bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Role of Materiality in an Era of Generative Artificial Intelligence
Authors: Tang Kok-Sing , Cooper Grant 
Published: February 2024

AbstractThe introduction of generative artificial intelligence (GenAI) tools like ChatGPT has raised many challenging questions about the nature of teaching, learning, and assessment in every subject area, including science. Unlike other disciplines, natural science is unique because the ontological and epistemological understanding of nature is fundamentally rooted in our interaction with material objects in the physical world. GenAI, powered by statistical probability arising from a massive corpus of text, is devoid of any connection to the physical world. The use of GenAI thus raises concerns about our connection to reality and its effect on science education. This paper emphasizes the importance of materiality (or material reality) in shaping scientific knowledge and argues for its recognition in the era of GenAI. Drawing on the perspectives of new materialism and science studies, the paper highlights how materiality forms an indispensable aspect of human knowledge and meaning-making, particularly in the discipline of science. It further explains how materiality is central to the epistemic authority of science and cautions the outputs generated by GenAI that lack contextualization to a material reality. The paper concludes by providing recommendations for research and teaching that recognize the role of materiality in the context of GenAI, specifically in practical work, scientific argumentation, and learning with GenAI. As we navigate a future dominated by GenAI, understanding how the epistemic authority of science arises from our connection to the physical world will become a crucial consideration in science education.
Aggregating the Human Development Index: A Non-compensatory Approach
Authors: Natoli Riccardo , Feeny Simon , Li Junde , Zuhair Segu 
Published: February 2024

AbstractThe United Nations’ Human Development Index remains a widely used and accepted measure of human development. Although it has been revised over the years to address various critiques, a remaining concern is the way the three dimensions are aggregated into the single index. A deterioration in one dimension can be compensated for by an improvement in another. Since compensability is inextricably linked with trade-offs and intensity of preferences, a non-compensatory (i.e., Condorcet) approach to aggregation is employed in this paper. Although non-compensatory approaches have been employed previously, this paper adds to the literature by undertaking an application of the Condorcet approach to the entire HDI. This approach, which does not use intensities of preferences, ensures that the degree of compensability connected with the aggregation model is at the minimum possible level. To achieve this, country level rankings are then compared to those for the 2020 Human Development Index which aggregates dimensions using a geometric mean. The findings demonstrated substantial changes in rank-order between the HDI and Condorcet approach. This outcome provides empirical evidence which demonstrates that the non-compensatory Condorcet approach can mitigate issues of compensation present within the geometric aggregation technique currently employed by the HDI. These findings have potential implications in aiding the identification and employment of potential policy priorities—specifically, the notion that policy should emphasise the development of a country as opposed to economic growth alone.
Prediction of monthly evapotranspiration by artificial neural network model development with Levenberg–Marquardt method in Elazig, Turkey
Authors: Kartal Veysi 
Published: February 2024

Abstract The phenomenon of evapotranspiration (ET) is closely linked to the issue of water scarcity, as it involves water loss through both evaporation and plant transpiration. Accurate prediction of evapotranspiration is of utmost importance in the strategic planning of agricultural irrigation, effective management of water resources, and precise hydrological modeling. The current investigation aims to predict the monthly ET values in the Elazig province by developing an artificial neural network (ANN) model utilizing the Levenberg–Marquardt method. Consequently, the values of temperature, precipitation, relative humidity, solar hour, and mean wind speed were utilized in forecasting evapotranspiration values by implementing ANN algorithms. This research makes a valuable contribution to the existing body of literature by utilizing an ANN model developed with the Levenberg–Marquardt method to estimate evapotranspiration. It has been discovered that evapotranspiration values are impacted by various factors such as temperature (minimum, average, maximum), relative humidity (minimum, average, maximum), wind speed, solar hour, and precipitation values, which are taken into consideration for prediction. The findings indicated that Elazig, Keban, Baskil, and Agin sites had R values of 0.9995, 0.9948, 0.9898, and 0.9994 in the proposed model. It was found that Elazig’s MAPE ranged from 0 to 0.2288, Keban’s was 0.0001 to 0.3703, Baskil’s was between 0 and 0.4453, and Agin’s was both 0 and 0.2784. The findings obtained from the proposed model are compatible with evapotranspiration values computed from the Hargreaves method (R2 = 0.996). The study’s findings provide significant insights for planners and decision-makers involved in the planning and managing water resources and agricultural irrigation.
Epigenetic clock in the aorta and age-related endothelial dysfunction in mice
Authors: Pośpiech Ewelina , Bar Anna , Pisarek-Pacek Aleksandra , Karaś Agnieszka , Branicki Wojciech , Chlopicki Stefan 
Published: February 2024

