of Dhaka, Bangladesh
Authors: Miah Osman , Anik Amit Hasan , Sorker Raihan , Parvin Fahmida , Shammi Mashura , Tareq Shafi M.
Published: January 2025

This study was carried out to determine the current state of the physicochemical water quality parameters and the effects of urbanization over 50 years in the peripheral rivers by using primary and secondary data adjacent to Dhaka city. These rivers and waterways had DO levels much below the recommended standard of Bangladesh, and occasionally, they even approached 0. This suggests that the water in these rivers is highly polluted and unfit for aquatic life. For the most part, high rates of pollution also contribute to high BOD readings. Besides, the weighted arithmetic method discovered that the urban rivers have deficient water quality, which requires immediate attention. Compared to the seasonal variations, the water quality is worse in the dry season compared to the wet season. Among all the rivers, the lowest WQI found was 11.89 in the wet season and 123.65 in the dry season. Moreover, the Heavy Metal Pollution Index (HPI) calculation was done, with data from 1 to 3797 indicating that most heavy metal data sets are unsuitable for drinking and household uses. The current study found that built‐up areas have grown 288%, and the water bodies have declined by 60% over the last 30 years. This study shows that the quality of peripheral river water in Dhaka city hinders the objectives of the SDG 6 Goal: Clean Water and Sanitation. Revitalizing the water supply requires the attention of the city authorities.

Practitioner Points

Rapid urbanization has made Dhaka one of the least habitable cities, with industrial growth contributing significantly to pollution.

DO levels are far below than Bangladesh's standards, sometimes approaching zero, making the water unfit for aquatic life.

The study reveals a decline in water quality, especially during the dry season, and WQI indicates extremely low standards.

Built‐up areas have increased by 288%, while water bodies have decreased by 60% over the past 30 years.
DS-HECK: double-lasso estimation of Heckman selection model
Authors: Hirukawa Masayuki , Liu Di , Murtazashvili Irina , Prokhorov Artem
Published: January 2025

We extend the Heckman (1979) sample selection model by allowing for a large number of controls that are selected using lasso under a sparsity scenario. The standard lasso estimation is known to under-select causing an omitted variable bias in addition to the sample selection bias. We outline the required adjustments needed to restore consistency of lasso-based estimation and inference for vector-valued parameters of interest in such models. The adjustments include double lasso for both the selection equation and main equation and a correction of the variance matrix. We also connect the estimator with results on redundancy of moment conditions. We demonstrate the effect of the adjustments using simulations and we investigate the determinants of female labor market participation and earnings in the US using the new approach. The paper comes with , a dedicated Stata command for estimating double-selection Heckman models.
Identification and estimation of categorical random coefficient models
Authors: Gao Zhan , Pesaran M. Hashem
Published: January 2025

This paper proposes a linear categorical random coefficient model, in which the random coefficients follow parametric categorical distributions. The distributional parameters are identified based on a linear recurrence structure of moments of the random coefficients. A generalized method of moments estimation procedure is proposed, also employed by Peter Schmidt and his coauthors to address heterogeneity in time effects in panel data models. Using Monte Carlo simulations, we find that moments of the random coefficients can be estimated reasonably accurately, but large samples are required for the estimation of the parameters of the underlying categorical distribution. The utility of the proposed estimator is illustrated by estimating the distribution of returns to education in the USA by gender and educational levels. We find that rising heterogeneity between educational groups is mainly due to the increasing returns to education for those with postsecondary education, whereas within-group heterogeneity has been rising mostly in the case of individuals with high school or less education.
Testing for correlation between the regressors and factor loadings in heterogeneous panels with interactive effects
Authors: Kapetanios George , Serlenga Laura , Shin Yongcheol
Published: January 2025

