bluuebunny/crossref_metadata_2025 huggingface dataset:
Decarbonizing Conventional Building Materials for Net-Zero Emissions: A Feasibility Study in Canada
Authors: Dara Chi
Published: January 2025

Governments around the world are aiming for net-zero carbon emissions by 2050. To drive broader decarbonization efforts, the building industry is challenged by the mission to reduce embodied carbon emissions, which stem from building materials and systems. Most efforts in buildings are focused on operational energy, but up to 80% of a building’s emissions occur before use and occupancy, from extraction to construction phases. These emissions are irreversible and contribute around 11% of global carbon emissions. This study emphasizes the need to prioritize the decarbonization of conventional building materials during production using low carbon constituents to mitigate associated environmental impact. Quantitative data analysis and reviews have identified alternative low-carbon options for possible application in mix design. Examples include substituting general use (GU) Portland cement with Portland limestone cement, using supplementary cementitious materials (SCMs) to reduce cement content, and utilizing low-carbon concrete masonry units. Achieving net-zero embodied carbon requires promoting circular bio-based products and reducing conventional materials’ carbon throughout their life cycle. At material level analysis, this is possible not only by promoting the use of circular bio-based materials but also by purposefully reducing the embodied carbon of conventional building materials throughout their life cycle, as well as communicating the best practices as lessons learnt to promote broader adoption by the architecture, construction and engineering (ACE) industry. However, collaboration among designers, contractors, and manufacturers is essential. This study provides a preliminary pathway to overall decarbonization efforts, understanding that conventional, existing building materials will play a significant role in attaining the net-zero commitments of the future built environment.
Advancing Sustainable Construction Materials: Wood and Rubber Geopolymer Masonry Mix Development
Authors: Gigar Firesenay Zerabruk , Khennane Amar , Liow Jong-leng , Al-Deen Safat , Tekle Biruk Hailu , Fitzgerald Cooper J. , Basaglia Anthony , Webster Charlie
Published: January 2025

Recycling industrial waste into construction materials is becoming a fundamental strategy, offering a hopeful path toward sustainable construction practices. This study focuses on the innovative reuse of end-of-service wood and crumb rubber to develop environmentally favorable materials. Their high availability, lightweight properties, and high-energy absorption capacity make them highly suitable as additives in masonry unit production. Furthermore, using them with sustainable binding material, such as geopolymer, enhances the overall sustainability of the masonry, facilitating rapid strength development and enhancing durability while providing increased protection against fire and weathering. The study involved the development of an optimal mix design, which can potentially be used for the production of load-bearing and non-load-bearing masonry units. This was achieved by examining various proportions of wood, as well as combinations of wood and rubber, using a partial–factorial experimental design. The results show that wood-to-binder ratios ranging from 0.2 to 0.4 can potentially be used for the production of wood–geopolymer masonry units. Additionally, a ratio of 0.3 (with 50% wood and 50% rubber) was identified as potentially suitable for producing wood and rubber-based units.
Machine Learning Integration in LCA: Addressing Data Deficiencies in Embodied Carbon Assessment
Authors: Hu Ming , Wang Chaoli , Ghorbany Siavash , Yao Siyuan , Nouri Ali
Published: January 2025

Life Cycle Assessment (LCA) is an essential tool for quantifying the environmental burdens of products and processes, critical for advancing sustainability goals. Central to the effectiveness of LCA is the Life Cycle Inventory (LCI) phase, which requires reliable data to reflect the environmental footprint of products accurately. However, LCA practitioners often encounter data gaps that can compromise the assessment’s accuracy. To address this, we explore the integration of Machine Learning (ML) to enhance LCA data quality, particularly in the LCI stages B to D, which focus on product use, end-of-life, and beyond-life phases. This chapter introduces a novel framework that leverages ML to overcome LCI data challenges, emphasizing reducing the embodied carbon of construction products. We extract existing data from the Environment Product Declaration online library and apply natural language processing to interpret this unstructured data. Subsequently, we employ a random forest algorithm, a robust ensemble tree-based ML method, to refine the data analysis. We present a pilot study that validates the feasibility of our ML-enhanced framework. The incorporation of ML addresses the voluminous data in LCA. It augments the analytical capacity, thereby improving the precision and reliability of both LCI and Life Cycle Impact Assessment (LCIA) datasets. Consequently, our approach yields higher quality LCA outcomes, offering a more reliable basis for environmental impact evaluation. In summary, the successful application of ML in this research bridges the critical data gap in LCI for construction products, paving the way for a more sustainable industry through improved accuracy in environmental impact assessments and more informed decision-making in green product innovation.
Smart Technologies: New Perspectives for the Heritage Environment
Authors: Calzolari Marta , Davoli Pietromaria , Frighi Valentina
Published: January 2025