AbstractWhile epigenetic age (EA) of mouse blood can be determined using DNA methylation analysis at three CpG sites in the Prima1, Hsf4 and Kcns1 genes it is not known whether this approach is useful for predicting vascular biological age. In this study we validated the 3-CpG estimator for age prediction in mouse blood, developed a new predictive model for EA in mouse aorta, and assessed whether epigenetic age acceleration (EAA) measured with blood and aorta samples correlates with age-dependent endothelial dysfunction. Endothelial function was characterized in vivo by MRI in 8–96-week-old C57BL/6 mice. Arterial stiffness was measured by USG-doppler. EA-related changes within 41 CpG sites in Prima1, Kcns1 and Hsf4 loci, were analyzed in the aorta and blood using bisulfite amplicon high-throughput sequencing. Progressive age-dependent endothelial dysfunction and changes in arterial stiffness were observed in 36-96-week-old C57BL/6 mice. Methylation levels of the investigated loci correlated with chronological age in blood and the aorta. The new model for EA estimation in aorta included three cytosines located in the Kcns1 and Hsf4, explained R2 = 87.8% of the variation in age, and predicted age with an mean absolute error of 9.6 weeks in the independent test set. EAA in the aorta was associated with endothelial dysfunction in the abdominal aorta and femoral artery what was consistent with the EAA direction estimated in blood samples. The rate of vascular biological ageing in mice, reflected by the age-dependent systemic endothelial dysfunction, could be estimated using DNA methylation measurements at three loci in aorta and blood samples.
Topographic seismic effects and avalanche hazard: A case study of Mount Siella (L’Aquila, Central Italy)
Authors: Totani Ferdinando 
Published: February 2024

AbstractIn mountainous areas, snow avalanches could be triggered by the shaking produced by earthquakes. The forces induced by the earthquake can cause an irregular increase of shear strength load down the slope, for the presence of complex surface and buried morphologies. Topographic irregularities generate maximum effects of waves amplification linked to wavelengths comparable to the horizontal dimension of the topographic feature. For this reason, the selected time-histories represent an appropriate input for the two-dimensional numerical response analyses when a dynamic phenomenon produce the resonant motion of a whole mountain. This represents an important earthquake-induced hazard in snow-covered mountain areas with high probability of seismic events. Some valleys are located in regions with scare ground motion data and investments on infrastructures are not always accompanied by adequate protection against earthquake-induced avalanches. The paper points out a simple deterministic approach for selecting a set of real accelerograms applied to a real case of Siella Mountain (Central Italy) where a large avalanche destroying a tourist facility of Rigopiano resort on 18 January 2017. The selected time histories were used as input for the two-dimensional numerical model of the subsoil to evaluate the topographic seismic amplification in ridge and compare it with the results of other authors. These methods suggest that morphology-related inertial effects should be considered as an overload action on snow layers when controlling multi-hazard studies and spatial planning.
Using satellite-derived land surface temperatures to clarify the spatiotemporal warming trends of the Alborz Mountains in northern Iran
Authors: Roshan Gholamreza , Sarli Reza , Ghanghermeh Abdolazim , Taherizadeh Mehrnoosh , Niknam Arman 
Published: February 2024

