bluuebunny/crossref_metadata_2025_split huggingface dataset:
Experimental analysis of rotating bridge structural responses to existing railway train loads via time–frequency and Hilbert–Huang transform energy spectral analysis
Authors: Liu Xu , Wu Honggang , Zhao Shouquan , Yang Xuehu 
Published: April 2024

AbstractWith the rapid development of national infrastructure projects, there has been a significant increase in intersecting lines in transportation construction. As a result, rotating bridges are increasingly used in engineering projects that span existing railway lines. In order to study the spatial response characteristics and vibration wave transmission mechanisms of the rotating bridge structure under the loading of existing railway trains, field experiments and numerical analyses were conducted. The response characteristics of these bridges were investigated under different types and speeds of adjacent existing lines. A comprehensive methodology has been proposed, integrating the time domain spectrum and the Hilbert–Huang Transform (HHT) energy spectrum for signal processing and vibration analysis. The analysis was carried out using MATLAB 2018a software. This methodology was applied to analyze the test data. The results show that significant resonance phenomenon occurs in the girders of the rotating bridge under the loading of trains on the existing line. The low-frequency component f1 (2–5 Hz) is the primary factor contributing to the amplification of the acceleration response in the rotating bridge, while f3 (10–13 Hz) plays a secondary role. The frequency distribution characteristics of vibration waves caused by train loads on the existing line have a significant influence on the acceleration response of the rotating bridge's girders. The predominant frequency of vibration waves at each measuring point along the transmission path shows a trend of decreasing → increasing → decreasing. The impact on the rotating bridge structure of vibration waves generated by low-speed freight trains on existing railways is greater. The research findings are of great importance for studying the dynamic response of rotating bridges adjacent to existing railway lines.
Urban segregation on multilayered transport networks: a random walk approach
Authors: Neira Mateo , Molinero Carlos , Marshall Stephen , Arcaute Elsa 
Published: April 2024

AbstractWe present a novel method for analysing socio-spatial segregation in cities by considering constraints imposed by transportation networks. Using a multilayered network approach, we model the interaction probabilities of socio-economic groups with random walks and Lévy flights. This method allows for evaluation of new transport infrastructure’s impact on segregation while quantifying each network’s contribution to interaction opportunities. The proposed random walk segregation index measures the probability of individuals encountering diverse social groups based on their available means of transit via random walks. The index incorporates temporal constraints in urban mobility with a parameter, $$\alpha \in [0,1)$$

α
∈
[
0
,
1
)

, of the probability of the random walk continuing at each time step. By applying this to a toy model and conducting a sensitivity analysis, we explore how the index changes dependent on this temporal constraint. When the parameter equals zero, the measure simplifies to an isolation index. When the parameter approaches one it represents the city’s overall socio-economic distribution by mirroring the steady-state of the random walk process. Using Cuenca, Ecuador as a case study, we illustrate the method’s applicability in transportation planning as a valuable tool for policymakers, addressing spatial distribution of socio-economic groups and the connectivity of existing transport networks, thus promoting equitable interactions throughout the city.
Fiber optics passive monitoring of groundwater temperature reveals three-dimensional structures in heterogeneous aquifers
Authors: Furlanetto Davide , Camporese Matteo , Schenato Luca , Costa Leonardo , Salandin Paolo 
Published: April 2024

AbstractAlluvial aquifers often exhibit highly conductive embedded formations that can act as preferential pathways for the transport of solutes. In this context, a detailed subsurface characterization becomes crucial for an effective monitoring of groundwater quality and early detection of contaminants. However, small-scale heterogeneities are seldom detected by traditional nondestructive investigations. Heat propagation in porous media can be a relatively inexpensive tracer for groundwater flow, potentially offering valuable information in various applications. In this study, we applied passive Fiber Optics Distributed Temperature Sensing (FO-DTS) to a group of observation wells in a highly heterogeneous phreatic aquifer to uncover structures with different hydraulic conductivity, relying on their response to temperature fluctuations triggered by natural and anthropogenic forcings. A comprehensive data analysis approach, combining statistical methods and physics-based numerical modeling, allowed for a three-dimensional characterization of the subsurface at the experimental site with unprecedentedly high resolution.
Highly biomimetic spiking neuron using SiGe heterojunction bipolar transistors for energy-efficient neuromorphic systems
Authors: Kim Yijoon , Kim Hyangwoo , Oh Kyounghwan , Park Ju Hong , Baek Chang-Ki 
Published: April 2024