A large literature on modelling cross-section dependence in panels has been developed through interactive effects. However, there are areas where research has not really caught on yet. One such area is the one concerned with whether the regressors are correlated with factor loadings or not. This is an important issue because if the regressors are uncorrelated with loadings, we can simply use the consistent two-way fixed effects (FE) estimator without employing any more sophisticated econometric methods such as the principal component (PC) or the common correlated effects estimators. We explore this issue, which has received surprisingly little attention and propose a Hausman-type test to address the matter. Further, we develop two nonparametric variance estimators for the FE and PC estimators as well as their difference, that are robust to the presence of heteroscedasticity, autocorrelation and slope heterogeneity. Under the null hypothesis of no correlation between the regressors and loadings the proposed test follows the $$ {\chi}^2 $$

χ
2

distribution asymptotically. Monte Carlo simulation results confirm satisfactory size and power performance of the test even in small samples. Finally, we provide extensive empirical evidence in favour of uncorrelated factor loadings. In this situation, the FE estimator would provide a simple and robust estimation strategy which is invariant to nontrivial computational issues associated with the PC estimator.
Circular Bio-based Walls: Applications and Challenges
Authors: Cascione Valeria , Dams Barrie , Roberts Matt , Shea Andrew , Maskell Dan , Allen Stephen , Walker Pete , Emmitt Stephen
Published: January 2025

Circular economy principles can be applied to the construction sector to reduce use of resources, energy consumption and wastes. Bio-based construction materials are particularly suitable to circular building design. Advantages of bio-based materials include: (1) a renewable supply chain, (2) often fast-growing, (3) recyclable or used as fertilisers/compost and (4) can sequester carbon. In this paper, the design of three circular bio-based wall panels is presented. The three panels were designed to be disassembled, and innovative bio-based materials, such as mycelium, sheep’s wool and cellulose were implemented in the walls. The wall assemblies were tested in a large environmental chamber to assess whether the panels achieved high insulating performances. Monitoring results showed that the three panels have excellent thermal properties. In parallel, life cycle assessment (LCA) of the bio-based construction materials applied in the three panels was undertaken to assess the sustainability and circularity of the selected materials. LCA results showed that some of the materials, such as sheep’s wool and flax, do have a low carbon footprint. However, there are uncertainties around the carbon footprint of other bio-based materials (e.g. fungi-based products), as information on the manufacturing process and associated emissions are not always available. This paper provides an overview of the applicability, advantages and challenges of innovative and sustainable technologies in buildings to achieve net-zero targets and to apply circular economy model of construction in buildings.
Structural Response of CLT Bridge Decks to Heavy Vehicle Loads: A Serviceability Evaluation
Authors: Lindersson Emil , Askari Mohammed , Vakili Amirhosein , Dahlberg Justin , Kioumarsi Mahdi , Shafei Behrouz
Published: January 2025

Timber is widely recognized as a construction material of choice, owing to its numerous advantages, including its sustainability and abundance in large parts of the world. Although timber is frequently employed by the construction industry for buildings, its usage in modern bridge structures has remained limited. This research investigates the structural performance of cross-laminated timber (CLT) decks for bridge applications. For this purpose, CLT deck made of Douglas Fir North was fabricated to full-scale but with some reduced width dimensions. The deck was then tested under static and fatigue loading conditions. The experiments evaluated various structural response features, including the bending stiffness, interlaminar properties between the panels, and elongation characteristics from the applied vertical forces, representing heavy vehicular loads equivalent to the design loads expected on a typical short-span bridge. The results demonstrate the promising performance of CLT decks, exhibiting excellent structural performance compared to design standards. Overall, this research addresses a knowledge gap by providing valuable information for CLT bridge deck design and optimization, addressing the lack of modeling guides, and offering recommendations to meet standard requirements. Moreover, it emphasizes the environmental benefits of using timber sourced from sustainable sources, which is feasible in areas that have an abundance of such resources.
Exploring the Predictive Performance of Simple Regression Models and ANN in 2D Truss Analysis
Authors: Plevris Vagelis , Rios Alejandro Jiménez , Ebead Usama A.
Published: January 2025