AbstractThe Alborz Mountains are some of the highest in Iran, and they play an important role in controlling the climate of the country’s northern regions. The land surface temperature (LST) is an important variable that affects the ecosystem of this area. This study investigated the spatiotemporal changes and trends of the nighttime LST in the western region of the Central Alborz Mountains at elevations of 1500–4000 m above sea level. MODIS data were extracted for the period of 2000–2021, and the Mann–Kendall nonparametric test was applied to evaluating the changes in the LST. The results indicated a significant increasing trend for the monthly average LST in May–August along the southern aspect. Both the northern and southern aspects showed decreasing trends for the monthly average LST in October, November, and March and an increasing trend in other months. At all elevations, the average decadal change in the monthly average LST was more severe along the southern aspect (0.60°C) than along the northern aspect (0.37°C). The LST difference between the northern and southern aspects decreased in the cold months but increased in the hot months. At the same elevation, the difference in the lapse rate between the northern and southern aspects was greater in the hot months than in the cold months. With increasing elevation, the lapse rate between the northern and southern aspects disappeared. Climate change was concluded to greatly decrease the difference in LST at different elevations for April–July.
Orthogonal beamforming technique for massive MIMO systems
Authors: Abdelfatah Marwa , Zekry Abdelhalim , ElSayed Shaimaa 
Published: February 2024

Abstract
Beamforming represents a pivotal technology in massive multiple-input multiple-output (MIMO) systems, as it facilitates the regulation of transmission and reception operations. Beamforming techniques’ categorization is based either on their hardware architecture or implementation strategy. This paper proposes an orthogonal beamforming technology founded on a specific implementation method that utilizes predetermined orthogonal beams to serve users. The suggested approach incorporates numerous orthogonal beams relying on a substantial number of antennas at the base station. The primary objective of this approach is to enhance the performance of massive MIMO systems by augmenting spectral efficiency and accommodating more users. The proposed beamforming approach is well suited for millimeter frequency bands. The purpose of this paper is to explore the suggested orthogonal beamforming technology. The concept of this approach is described at first and then followed by an evaluation of its efficacy for a single user through the allocation of orthogonal beams. The suggested approach is also examined in the context of multiuser systems, and the results are compared with the adaptive ZF beamforming technique. Furthermore, the paper presents solutions to the issues that may arise in multiuser systems, for example, ensuring that each orthogonal beam is assigned to only one user. The simulations conducted in this study demonstrate that the suggested approach outperforms the ZF technique in terms of both the spectral efficiency and the number of serviced users. Specifically, the suggested approach can enhance SE by approximately 40.6% over the ZF technique, and it can support up to double the number of users when compared to the ZF approach.
Using Machine Learning to Identify and Optimize Sensitive Parameters in Urban Flood Model Considering Subsurface Characteristics
Authors: Jin Hengxu , Zhao Yu , Lu Pengcheng , Zhang Shuliang , Chen Yiwen , Zheng Shanghua , Zhu Zhizhou 
Published: February 2024

AbstractThis study presents a novel method for optimizing parameters in urban flood models, aiming to address the tedious and complex issues associated with parameter optimization. First, a coupled one-dimensional pipe network runoff model and a two-dimensional surface runoff model were integrated to construct an interpretable urban flood model. Next, a principle for dividing urban hydrological response units was introduced, incorporating surface attribute features. The K-means algorithm was used to explore the clustering patterns of the uncertain parameters in the model, and an artificial neural network (ANN) was employed to identify the sensitive parameters. Finally, a genetic algorithm (GA) was used to calibrate the parameter thresholds of the sub-catchment units in different urban land-use zones within the flood model. The results demonstrate that the parameter optimization method based on K-means-ANN-GA achieved an average Nash-Sutcliffe efficiency coefficient (NSE) of 0.81. Compared to the ANN-GA and K-means-deep neural networks (DNN) methods, the proposed method better characterizes the runoff generation and flow processes. This study demonstrates the significant potential of combining machine learning techniques with physical knowledge in parameter optimization research for flood models.
Breast Cancer Risk Perceptions Among Underserved, Hispanic Women: Implications for Risk-Based Approaches to Screening
Authors: Austin Jessica D. , Jenkins Sarah M. , Suman Vera J. , Raygoza Jhenitza P. , Ridgeway Jennifer L. , Norman Aaron , Gonzalez Crystal , Hernandez Valentina , Ghosh Karthik , Patel Bhavika K. , Vachon Celine M. 
Published: February 2024

Abstract
Background
Understanding factors that shape breast cancer risk perceptions is essential for implementing risk-based approaches to breast cancer detection and prevention. This study aimed to assess multilevel factors, including prior screening behavior, shaping underserved, Hispanic women’s perceived risk for breast cancer.