Today, the role of the construction sector is fundamental to mitigating climate change, especially given the potential of innovations introduced during the Industrial Revolution. The Internet of Things (IoT), together with Internet-enabling technologies, has developed and spread even in the architecture, engineering, and construction (AEC) sector, though with some differences in purposes and objectives. However, especially in the field of heritage buildings, a gap in the definition of cultural heritage (CH) and the one in the concept of smartness need to be bridged. This chapter aims to identify specific innovative approaches for CH, through an analysis of a literature review and best practices related to the different applications of the aforementioned technologies, to develop a roadmap toward new perspectives against climate change while increasing the smartness of the heritage environment.
REVERT Framework: Stakeholder Perspective to Enable Circular Transformation of Construction Industry
Authors: Bostancı Hafize Büşra , Tanyer Ali Murat , Habert Guillaume
Published: January 2025

The stakeholders in various industries focus on developing innovative preventions to increase environmental, economic, and social sustainability to tackle the negative impacts of climate change. Hence, the interest in transitioning from a linear to a circular model has gained momentum in the last decade. The circular economy (CE), therefore, has attracted the construction industry stakeholders to adopt the sustainable model based on the CE principles because it is the most resource-consuming and waste-producing industry. Recycling the materials and construction and demolition waste, reusing the building components, renovating and refurbishing the buildings, adapting circular building design principles, innovating for a regenerative built environment, developing circular supply chains, and enabling circular business models are the core topics to ground this new model. However, the more perspectives, the more challenging the transition. Therefore, circular transition in the construction industry becomes compelling since it has complex and distributed collaborations due to its nature. Although the number of studies has increased, the circular construction industry from the stakeholder perspective still needs to be explored. Within this point of view, this study aims to present a new framework developed to increase stakeholder collaboration for circular transition at micro, meso, and macro-scales. It approaches the micro-scale for materials, meso-scale for buildings, and macro-scale for cities. Besides, it considers the construction industry target groups determined by the European Commission to demonstrate the circular building design principles. The research obtains data by literature review, maps the findings at micro, meso, and macro-scales, and employs natural language processing (NLP) to analyze the CE strategies. Followingly, it constructs thirty-seven success factors to treat the strategies obtained by NLP. Consequently, the REVERT framework based on six dimensions and thirty-seven success factors is introduced to consider stakeholder collaboration for circular transformation in the construction industry.
Urban Waste Recycling: A Multi-objective Approach for Sustainable Construction in European Regions
Authors: Komkova Anastasija , Krog Agergaard Sophie , Holt Andersen Birgitte , Habert Guillaume
Published: January 2025

Urgent needs to mitigate climate change and reduce waste generation require collaborations between sectors. We examine the impacts of the potential recycling of ashes from the incineration of urban waste streams such as municipal solid waste, sewage sludge, and biomass within the construction sector. We perform material flow analysis to estimate the flows and stocks of ashes to identify underutilized waste streams. In this study, we use a multi-objective optimization model at the regional level (country level) to estimate optimal scenarios for urban waste recycling in the construction sector, with a focus on minimizing CO2 eq. emissions and costs. We combine geographic information systems and life cycle assessment (LCA) to examine the configurations of optimal supply chain networks, including direct symbiosis between waste producers and construction material manufacturers, as well as centralized waste recycling plants with recovery of valuable substances. We apply the proposed methodology to a case of sewage sludge recycling and phosphorus recovery in Denmark. Results show that recycling of sewage sludge ashes as supplementary cementitious materials with mineral recovery can bring up to 69% lower CO2 eq. emissions compared to business-as-usual ash landfilling and production of conventional cement construction materials and fertilizers. The methodology can be further applied to assess impacts with potential urban waste recycling in different regions. The results can provide indications to policymakers to encourage the establishment of new urban-industrial collaborations, promote sustainable waste management practices, and advance the goals of a circular economy.
Sustainability and Uncertainty in Collaborative Project Delivery
Authors: Narum Kristoffer Brattegard , Kals Per Morten , Lædre Ola
Published: January 2025

Building construction has a profound impact on economic, social and environmental sustainability. The transformation of building construction towards reaching the United Nations sustainability goals will necessitate a transformation of project delivery models (PDMs) in construction projects. Successful management of uncertainty is essential for a project to reach its goals. Sustainable transformation is increasing the complexity and need for innovation in construction projects, and complex projects have a relatively high tendency to fail in reaching their goals. Collaborative project delivery models (CDMs) are considered particularly suitable for complex projects with high uncertainty and need for innovation. A CDM can be divided into contractual, organizational and cultural elements. The relationship between CDM elements, uncertainty and sustainability is insufficiently understood. This chapter seeks to fill the research gap by examining experiences from five large European collaborative projects studied in two longitudinal multiple-case studies carried out in cooperation with two of the largest project owners in the Norwegian construction industry. Experiences from the five case projects demonstrate how CDM elements facilitate early and joint management of opportunities and risks in a way which can advance both economic, social and environmental sustainability. For a CDM to successfully contribute to the advancement of sustainability, its elements must be selected and implemented in ways that ensure the recruitment, incentivization and organization of suppliers and personnel with competence and commitment to create a collaborative culture aimed at achieving sustainability goals. Social, political and market uncertainty in the front-end greatly impacts the ability of the client to select and implement such a CDM. In future research, it is recommended to study in detail how collaboration towards sustainability goals can be integrated into CDM elements and to carry out comparative quantitative studies on how projects with various forms of such integration perform economically, socially and environmentally.
Future-Proofing Energy Infrastructure: Power Grid Risk Assessment
Authors: Qudaisat Muneer , Houssou Dela , Gallus William , Alipour Alice
Published: January 2025