This research investigates the performance of various regression models in predicting critical structural parameters within a plane truss model. The study encompasses linear, second- and third-degree polynomial, and artificial neural network (ANN) regression models, which are evaluated for their accuracy in estimating the maximum displacement, maximum (tensile) stress, and minimum (compressive) stress of the truss under specific loading conditions. The findings unequivocally establish the superiority of the ANN model, showcasing its ability to capture complex nonlinear relationships within the data. Moreover, the research explores the influence of model complexity, demonstrating that the transition from simpler to more intricate models enhances predictive performance. The implications of this study extend to diverse engineering applications, offering insights into the selection of appropriate regression models for structural analysis and design. Beyond improved predictive accuracy, the ANN’s predictions provide potential for reducing computational demands, making them valuable tools in structural optimization and similar contexts. However, the study underscores the importance of cautious interpretation, as certain scenarios may yield outlier predictions. Overall, this research contributes to the understanding of regression modeling in engineering and provides a foundation for informed decision-making in structural analysis and design.
Data-Driven Decision-Making for Road Maintenance in Norway
Authors: Giudici Henri
Published: January 2025

Rapid increase in urbanization and mobility demand are rising concerns for the development of sustainable urban areas. Transport infrastructures play a major role in this regard by promoting well-being, social inclusivity, and economic growth. This is true also for road infrastructure. Over the life cycle of a road infrastructure, the operational stage is the longest one and requires continuous maintenance and/or rehabilitation activities to keep the road operating at a satisfactory level of service. Data-driven decisions are essential to assess and evaluate the status of the road network. However, the data-driven decision-making process is not trivial but rather challenging due to the need of balancing multiple road qualities simultaneously. This chapter presents an overview of the road maintenance decision-making process using the Norwegian case as a case study. After presenting a background on monitoring systems and pavement management systems, this chapter focuses on the data-driven decision-making process of the Norwegian national road network. Finally, this chapter discusses the opportunities to better align this decision-making process with the Norwegian transport plan.
Sustainability Potentials of the Precast Industry in Kenya
Authors: Marangu Joseph Mwiti , Nyabuto Andrew Onderi , Pfeiffer Thomas , Kruschwitz Sabine , Völker Christoph , Schmidt Wolfram
Published: January 2025

Kenya is overly affected by the consequences of climate change and struggling to find ways to balance mitigation with the urgent need to meet the country’s infrastructure and housing needs. Traditional concreting methods, such as onsite mixing and manual compaction, are slow, material, water, and labor-intensive. The precast industry therefore offers a competitive alternative in terms of cost and environmental impact. When ordinary Portland cement is used, it is responsible for 80–90% of the carbon footprint of concrete. Hence, there is urgent need to minimize carbon emissions by using supplementary cementitious materials (SCMs) in concrete construction. Since cement factories are mostly located around the city of Nairobi, in other regions, the price of cement increases with transport distance. Precast concrete construction could become a lever for both lower prices and carbon emissions. Clinker reduction can take place at the cement plant or concrete mixing plant. Blending in the cement factory can produce more robust binder qualities but is limited to large SCM supply streams. Blending at the precast plant allows for tailored, smaller, local supply streams from industrial and agricultural by-products. The paper discusses the potential of using artificial intelligence to merge multiple small heterogeneous feed streams from renewable and recyclable resources into large homogeneous feed streams, with a particular focus on the use in precast concrete processing.
Construction Industry and the Circular Economy: A Systems Analysis
Authors: Sheen Raymond L.
Published: January 2025

The building construction industry is an old industry with entrenched behaviors and interaction patterns. The European Union (EU) published a study analyzing these behaviors and measuring the application of circular economy to the construction industry in June 2023. This study included a diagram describing the construction industry as a system, but it did not include all elements or fully analyze the system. The discipline of systems thinking is a dynamic analysis that integrates societal forces with industry dynamics to provide a comprehensive description of behaviors within an industry. This study builds on the EU report and creates a causal loop diagram for the construction industry that includes societal and industrial environmental elements. This diagram is analyzed to identify the reinforcing and balancing loops that explain dynamic system behavior and sources of resistance to change. In addition, potentially dysfunctional elements of the system are identified. The study also assesses the recommended changes from the EU report to determine their likely impact on system performance and identifies additional leverage points that should be considered.
Preliminary Environmental Assessment of Ultra-High-Performance Concrete Mixtures
Authors: Farahzadi Leila , Bozorgmehr Nia Saeed , Shafei Behrouz , Kioumarsi Mahdi
Published: January 2025