Methods
Secondary analysis of survey data from Hispanic women (N = 1325, 92% Spanish speaking, 64% < 50) enrolled in a large randomized controlled trial. Analyses were performed in two cohorts to account for the role of age on screening guideline recommendations (< 50 and 50 +). For each cohort, we examined differences in three common measures of perceived risk of breast cancer (percent lifetime, ordinal lifetime, comparative) by participant factors with chi-square or Kruskal–Wallis tests, as appropriate. Multivariate analyses examined the association between mammography history with percent perceived lifetime risk (outcome > 10 vs ≤ 10%).

Results
Overall, 75% reported a lifetime risk between 0 and 10%, 96% rated their ordinal risk as “not high,” and 50% rated their comparative risk as “much lower.” Women < 50 with a family history of breast cancer reported significantly higher levels of perceived risk across all three measures. Among women 50 + , those reporting lower levels of perceived risk were significantly more likely to be Spanish speaking. No significant association was observed between mammography history and percent lifetime risk of breast cancer.

Conclusion
Factors shaping breast cancer risk perceptions differ by age. Prior screening may play less of role in constructing risk perceptions. Research is needed to develop culturally and linguistically appropriate strategies to improve implementation of risk-based screening.
Forest Tree Virome as a Source of Tree Diseases and Biological Control Agents
Authors: Vainio Eeva J. , Rumbou Artemis , Diez Julio J. , Büttner Carmen 
Published: February 2024

Abstract
Purpose of Review
The collective virome of forest trees can be considered to include not only plant viruses, but also viral communities harbored by all tree-associated organisms. In this review, we will concentrate on reviewing recent developments in the two fields of forest tree virology that have received the most research input during the last 5 years: (1) current knowledge of virus diseases affecting forest trees and their causal agents and (2) fungal viruses (mycoviruses) and properties that are required for utilizing them for biocontrol purposes.

Recent Findings
The discovery of plant and mycoviruses has been revolutionized during the last few years due to high-throughput sequencing (HTS). This has altered our view of virus diversity and prevalence, but also their host ranges, transmission routes, and host effects. Utilization of HTS has greatly expanded our knowledge of plant virus diversity and disease etiology in forest trees and revealed the commonness of cross-kingdom transmission events between fungi, oomycetes, plants, and arthropods. Research on mycoviruses has also identified several new mycoviruses that restrict the growth or virulence of forest pathogenic fungi.

Summary
Gaining knowledge of the collective virome of forest ecosystems is essential not only for understanding virus evolution and diversity but also for improving our understanding on virus impacts, and our ability for biocontrol-based and environmentally friendly management of viral and fungal diseases that affect economically important plants and beneficial insects, and for preventing possible disease outbreaks in the future. Virus infections play a central role in plant health, but viral symptoms on forest trees remain often unrecognized and may be confused with other biotic or abiotic damages. However, recent studies have revealed previously unknown viruses as causes of forest tree symptoms and suggest that viruses are responsible for far greater economic losses than recognized earlier. However, many knowledge gaps still need to be filled, particularly on the diversity of viruses that infect different species of forest trees, their irregular distribution within the plant, their mode of transmission, epidemiology and choice of hosts also regarding crop plants, their effect on the metabolism of their host tree, and their interaction with other microorganisms. Mycovirus research has already deciphered detailed information on many critical properties that affect utilizing them for biocontrol purposes. Still, more knowledge is needed concerning mycoviral transmission mode and stability in field conditions, the level of host tolerance against mycoviral infection, and the occurrence of interspecies mycovirus transmission in nature, and safety issues related to these topics.
A study on the ambient electromagnetic radiation level of 5G base stations in typical scenarios
Authors: Wei Qing , Ge Xiaoyang , Liu Jiaxue , Li Haijie 
Published: February 2024