Climate-change-imposed challenges in the form of heightened frequency and intensity of weather events exert additional pressure on securing the imperative continuous and reliable power supply, leading to increased power outages. This research proposes a comprehensive framework for enhancing the resilience of electric power networks (EPNs) through reliability-based risk assessment, promoting predictions and proactive decisions. The presented research discusses weather phenomena, their association with climate change, and their projected impacts. The numerical weather prediction model, WRF 3.4.1, with a 4 km resolution cell grid, gives a more accurate projection of high winds’ frequency and intensity. The simulation period from 2086 to 2099 is based on a reference control period spanning from 2000 to 2013, with adjustments made to background conditions using climate model output consistent with projections for the late century, a pseudo-global warming (PGW) technique. The presented research focuses on the wooden power distribution poles. The reliability assessment approach employs fragility development and analysis against wind scenarios through advanced modeling techniques and statistical analysis used to mimic historical and projected wind scenarios and to allow numerous factors on both the demand and capacity sides and their inherent uncertainties to be considered. The annual probability of failure is obtained by performing a mathematical convolution of the fragility and the hazard curves, showing the reflection of the effects of climate change on the annual probability of failure. Scaling these results to a system-level resilience assessment will facilitate the flexible energy design strategies integration and allow smoother net-zero standards incorporation and adaptation to the changing environmental conditions. This understanding will allow the decision-makers to evaluate the critical locations within a distribution line and plan to address the vulnerabilities by hardening the assets or implementing modern microgrid techniques or distributed energy resource integration.
Behavioral corroboration that Saitis barbipes jumping spiders cannot discriminate between males’ red and black ornaments
Authors: Plate Janka , Tedore Cynthia
Published: January 2025

Physiological or genetic assays and computational modeling are valuable tools for understanding animals’ visual discrimination capabilities. Yet sometimes, the results generated by these methods appear not to jive with other aspects of an animal’s appearance or natural history, and behavioral confirmatory tests are warranted. Here we examine the peculiar case of a male jumping spider that displays red, black, white, and UV color patches during courtship despite the fact that, according to microspectrophotometry and color vision modeling, they are unlikely able to discriminate red from black. To test whether some optical or neurological component could have been missed using these methods, we conduct mate choice experiments. Some females are presented with a choice between males with their red leg coloration painted over with either red or black paint, while other females are presented with a choice between males with the same coloration painted over by either red or white paint. This latter pairing of red and white males should have been easily distinguishable to the spiders and served as a control to ensure our experimental setup was conducive to natural mating behavior. Red males were more likely to mate than white males (P = 0.035), whereas red and black males had identical mating success (P = 1.0). This suggests that previous physiological and computational work on these spiders was correct in concluding that they are unable to discriminate between red and black. Any functional significance of displaying both colors, rather than only black, remains unresolved.
New method for lightweight design of hybrid components made of isotropic and anisotropic materials
Authors: Stolz Lorenz , Fang Xiangfan
Published: January 2025

For the development of efficient and economical car body structures, high-performance lightweight materials such as continuous fiber-reinforced plastics (C-FRP)—especially in combination with quasi-isotropic materials (f.e. metal) as multi-material components—have gained importance. However, the systematic design of such hybrid components is extremely challenging. In the following work, a newly developed method for the weight- and load-optimized design of hybrid components made of isotropic and anisotropic materials based on physical parameters is presented. With the principal stresses of a reference component a weight-optimized structure between isotropic "base material" and load-dependent reinforcement made of C-FRP is calculated for a new multi-material component. The user specifies the mechanical properties as well as min. and max. material thicknesses for the isotropic material and the C-FRP. With this information the lightest possible material combination of isotropic base material and anisotropic C-FRP is then determined. Using this method, a weight saving of 18–62% could be achieved with flat validation examples while maintaining the same stiffness. Application to the frame of a vehicle door also results in a significant weight saving without compromising stiffness. In summary, this method offers the possibility to identify suitable components for the application of weight- and load-dependent hybrid components and to design them in the early stage of the product development process.
Pelvic Organ Prolapse Repair Using Robotic-Assisted Sacral Hysterocolpopexy vs Vaginal Surgery with the Uphold™ System: 1-Year Clinical Outcomes
Authors: Poutakidis Georgios , Falconer Christian , Altman Daniel , Johannesson Ulrika , Zhang Anju , Ericson Charlotta , Stenberg Mats , Altrock Sabine , Morcos Edward
Published: January 2025

Introduction and Hypothesis

The aim of the study was to compare clinical outcomes when using robotic-assisted sacral hysterocolpopexy (RASC) and vaginal surgery using the Uphold™ Vaginal Support System mesh for pelvic organ prolapse repair.