Ultra-high-performance concrete (UHPC) is well known for its exceptional strength and durability in modern construction and bridges. Despite its advantages, traditional UHPC mixes with high cement content can negatively affect the environment through CO2 emissions. This study aims to investigate using low-impact supplementary cementitious materials (SCMs) such as ground granulated blast furnace (GGBF) slag, fly ash, and silica fume as replacements for cement in different ratios in UHPC compositions. A life cycle assessment (LCA) has been conducted to evaluate the environmental impact of these innovative UHPC compositions. The evaluation considers critical variables, including resource allocation, energy sources, raw material procurement distances, and manufacturing processes. Using SCMs in UHPC formulas helps lessen the impact of global warming and aids in mitigating climate change. These results highlight the importance of using new material combinations to promote sustainability in construction, showing ways to adopt more environment-friendly solutions and creating a path toward a more sustainable future in concrete production.
Marine-Based Photocatalytic Protection of Building Envelopes on Behalf of Climate Change
Authors: Bersch Jéssica Deise , Dias Ana Paula Soares , Dal Molin Denise , Masuero Angela Borges , Flores-Colen Inês
Published: January 2025

Photocatalysis in building envelopes can reduce air pollution, further providing surfaces with antimicrobial and self-cleaning effects. However, conventional photocatalysts have drawbacks, like environmentally unfriendly industrial production processes, UV-restricted light absorption, and human health concerns. So, this chapter reviewed photocatalysts synthesized following a green route in several research fields, relying on the wide availability of sea waste. The final goal was to assess if the construction sector already encompasses the topic and provide experimental paths to preserve renders with marine-based photocatalysts and enhance their resilience under climate change. The final sample had 64 papers, in which algae, shells, fish waste, and other marine materials were bio-sources. Indoor air pollution was the closest topic to buildings, addressed by three papers but without direct applications, and no papers have tested bio-photocatalysts in façades. Titanium, zinc, and silver were the most common metals combined with the biomaterials. A lack of toxicity and life cycle assessments prevented a comprehensive environmental discussion.
Importance of Optimally Combining Binder Types and Rebar Cover in Reducing Lifetime CO2 Emissions in RC Structures
Authors: Hasnat Sakib , Manzur Tanvir
Published: January 2025

The global imperative to transition towards sustainable and energy-efficient practices has brought to the forefront the need for innovative solutions and strategies within the construction industry, a major contributor to energy-related emissions. With over a third of global emissions stemming from the built environment, the construction sector, particularly in extreme exposures, faces unique challenges. Reinforced Concrete (RC) structures in chloride-laden environments are especially vulnerable to rapid deterioration. The integration of binders such as fly ash and slag, as well as blended cements, has been suggested in international and local codes as a relief to this problem. Despite these preventive strategies, insufficient concrete cover often undermines these efforts, resulting in severe degradation of RC structures in regions like Bangladesh where performance-based rebar cover design is not available in local codes. Once an RC structure reaches a limit state of spalling due to rebar corrosion, it often necessitates concrete patchworks to ensure continued service. However, such patchworks are often not only expensive but also energy intensive due to further utilization of concrete, resulting higher-than-anticipated lifetime CO2 emissions. This study shows the effectiveness of concrete cover as a strategy in reducing the carbon footprint of marine RC construction from the perspective of Bangladesh. Few commonly practiced concrete mixes in Bangladesh have been investigated for durability parameters, exploring the integration of environmentally friendly supplementary binders such as fly ash and slag. To assess the impact of various rebar covers in combination with binder types on the lifecycle CO2 emission of RC structures, a probabilistic approach utilizing Monte Carlo Simulation is employed. This allowed for a comprehensive evaluation of the service life of structures built with different mixes, emphasizing the critical role of concrete cover practices in reducing the frequency of repair works and associated energy-intensive CO2 emissions.
Misconceptions Around Strength Requirements for Concrete Repair Materials and Related Sustainability Issues
Authors: Jarratt Nicholas , Beushausen Hans
Published: January 2025