AbstractWe demonstrate a highly biomimetic spiking neuron capable of fast and energy-efficient neuronal oscillation dynamics. Our simple neuron circuit is constructed using silicon–germanium heterojunction based bipolar transistors (HBTs) with nanowire structure. The HBT has a hysteresis window with steep switching characteristics and high current margin in the low voltage range, which enables a high spiking frequency (~ 245 kHz) with low energy consumption (≤ 1.37 pJ/spike). Also, gated structure achieves a stable balance in the activity of the neural system by incorporating both excitatory and inhibitory signal. Furthermore, inhibition of multiple strengths can be realized by adjusting the integration time according to the amplitude of the inhibitory signal. In addition, the spiking frequency can be tuned by mutually controlling the hysteresis window in the HBTs. These results ensure the sparse activity and homeostasis of neural networks.
Antioxidant capacity sources of soils under different land uses
Authors: Ćwieląg-Piasecka Irmina , Łyczko Jacek , Jamroz Elżbieta , Kocowicz Andrzej , Kawałko Dorota 
Published: April 2024

AbstractAntioxidants (AOX) in soils originate mainly from secondary plant metabolites and are pivotal in many redox processes in environment, maintaining soil quality. Still, little is known about the influence of land uses on their accumulation in soil. The aim of the paper was to determine the content of these redox-active compounds in the extracts of A horizons of abandoned fallows, arable and woodland soils. Total antioxidant capacity (TAC) of soils under various uses and vegetation was evaluated in different soil extracts using Folin-Ciocâlteu method. The contribution of humic acids to TAC was determined and antioxidant profiles estimated using the chromatographic GC–MS method. Forest soils exhibited the highest TAC (15.5 mg g−1) and AOX contents (4.34 mg g−1), which were positively correlated with soil organic carbon content. It was estimated that humic acids contribute to over 50% of TAC in soils. The main phenolics in woodland A horizons were isovanillic and p-hydroxybenzoic acid (p-HA), while esculetin and p-HA predominated in the abandoned fallows due to the prevalence of herbaceous vegetation. Cultivated soils were the most abundant in p-HA (56.42%). In the studied topsoils, there were considerable amounts of aliphatic organic matter, which role in redox processes should be further evaluated.
Incidence of coronary heart disease among remote workers: a nationwide web-based cohort study
Authors: Zaitsu Masayoshi , Ishimaru Tomohiro , Tsushima Saki , Muramatsu Keiji , Ando Hajime , Nagata Tomohisa , Eguchi Hisashi , Tateishi Seiichiro , Tsuji Mayumi , Fujino Yoshihisa 
Published: April 2024

AbstractCoronary heart disease (CHD) risk is influenced by socioeconomic status-related parameters, particularly occupation. We investigated occupational gaps in CHD risk and how the introduction of remote work moderated the observed occupational differences in CHD risk during the coronavirus disease 2019 pandemic in Japan. Data from a web-based, nationwide cohort study, comprising 17,640 workers (aged 20–65 years) with baseline data from December 2020, were analyzed. Participants were grouped by occupation as upper-level nonmanual workers (managers/professionals) and others (reference group). The primary outcome was CHD (angina pectoris/myocardial infarction) onset retrospectively confirmed at the 1-year follow-up survey. Upper-level nonmanual workers exhibited a higher CHD incidence than others (2.3% vs. 1.7%). This association was pronounced in the younger (20–49 years) population, with a significant CHD risk (adjusted risk ratio = 1.88). Upper-level nonmanual workers exhibited nearly 15% higher remote work prevalence, with a significant remote work-related CHD risk (adjusted risk ratio = 1.92). The mediating effects of remote work explained an overall disparity of 32% among the younger population. Occupational gaps in CHD incidence in Japan differ from those in Western countries, where upper-level nonmanual workers have lower cardiovascular risk. In Japan, remote work can mediate CHD risk in the younger population of upper-level nonmanual workers.
Longitudinal markers of cerebral amyloid angiopathy and related inflammation in rTg-DI rats
Authors: Schrader Joseph M. , Xu Feng , Agostinucci Kevin J. , DaSilva Nicholas A. , Van Nostrand William E. 
Published: April 2024