Methods

This was a nonrandomized, prospective, multicenter study in which 72 women underwent RASC, and 73 Uphold™ surgery, for apical prolapse (POP-Q C ≥ stage II). Anatomical outcomes were assessed using the Pelvic Organ Prolapse Quantification (POP–Q) system. Subjective outcomes were evaluated using the Pelvic Floor Distress Inventory 20 (PFDI-20), the Pelvic Floor Impact Questionnaire – short form (PFIQ-7), and the Pelvic Organ Prolapse/Urinary Incontinence Sexual Questionnaire (PISQ-12), as well as pain estimation using the visual analog scale (0–10).

Results

One year after surgery, an optimal apical segment outcome (POP-Q C stage 0–1) was achieved in 96.4% and 93.3% for the RASC and Uphold™ respectively, p = 0.49. However, reoperation for prolapse recurrence was significantly more common after RASC (11 out of 72 [15.3%] vs Uphold™ (2 out of 71 [2.8%], p = 0.005), and an optimal outcome of the anterior vaginal wall was higher after Uphold™ (p < 0.001). Postoperative PFDI-20, PFIQ-7, and pain significantly improved for both RASC and Uphold™ (p = 0.004 to < 0.001), but a more pronounced improvement in the total PFDI-20 and POPDI-6 sub-scores was observed after Uphold™ than after RASC (−73 ± 55.6 vs −49.2 ± 43.7, p = 0.005 and −39.6 ± 23.6 vs −27 ± 23.9, p < 0.001 respectively).

Conclusions

Reoperation for prolapse recurrence within 1 year was more common after RASC than after Uphold™. However, the rate of complications was low overall and there were few and largely insignificant differences in outcomes when comparing RASC and Uphold™.
The role of muscle synergies and task constraints on upper limb motor impairment after stroke
Authors: Ortega-Auriol Pablo , Byblow Winston D. , Ren April Xiaoge , Besier Thor , McMorland Angus J. C.
Published: January 2025

This study explores the role of task constraints over muscle synergies expression in the context of upper limb motor impairment after stroke. We recruited nine chronic stroke survivors with upper limb impairments and fifteen healthy controls, who performed a series of tasks designed to evoke muscle synergies through various spatial explorations. These tasks included an isometric force task, a dynamic reaching task, the clinical Fugl-Meyer (FM) assessment, and a pinch task. Electromyographic data from 16 upper limb muscles were collected during each task, alongside intermuscular coherence (IMC) measurements during the pinch task to assess neuromuscular connectivity. The findings confirm that motor impairment is inversely related to the diversity of muscle synergies, with fewer synergies and more stereotypical synergy structures observed post-stroke. The study further reveals that the nature of motor tasks significantly affects the number of identifiable muscle synergies, with less constrained tasks revealing a broader array of synergies. These findings highlight the importance of carefully selecting motor tasks in the context of clinical research and assessments to understand a patient’s motor impairment, thus aiding in developing tailored rehabilitation strategies.
Repeatability of AI-based, automatic measurement of vertebral and cardiovascular imaging biomarkers in low-dose chest CT: the ImaLife cohort
Authors: Hamelink Iris , van Tuinen Marcel , Kwee Thomas C. , van Ooijen Peter M. A. , Vliegenthart Rozemarijn
Published: January 2025

Objective

To evaluate the repeatability of AI-based automatic measurement of vertebral and cardiovascular markers on low-dose chest CT.

Methods

We included participants of the population-based Imaging in Lifelines (ImaLife) study with low-dose chest CT at baseline and 3–4 month follow-up. An AI system (AI-Rad Companion chest CT prototype) performed automatic segmentation and quantification of vertebral height and density, aortic diameters, heart volume (cardiac chambers plus pericardial fat), and coronary artery calcium volume (CACV). A trained researcher visually checked segmentation accuracy. We evaluated the repeatability of adequate AI-based measurements at baseline and repeat scan using Intraclass Correlation Coefficient (ICC), relative differences, and change in CACV risk categorization, assuming no physiological change.

Results

Overall, 632 participants (63 ± 11 years; 56.6% men) underwent short-term repeat CT (mean interval, 3.9 ± 1.8 months). Visual assessment showed adequate segmentation in both baseline and repeat scan for 98.7% of vertebral measurements, 80.1–99.4% of aortic measurements (except for the sinotubular junction (65.2%)), and 86.0% of CACV. For heart volume, 53.5% of segmentations were adequate at baseline and repeat scans. ICC for adequately segmented cases showed excellent agreement for all biomarkers (ICC > 0.9). Relative difference between baseline and repeat measurements was < 4% for vertebral and aortic measurements, 7.5% for heart volume, and 28.5% for CACV. There was high concordance in CACV risk categorization (81.2%).