Concrete repair and rehabilitation are vital disciplines in structural and civil engineering, given the age of concrete infrastructure and the need to extend its service life. Most repair projects involve removing deteriorated or damaged concrete, followed by applying a patch repair mortar or bonded overlay. These repairs are typically done with proprietary repair materials of very high strength exceeding 40 MPa, which is related to the general misconception that the high strength of cementitious materials correlates with high quality and structural contribution. However, the performance of concrete repairs deteriorates with the increasing strength of the repair material, which is related to an increasing tendency to crack and debond. Furthermore, repair patches commonly do not contribute to the load-bearing behaviour of the structure, mainly because of creep and shrinkage of the repair mortar. This paper discusses common misconceptions around the ‘structural repair’ of concrete members and the related adverse effects regarding sustainability costs. Recommendations for rational and more sustainable repair approaches are presented.
Review of South African Waste Management Practices and Their Integration into the Construction Industry
Authors: Gamieldien Areej , Beushausen Hans , Alexander Mark
Published: January 2025

Construction and demolition waste (CDW) is defined as non-hazardous waste produced during the construction, repair and rehabilitation, or demolition of infrastructure. While only 19% of the CDW produced in South Africa has been reported to be diverted annually, during the same period, up to 40% of the CDW produced in the Western Cape province of South Africa was beneficiated to be reused or recycled. This discrepancy is due to a shift in local government legislation and implementation thereof which, in turn, has encouraged a change in the behaviours of waste management and built environment professionals. This paper aims to review and contrast the waste management legislation and policies of South African local and national governments, as well as the waste management practices used at landfills and recycling facilities, and the quality and uses of materials produced at these facilities from CDW in various parts of the country.
Energy Efficiency Through Building Renovation: A Study of Challenges and Solutions
Authors: Moradi Sina , Hirvonen Janne , Lastovets Natalia , Sormunen Piia
Published: January 2025

The realization of energy efficiency targets in Europe requires renovation of 30 million buildings by 2050. Compared to new building constructions, there is currently very limited research-based knowledge concerning the challenges and solutions of achieving energy efficiency in renovation through the lens of the project delivery process. Hence, this study aims to fill this knowledge gap through a qualitative study, involving project professionals representing clients, designers, general contractors, building services contractors, and maintenance experts. To do so, 21 semi-structured interviews were conducted, and the extracted data were analyzed through thematic and content analysis methods. The findings reveal that high investment cost and an uncertain payback period for replacing the old energy system together with insufficient space for new building services systems and building protection issues for façade renovation seem to be the most critical challenges. Regarding the enablers, the interviewees frequently mentioned a competent maintenance workforce, practice-oriented training and education for maintenance and operation staff, and detailed as well as purposeful measurement/metering of energy consumption for achieving energy efficiency in building renovation projects. The findings highlight the significance of investing in people and technological solutions for realizing energy efficiency through building renovation.
Urban Heat Islands in the Urban Built Environment: Quantifying the Spatial Patterns of UHIs Intensity in Oslo, Norway, Using High-Resolution Crowdsourced Weather Observations
Authors: Badach Joanna , Coelho Guilherme B. A. , Kraniotis Dimitrios , Schild Peter
Published: January 2025