AbstractCerebral amyloid angiopathy (CAA) is a prevalent vascular dementia and common comorbidity of Alzheimer’s disease (AD). While it is known that vascular fibrillar amyloid β (Aβ) deposits leads to vascular deterioration and can drive parenchymal CAA related inflammation (CAA-ri), underlying mechanisms of CAA pathology remain poorly understood. Here, we conducted brain regional proteomic analysis of early and late disease stages in the rTg-DI CAA rat model to gain molecular insight to mechanisms of CAA/CAA-ri progression and identify potential brain protein markers of CAA/CAA-ri. Longitudinal brain regional proteomic analysis revealed increased differentially expressed proteins (DEP) including ANXA3, HTRA1, APOE, CST3, and CLU, shared between the cortex, hippocampus, and thalamus, at both stages of disease in rTg-DI rats. Subsequent pathway analysis indicated pathway enrichment and predicted activation of TGF-β1, which was confirmed by immunolabeling and ELISA. Further, we identified numerous CAA related DEPs associate with astrocytes (HSPB1 and MLC1) and microglia (ANXA3, SPARC, TGF-β1) not previously associated with astrocytes or microglia in other AD models, possibly indicating that they are specific to CAA-ri. Thus, the data presented here identify several potential brain protein biomarkers of CAA/CAA-ri while providing novel molecular and mechanistic insight to mechanisms of CAA and CAA-ri pathological progression and glial cell mediated responses.
Microbe cultivation guidelines to optimize rhamnolipid applications
Authors: Kłosowska-Chomiczewska Ilona E. , Macierzanka Adam , Parchem Karol , Miłosz Pamela , Bladowska Sonia , Płaczkowska Iga , Hewelt-Belka Weronika , Jungnickel Christian 
Published: April 2024

AbstractIn the growing landscape of interest in natural surfactants, selecting the appropriate one for specific applications remains challenging. The extensive, yet often unsystematized, knowledge of microbial surfactants, predominantly represented by rhamnolipids (RLs), typically does not translate beyond the conditions presented in scientific publications. This limitation stems from the numerous variables and their interdependencies that characterize microbial surfactant production. We hypothesized that a computational recipe for biosynthesizing RLs with targeted applicational properties could be developed from existing literature and experimental data. We amassed literature data on RL biosynthesis and micellar solubilization and augmented it with our experimental results on the solubilization of triglycerides (TGs), a topic underrepresented in current literature. Utilizing this data, we constructed mathematical models that can predict RL characteristics and solubilization efficiency, represented as logPRL = f(carbon and nitrogen source, parameters of biosynthesis) and logMSR = f(solubilizate, rhamnolipid (e.g. logPRL), parameters of solubilization), respectively. The models, characterized by robust R2 values of respectively 0.581–0.997 and 0.804, enabled the ranking of descriptors based on their significance and impact—positive or negative—on the predicted values. These models have been translated into ready-to-use calculators, tools designed to streamline the selection process for identifying a biosurfactant optimally suited for intended applications.
AI-driven remote sensing enhances Mediterranean seagrass monitoring and conservation to combat climate change and anthropogenic impacts
Authors: Chowdhury Masuma , Martínez-Sansigre Alejo , Mole Maruška , Alonso-Peleato Eduardo , Basos Nadiia , Blanco Jose Manuel , Ramirez-Nicolas Maria , Caballero Isabel , de la Calle Ignacio 
Published: April 2024

AbstractSeagrasses are undergoing widespread loss due to anthropogenic pressure and climate change. Since 1960, the Mediterranean seascape lost 13–50% of the areal extent of its dominant and endemic seagrass-Posidonia oceanica, which regulates its ecosystem. Many conservation and restoration projects failed due to poor site selection and lack of long-term monitoring. Here, we present a fast and efficient operational approach based on a deep-learning artificial intelligence model using Sentinel-2 data to map the spatial extent of the meadows, enabling short and long-term monitoring, and identifying the impacts of natural and human-induced stressors and changes at different timescales. We apply ACOLITE atmospheric correction to the satellite data and use the output to train the model along with the ancillary data and therefore, map the extent of the meadows. We apply noise-removing filters to enhance the map quality. We obtain 74–92% of overall accuracy, 72–91% of user’s accuracy, and 81–92% of producer’s accuracy, where high accuracies are observed at 0–25 m depth. Our model is easily adaptable to other regions and can produce maps in in-situ data-scarce regions, providing a first-hand overview. Our approach can be a support to the Mediterranean Posidonia Network, which brings together different stakeholders such as authorities, scientists, international environmental organizations, professionals including yachting agents and marinas from the Mediterranean countries to protect all P. oceanica meadows in the Mediterranean Sea by 2030 and increase each country’s capability to protect these meadows by providing accurate and up-to-date maps to prevent its future degradation.
Occurrence, distribution, and ecological risk assessment of heavy metals in Chao Phraya River, Thailand
Authors: Niampradit Sarima , Kiangkoo Nuttapohn , Mingkhwan Rachaneekorn , Kliengchuay Wissanupong , Worakhunpiset Suwalee , Limpananont Yanin , Hongsibsong Surat , Inthorn Duangrat , Tantrakarnapa Kraichat 
Published: April 2024