Conclusion

In low-dose chest CT, segmentation accuracy of AI-based software was high for vertebral, aortic, and CACV evaluation and relatively low for heart volume. There was excellent repeatability of vertebral and aortic measurements and high concordance in overall CACV risk categorization.

Key Points

QuestionCan AI algorithms for opportunistic screening in chest CT obtain an accurate and repeatable result when applied to multiple CT scans of the same participant?

FindingsVertebral and aortic analysis showed accurate segmentation and excellent repeatability; coronary calcium segmentation was generally accurate but showed modest repeatability due to a non-electrocardiogram-triggered protocol.

Clinical relevanceOpportunistic screening for diseases outside the primary purpose of the CT scan is time-consuming. AI allows automated vertebral, aortic, and coronary artery calcium (CAC) assessment, with highly repeatable outcomes of vertebral and aortic biomarkers and high concordance in overall CAC categorization.
Natural conditions and sociocultural development in the Mid-Kama region (cis-Ural, Russia) over the last ten millennia: insights from the Shabunichi-1 peat core
Authors: Batalova Vlada , Sannikov Pavel , Pereskokov Mikhail , Mingalev Vitaliy , Vyazov Leonid , Salova Julia , Novikova Ekaterina , Mekhonoshina Elizaveta , Orlova Elizaveta , Shumilovskikh Lyudmila
Published: January 2025

The Ural Mountains represent a distinctive bioecological and climatic boundary between Europe and Asia, simultaneously uniting them through cultural, ethnic, and economic ties throughout history. To investigate these complex human-environment interactions during the last ~ 10,000, we obtained a peat core Shabunichi-1 and analyzed it using AMS radiocarbon dating, loss-on-ignition, pollen, non-pollen palynomorphs, micro- and macrocharcoal analyses. Our palaeoecological study demonstrate that climate and frequent fires were the main drivers of ecosystem change until ~ 4,000 cal bp. Dry climate conditions between ~ 9,300 and 7,400 cal bp resulted in the dominance of pine-birch forest-steppe as well as frequent local fires. Subsequent climate humification led to the expansion of broad-leaved-dark coniferous forests and a change in the fire regime, reducing the frequency and/or severity of fire events between ~ 7,400 and 5,100 cal bp. The peak in climatic humidity was reached between 5,100 and 3,900 cal bp, which favored the development of spruce forests with a greater admixture of broad-leaved species. After ~ 4,000 cal bp, anthropogenic impacts began to shape the appearance of regional ecosystems culminating in the maximum landscape openness during the Bronze and Iron Ages. The activities of Bronze Age cultures and the emergence of metallurgy and pastoralism in the region led to the strong decline of spruce forests and the spread of secondary pine-birch formations and meadows. Human impact during the Iron Age and the emergence of agriculture in the region caused the largest local fires and the reduction of interfluvial forests. Despite humans becoming the primary driver of ecosystem change in the second half of the Middle and Late Holocene, climate continued to play a critical role in triggering cultural transformations and migration processes in the region.
Hospital to home transition of children with medical complexities in the Netherlands: current practice
Authors: Haspels H. N. , Knoester H. , Jansen N. J. G. , Ahout I. M. L. , van Karnebeek C. D. , de Hoog M. , vanWoensel J. B. M. , Joosten K. F. M.
Published: January 2025

Children with Medical Complexity (CMC) often require 24/7 expert care, which may impede discharge from hospital to home (H2H) resulting in prolonged admission. Limited research exists on pediatric patients with delayed discharges and the underlying reasons for such extended admissions. Therefore, our objectives were to (1) describe the demographics, clinical characteristics, and course of CMC who are in their H2H transition and (2) identify the reasons for postponement of H2H discharge. Prospective, multicenter, observational cohort study performed from February 2022 until November 2022 for 6 months in four Dutch University Medical Center children’s hospitals. Clinically admitted patients (age 0–18 years) were eligible for inclusion if they were medically stable, yet required specialized nursing and/or paramedical care and were in the H2H transition process. In total, 44 participants were included, of whom 32 (72.7%) were younger than 1 year. Median stay in the hospital was 7.3 weeks (range 0.7–28.7). Upon entering the H2H phase, postponement of discharge was for 65.1% of the patients primarily due to a combination of medical reasons and organizational/family factors. For the remaining 34.9% of the patients, discharge was delayed solely due to organizational and/or family factors.

Conclusion

Our study highlights several reasons contributing to the postponement of discharge for pediatric patients with medical complexity, including their medical fragility, the time-consuming process of parent training, and the challenges in organizing home care. Future steps should explore various transitional care programs aimed at improving the H2H transition.