AbstractKnowledge of the electromagnetic radiation characteristics of 5G base stations under different circumstances is useful for risk prevention, assessment, and management. This paper selects several typical scenes (Open spaces, building concentration areas, user and building intensive areas) for electromagnetic radiation monitoring, and analyzes the relationship between ambient radiated power density and base station background. The results show that the factors that have significant impacts on the environmental radiation power density of 5G base stations including transmission distance, base station distribution, user density, building reflection superposition and so on. The radiation energy decays rapidly with distance. When the density of the building distribution is too large, the superposition effect caused by the reflected wave is concentrated at the distance of 50-70 meters. When the user density decreases (the superposition effect of reflected waves decreases), the 5G monitoring value follows the direct wave attenuation law and decreases rapidly with the increase of distance. Points with higher measured radiation in the simple access condition also had higher measured radiation in the high-speed download condition. With the popularization of 5G mobile phones and the increase of user density, the resource utilization of a single user will decline to the normal operation state, and the radiation environmental impact will be further reduced.
Assessment of fly ash and ceramic powder incorporated concrete with steam-treated recycled concrete aggregates prioritising nano-silica
Authors: Rao Asha Uday , Shetty Prathibha P. , Bhandary P Radhika , Tantri Adithya , S. Blesson , Yaragal Subhash C. 
Published: February 2024

AbstractPresent research involves determining the effects of a proposed novel nano-silica prioritized-steam-treated recycled concrete aggregate (RCA) on microstructural, mechanical, and durability aspects of concrete incorporated with waste ceramic powder (WCP). The study on novel nano-silica prioritized-steam-treated recycled concrete aggregate revealed that 3% nano-silica induction with 3-h steam treatment for 50% adhered mortar bonded RCA performed optimally. The physical characterization of treated RCA showed improvement compared to untreated RCA, which was confirmed by microstructure study indicating the formation of additional calcium silicate hydrates in the bonded adhered mortar of treated RCA. Furthermore, as WCP has significant contents of alumina and silica, an optimum ternary binder mix was developed with cement, fly ash, and WCP. Later, a study was performed to analyse the performance of treated RCA incorporated in WCP prioritized concrete mix. The mechanical performance of WCP prioritized concrete with treated RCA was investigated through compressive strength, flexural strength, split tensile strength, and modulus of elasticity. The quality was ensured through ultrasonic pulse velocity, water absorption, and density characterization. The durability of concrete was studied with 5% concentrated hydrochloric acid attack and sea water (pH = 8.3 to 8.7) exposure conditions for a duration of 148 days (including 28 days of portable water curing period). Overall, 30% of the ternary mixture based on WCP prioritization, 50% adhere mortar-based RCA, and 3% of nano-silica prioritization steam treatment (3 h) demonstrated the best performance in terms of both mechanical and durability aspects. The study concluded that due to its improved performance, the innovative nano-silica priority steam treatment approach could replace 100% of RCA in concrete. Furthermore, treated RCA being advantageous because of easy adoptable technique for real-time practices as well as maintaining consistency regards RCA characteristics throughout concrete mixture be the challenge.
p-Compactness of Bloch maps
Authors: Jiménez-Vargas A. , Ruiz-Casternado D. 
Published: February 2024

AbstractInfluenced by the concept of a p-compact operator due to Sinha and Karn (Stud Math 150(1): 17–33, 2002), we introduce p-compact Bloch maps of the open unit disk $$\mathbb {D}\subseteq \mathbb {C}$$

D
⊆
C

to a complex Banach space X, and obtain its most outstanding properties: surjective Banach ideal property, Möbius invariance, linearisation on the Bloch-free Banach space over $$\mathbb {D}$$
D
, inclusion properties, factorisation of their derivatives, and transposition on the normalized Bloch space. We also present right p-nuclear Bloch maps of $$\mathbb {D}$$
D
to X and study its relation with p-compact Bloch maps.