Urban heat islands (UHIs) in the built environment are becoming alarmingly severe, calling for urgent climate change mitigation measures. Common data collection and data-driven analysis protocols are needed to efficiently study this phenomenon across different urban areas. The emerging low-cost sensing systems and weather data crowdsourcing are showing a great potential to support these efforts. This study explores the spatial patterns of UHIs in the city of Oslo, Norway, as similar studies in northern European cities are still too scarce. It leverages the available weather data from municipal stations and crowdsourced weather observations with high spatial resolution (over 2800 stations in the area) to characterize the phenomenon at city scale. The results show that Oslo is affected by UHIs, with its intensity reaching up to 5.5° in some districts. They also suggest that in particular conditions the spatial distribution of UHIs does not always follow the typical pattern, i.e., higher temperatures in downtown and more urbanized areas, and lower temperatures in less dense areas with more open and green spaces. Occasional negative UHIs intensity values were also captured. These effects may be the result of the strong influence of weather phenomena and topography. The findings in this study indicate the need for careful consideration of the underlying local conditions to better understand UHIs drivers and develop more targeted urban planning policies and mitigation strategies. Therefore, future studies should delve into the links between UHIs intensity and urban form characteristics.
The Effect of Student Active Learning on Awareness of Students on Environmental Impacts of Material Selection for Building Application: A Case Study
Authors: Baghban Mohammad Hajmohammadian
Published: January 2025

This study presents an investigation on implementing student active learning in a civil engineering course dealing with concrete as a building material. The primary objective was to enhance student engagement and learning outcomes through the integration of a variety of activities. A key anticipated learning outcome of this course was an understanding of sustainability issues, including the greenhouse gas emissions associated with the materials. Increasing student awareness of the environmental impacts associated with material selection for building applications can empower future experts to make informed choices that contribute to sustainability and net-zero construction. In this paper, the performance of the students in the course after implementing flipped classroom and selected student active learning methods with a focus on student awareness on consequences and environmental impacts of choice of the material is discussed. Selection and modification of the research methods were conducted by considering existing literature, own experience, communication with colleagues, and students’ feedback. The main activities include multiple choice questions before attending the physical classroom, laboratory-based project assignments with pre-recorded video guidelines, as well as quizzes and discussions during the physical classroom by using a digital learning platform. The learning outcomes were assessed by collecting the feedback from student activities during the course, as well as project report and the final exam. The results show that the selected student active learning approaches enhanced student motivation and their reflection on learning outcomes in the course. The student’s reflection on the environmental impacts of the materials and the way to reduce them was significantly improved due to conducting a lab-based project as a course assignment as well as the planned discussion arrangements.
Rural Education, Agroecology, and Environmental Know-How
Authors: Bricca Lucas
Published: January 2025

This chapter details the environmental education articles of the 2022 constitutional text in relation to a community garden initiative in the Province of Los Andes in central Chile. I explore how the text’s educational framework aimed to institutionalize local knowledge networks by supporting diverse learning environments, participatory education, and tying education to holistic social outcomes. I examine the kinds of education and knowledge that the constitutional text articulates, and the relevance of these notions for agroecology.
Comparative analysis of adenosine 1 receptor expression and function in hippocampal and hypothalamic neurons
Authors: Wegmann Lea , Haas Helmut L. , Sergeeva Olga A.
Published: January 2025

Background

Adenosine, an ATP degradation product, is a sleep pressure factor. The adenosine 1 receptor (A1R) reports sleep need. Histaminergic neurons (HN) of the tuberomamillary nucleus (TMN) fire exclusively during wakefulness and promote arousal. All of them express GABAA receptors and are inhibited by GABA. Does adenosine contribute to their silencing?

Subjects and treatment

Responses to adenosine were studied in mouse brain slices and primary dissociated cultures. For HN identification single-cell (sc)RT-PCR, reporter protein and pharmacology were used. Hippocampal Dentate Gyrus granular layer cells (DGgc) were studied in parallel.

Methods

Firing frequency was recorded in patch-clamp configuration or by microelectrode arrays. A1R-expression was studied by scRT-PCR and semiquantitative PCR.

Results

Most DGgc were inhibited through A1R, detected with scRT-PCR in 7 out of 10 PDZd2-positive DGgc; all HN were A1R negative. One HN out of 25 was inhibited by adenosine. The A1R mRNA level in the hippocampus was 6 times higher than in the caudal (posterior) hypothalamus. Response to adenosine was weaker in hypothalamic compared to hippocampal cultures.

Conclusions

Most HN are not inhibited by adenosine.