What is Known:

• Hospital to home transition for Children with Medical Complexity is a multi-faceted process with many challenges and obstacles

• Insight into the current practice of transitioning home in University Medical Centers remains unknown and is needed to develop a tailored yet standardized approach

What is New:

• Our findings reveal reasons for postponement of discharge home and show that patients are medically stable for more than half of their hospital stays. This indicates potential opportunities to reorganize care for better outcomes for the child, the family, and healthcare consumption
Blood neurofilament light chain and S100B as biomarkers of neurological involvement and functional prognosis in COVID-19: a multicenter study
Authors: Bisulli Francesca , Muccioli Lorenzo , Taruffi Lisa , Bedin Roberta , Felici Silvia , Zenesini Corrado , Baccari Flavia , Gentile Mauro , Orlandi Niccolò , Rossi Simone , Nicodemo Marianna , d’Achille Fabio , Viale Pierluigi , Zaccaroni Stefania , Lodi Raffaele , Liguori Rocco , Zini Andrea , Guarino Maria , Cortelli Pietro , Lazzarotto Tiziana , Janigro Damir , Meletti Stefano
Published: January 2025

Background and aim

COVID-19 is associated with neurological complications, termed neuro-COVID, affecting patient outcomes. We aimed to evaluate the association between serum neurofilament light chain (NfL) and S100B biomarkers with the presence of neurological manifestations and functional prognosis in COVID-19 patients.

Methods

A multicenter prospective cohort study was conducted in three hospitals in the Emilia-Romagna region, Italy, from March 2020 to April 2022. Hospitalized patients with PCR-confirmed COVID-19 were enrolled. Serum S100B and NfL levels were measured in the acute or subacute phase after admission. Diagnostic accuracy was assessed using receiver operating characteristic (ROC) analyses. Statistical analyses were performed to evaluate the association between biomarkers, clinical/laboratory variables, and prognosis, specifically focusing on worsening of the modified Rankin Scale (mRS) from admission to discharge.

Results

A total of 279 patients (153 males, median age 76.7 years) were included. Among them, 69 (24.7%) developed neuro-COVID. Serum NfL levels were significantly higher in the neuro-COVID group (median 110 vs 68.3; p = 0.035) and correlated with severe encephalopathy and extracranial neurologic manifestations. The ROC analysis showed low accuracy in the discrimination between the two groups for both NfL and S100B. Key predictors of worsening mRS included mechanical ventilation (OR = 9.56, 95% CI = 1.67–54.75; p = 0.011), severe encephalopathy (OR = 5.10, 95% CI = 1.58–16.19; p = 0.006), and elevated S100B levels (OR = 2.62, 95% CI = 1.10–6.46; p = 0.037).

Conclusions

Serum NfL and S100B biomarkers were not accurate in discriminating neuro-COVID patients, however NfL levels were associated with severe and extracranial neuro-COVID, while S100B with functional outcomes, potentially informing clinical management.
The protein cargo of extracellular vesicles correlates with the epigenetic aging clock of exercise sensitive DNAmFitAge
Authors: György Bernadett , Szatmári Réka , Ditrói Tamás , Torma Ferenc , Pálóczi Krisztina , Balbisi Mirjam , Visnovitz Tamás , Koltai Erika , Nagy Péter , Buzás Edit I. , Horvath Steve , Radák Zsolt
Published: January 2025

Extracellular vesicles (EVs) are implicated in inter-organ communication, which becomes particularly relevant during aging and exercise. DNA methylation-based aging clocks reflect lifestyle and environmental factors, while regular exercise is known to induce adaptive responses, including epigenetic adaptations. Twenty individuals with High-fitness (aged 57.7 ± 9.8 years) and twenty Medium–Low-fitness (aged 57.5 ± 9.7 years) subjects provided blood samples. EVs were isolated from the samples using a size exclusion chromatography (SEC)-based method, and their protein content was analyzed by mass spectrometry (MS). Acceleration of the biological age estimator DNAmFitAge (AgeAccelFit) was associated with the protein cargo of EVs, whereas PhenoAge and GrimAge acceleration did not show a significant relationship. This finding suggests that the epigenetic aging-modulating role of exercise may involve inter-organ communication via EVs. Set Enrichment Analysis was performed to identify enriched Gene Ontology (GO) terms for sets of proteins that were either correlated with AgeAccelFit or detected exclusively in individuals with high levels of aerobic fitness. The protein cargo of EVs further suggests that inter-organ communication influences inflammation, the immune system, cellular repair, adhesion, metabolism and coagulation. Our findings help to understand the preventive role of exercise, which could be mediated in part by EVs.
Pre-distance assessment from radial artery to lower extremity arterial lesion
Authors: Sano Arata , Sugimoto Takeshi , Iwasaki Tomoya , Miki Tomonori , Takai Shigeki , Wakana Noriyuki , Zen Kan , Yamada Hiroyuki , Matoba Satoaki
Published: January 2025

Endovascular treatment (EVT) for patients with lower extremity artery disease is widely used as a less invasive alternative to surgical bypass. Recently, transradial artery intervention has gained popularity owing to its minimally invasive nature. The distance from the radial artery to the target vessel is critical for success; however, effective pre-assessment methods have not yet been established. This study aimed to evaluate the usefulness of predistance measurements from the left radial artery using simple computed tomography (CT) images. In this study, distance measurements were performed from the left radial artery to the left and right iliac artery bifurcations and from the left radial artery to the common femoral artery at the upper femoral border. These distances, measured using CT images before and after the lower-extremity contrast study, were compared with the distances identified during the lower-extremity contrast study. Distances measured using simple CT images showed a high correlation with the distances identified during the lower-extremity contrast examination (r = 0.9317, p < 0.0001; from the left radial artery to the left and right iliac artery bifurcation; r = 0.9402, p < 0.0001; and from the left radial artery to the right common femoral artery at the upper femoral border). Our results suggest that pre-distance measurement using simple CT images can be a useful tool for EVT using the left radial artery approach. Although future large-scale studies are required, this technique merits consideration owing to its widespread adoption in clinical practice.
Factors influencing behavioral intention to use e-learning in higher education during the COVID-19 pandemic: A meta-analytic review based on the UTAUT2 model
Authors: Zheng Hao , Han Feifei , Huang Yi , Wu Yonghe , Wu Xinyi
Published: January 2025

Amidst the COVID-19 pandemic, the e-learning demand among in tertiary education sector has surged, which has produced prolific research on factors influencing students’ and faculties e-learning adoption. Anchored in the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework, this study employed a meta-analytic approach to investigate the effects of seven key antecedents (i.e., Performance Expectation, Effort Expectation, Social Influence, Facilitating Conditions, Hedonic Motivation, Price Value, and Habit) and possible moderators on Behavioral Intention (BI) towards using e-learning. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, the study identified 91 empirical studies involving 37,910 participants including both university faculties and students. The results show that Habit was the most influential antecedent on BI. Apart from Habit, Hedonic Motivation, Price Value, Performance Expectation, and Facilitating Conditions were strongly correlated with BI towards using e-learning, whereas Effort Expectation, Social Influence, and BI had moderate relations with BI. The moderation analyses demonstrate that the variables of gender, user type, region, cultural orientation, and income level all significantly moderated the relations between various antecedents and BI. The study results provide some practical implications on how e-learning providers or institutions may more effectively improve e-learning adoption among faculties and students. Possible strategies may include designing strategies to enhance habit formation of users, leveraging hedonic motivation by incorporating interactive and engaging contents, and offering technical support and cost-effective e-learning platforms. Furthermore, strategies which are designed to foster positive e-learning adoption should also be tailored to accommodate diverse learner profiles by taking the moderating factors of gender, cultural backgrounds, and economic disparities, ultimately leading to more equitable and inclusive e-learning in higher education.
Application of human activity/action recognition: a review
Authors: sedaghati Nazanin , ardebili Sondos , Ghaffari Ali
Published: January 2025

Human activity recognition is a crucial domain in computer science and artificial intelligence that involves the Detection, Classification, and Prediction of human activities using sensor data such as accelerometers, gyroscopes, etc. This field utilizes time-series signals from sensors present in smartphones and wearable devices to extract human activities. Various types of sensors, including inertial HAR sensors, physiological sensors, location sensors, cameras, and temporal sensors, are employed in diverse environments within this domain. It finds valuable applications in various areas such as smart homes, elderly care, the Internet of Things (IoT), personal care, social sciences, rehabilitation engineering, fitness, and more. With the advancement of computational power, deep learning algorithms have been recognized as effective and efficient methods for detecting and solving well-established HAR issues. In this research, a review of various deep learning algorithms is presented with a focus on distinguishing between two key aspects: activity and action. Action refers to specific, short-term movements and behaviors, while activity refers to a set of related, continuous affairs over time. The reviewed articles are categorized based on the type of algorithms and applications, specifically sensor-based and vision-based. The total number of reviewed articles in this research is 80 sources, categorized into 42 references. By offering a detailed classification of relevant articles, this comprehensive review delves into the analysis and scrutiny of the scientific community in the HAR domain using deep learning algorithms. It serves as a valuable guide for researchers and enthusiasts to gain a better understanding of the advancements and challenges within this field.
Point cloud quality metrics for incremental image-based 3D reconstruction
Authors: Neumann Kai A. , Tausch Reimar , Kutlu Hasan , Kuijper Arjan , Santos Pedro , Fellner Dieter
Published: January 2025

Image-based 3D reconstruction is a powerful method for accurately reconstructing an object’s geometry and texture from images. A crucial factor for the accuracy and completeness of the resulting reconstructed model is the choice of poses for capturing images, which is called view planning. One possible view planning strategy uses an iterative feedback loop that switches between planning poses and an incremental reconstruction to autonomously digitize an object without prior knowledge. However, this approach requires identifying which parts of an object are “poorly reconstructed” and thus would benefit from being part of additional images. This work explores the use of point cloud quality metrics to provide this feedback by comprehensively comparing a set of existing and newly introduced metrics in terms of their time-dependent behavior, similarity, and their applicability to view planning. Among the newly proposed metrics this work introduces the Reconstruction Quality Feedback (RQF), which shows a significantly improved performance in simulations when being used for view planning. The effectiveness of RQF is also demonstrated for real objects on an autonomous robotic 3D digitization system.
Perceived job security and politicians’ legislative effort
Authors: Nower Michael
Published: January 2025

The relationship between job security and politicians’ legislative effort is bidirectional, making isolating the impacts, and the mechanisms underlying them, in either direction difficult. Increased legislative effort could increase politicians’ job security, as they might be considered to be more desirable by voters, however, increased job security can change the incentives to engage in legislative activity. We analyse the behaviour of UK Members of Parliament (MPs) from 1997 to 2019 to examine the mechanisms driving any impact of job security on legislative effort, using an instrument for job security that is not impacted by individual effort. We show that the impact of job security on effort is primarily driven by an opportunity cost of time allocation mechanism, with MPs who are less secure in their job allocating less of their time to legislative activities. This opportunity cost increases with the breadth of their legislative effort, and is primarily driven by individuals with lower outside options, who face a greater cost of electoral defeat. We provide reduced-form evidence that this opportunity cost is primarily driven by the maintenance of non-parliamentary human capital by MPs, rather than activities designed to improve their electoral prospects.
Accelerating social science knowledge production with the coordinated open-source model
Authors: Turek Konrad
Published: January 2025

With the growing complexity of knowledge production, social science must accelerate and open up to maintain explanatory power and responsiveness. This goal requires redesigning the front end of the research to build an open and expandable knowledge infrastructure that stimulates broad collaborations, enables breaking down inertia and path dependencies of conventional approaches, and boosts discovery and innovation. This article discusses the coordinated open-source model as a promising organizational scheme that can supplement conventional research infrastructure in certain areas. The model offers flexibility, decentralization, and community-based development and aligns with open science ideas, such as reproducibility and transparency. Similar solutions have been successfully applied in natural science, but social science needs to catch up. I present the model’s design and consider its potential and limitations (e.g., regarding development, sustainability, and coordination). I also discuss open-source applications in various areas, including a case study of an open-source survey harmonization project Comparative Panel File.
Scaffolded Agents, for Better or Worse: Assessing the Formative Aspect of Scaffolding
Authors: Dengsø Mads J.
Published: January 2025

Cognitive scaffolding is typically conceptualized in terms of environmental design which serves to offload, facilitate, or enhance the cognitive capacities of interacting agents. Recent contributions to the literature on scaffolding have noted that environmental design might likewise scaffold cognition in ways that undermine the interests of interactant agents—giving rise to notions of problematic or hostile scaffolding. Given the pervasiveness of social and technological scaffolding in contemporary life, the importance of understanding and assessing its effects can hardly be overstated. At the same time, however, the very pervasiveness of scaffolding raises a challenge to the current criteria for evaluating its effects by comparison with agents’ interests. This is because human agents and their interests alike are themselves the results of various forms of social and technological scaffolding. This paper explores the relationship between scaffolding and the formation of agents along with their interests, as well as the implications of this relationship for evaluating scaffolding as being hostile, neutral, or beneficial. I will argue that the formative aspect of scaffolding imparts a degree of uncertainty to evaluations of scaffolding based on agents’ interests. I will then demonstrate the relevance of the formative aspect of scaffolding in evaluating and assessing the potentially pernicious effects of contemporary social and technological scaffolding focusing on the examples of servitization marketing models and social and vocational digital infrastructures.
Electrocatalytic Oxidation of Toxic Wastewater using Electrodes based on Transition d-metal Oxides
Authors: Yaşar Çırak Semra , Öztürk Dilara , Akyol Abdurrahman
Published: January 2025

The process of electrooxidation of the active substances Paracetamol (PCT), benzoquinone (BQ) and hydroquinone (HQ) was studied using a set of different dimensionally stable anode (DSA) and Boron doped diamond (BDD) electrodes. Comparison of the efficiency of electrocatalytic anodes was assessed using percent total organic carbon (%TOC) removal and PCT amount removal values. The removal of %TOC in synthetically prepared waters for the BDD anode reached 96%, for DSA electrodes Ti/PbO2-IrO2-RuO2 57%, Ti/IrO2-RuO2-TiO2 35%, Ti/IrO2-RuO2-SnO2 31%, Ti/RuO2-SnO2 30% and Pt 24%. BDD effectively degrades PCT and almost completely mineralizes BQ and HQ. A DSA-Ti/PbO2-IrO2-RuO2 electrode and a BDD electrode were used in the electrooxidation process of real industrial wastewater containing PCT. The BDD electrode had a TOC removal efficiency of 58%, while the DSA-Ti/PbO2-IrO2-RuO2 electrode achieved 52%. Despite similar values ​​of PCT removal by both electrodes, the Ti/PbO2-IrO2-RuO2 anode showed low mineralization of organic matter. The originality of this paper lies in the study of the electrooxidation of real PCT wastewater and the use of a Ti/PbO2-IrO2-RuO2 electrode.

Graphical Abstract