AbstractUnderstanding heavy metals in rivers is crucial, as their presence and distribution impact water quality, ecosystem health, and human well-being. This study examined the presence and levels of nine heavy metals (Cd, Cr, Cu, Fe, Hg, Mn, Ni, Pb, and Zn) in 16 surface water samples along the Chao Phraya River, identifying Fe, Mn, Zn, and Cr as predominant metals. Although average concentrations in both rainy and dry seasons generally adhered to WHO guidelines, Mn exceeded these limits yet remained within Thailand’s acceptable standards. Seasonal variations were observed in the Chao Phraya River, and Spearman’s correlation coefficient analysis established significant associations between season and concentrations of heavy metals. The water quality index (WQI) demonstrated varied water quality statuses at each sampling point along the Chao Phraya River, indicating poor conditions during the rainy season, further deteriorating to very poor conditions in the dry season. The hazard potential index (HPI) was employed to assess heavy metal contamination, revealing that during the dry season in the estuary area, the HPI value exceeded the critical threshold index, indicating the presence of heavy metal pollution in the water and unsuitable for consumption. Using the species sensitivity distribution model, an ecological risk assessment ranked the heavy metals’ HC5 values as Pb > Zn > Cr > Cu > Hg > Cd > Ni, identifying nickel as the most detrimental and lead as the least toxic. Despite Cr and Zn showing a moderate risk, and Cu and Ni posing a high risk to aquatic organisms, the main contributors to ecological risk were identified as Cu, Ni, and Zn, suggesting a significant potential ecological risk in the Chao Phraya River’s surface water. The results of this study provide fundamental insights that can direct future actions in preventing and managing heavy metal pollution in the river ecosystem.
Overburden failure and water–sand mixture outburst conditions of weakly consolidated overlying strata in Dananhu No.7 coal mine
Authors: Zhu Jingzhong , Li Wenping , Teng Bo , Lu Qinggang , Li Dongding , Li Liangning 
Published: April 2024

AbstractThis study presents a case of weakly consolidated strata developed in Dananhu No.7 coal mine. Using a combination of numerical simulation, field measurement comparison, and the critical hydraulic gradient criterion, we investigate the overburden failure and the risk possibility of water–sand mixture inrush during excavation. The following are the principal findings: (1) Weakly consolidated rocks have poor physical characteristics, particularly when they are mudded and disintegrated after encountering water, which may become a favorable source of water–sand inrush; (2) The water-conducting zone develops to a height of 160.5 m with a crack-mining ratio of 15.29 times, extending upward to Toutunhe Formation aquifer. The predictions are consistent with measurements in adjacent mines with similar geological conditions; (3) Cracks without larger subsidence are developed at the front edge of the mining direction, and some parallel stepped cracks behind the goaf could be easily observed. Ground subsidence along the goaf center finally displays a symmetrically wide-gentle U shape; (4) The critical hydraulic gradient of Toutunhe Formation aquifer, aquifer above 3# coal seam, and aquifer of 3#–7# coal seam in Xishanyao Formation is 1.314, 1.351, and 1.380, the actual value is 0.692, 2.089, and 7.418 accordingly. It is inferred water–sand mixture outburst will not occur in Toutunhe Formation aquifer, while the potential risk exists in the aquifers of Xishanyao Formation. Through drainage and depressurization projects, a water–sand mixture outburst accident does not occur during excavation. This study reveals the overburden failure characteristics and the initiation mechanism of water–sand inrush in weakly cemented strata, as well as the internal relationship between them, which provides new research ideas for safe operation in other mining areas with similar geological conditions. The research work has certain practical guiding significance.
Understanding the errors made by artificial intelligence algorithms in histopathology in terms of patient impact
Authors: Evans Harriet , Snead David 
Published: April 2024

AbstractAn increasing number of artificial intelligence (AI) tools are moving towards the clinical realm in histopathology and across medicine. The introduction of such tools will bring several benefits to diagnostic specialities, namely increased diagnostic accuracy and efficiency, however, as no AI tool is infallible, their use will inevitably introduce novel errors. These errors made by AI tools are, most fundamentally, misclassifications made by a computational algorithm. Understanding of how these translate into clinical impact on patients is often lacking, meaning true reporting of AI tool safety is incomplete. In this Perspective we consider AI diagnostic tools in histopathology, which are predominantly assessed in terms of technical performance metrics such as sensitivity, specificity and area under the receiver operating characteristic curve. Although these metrics are essential and allow tool comparison, they alone give an incomplete picture of how an AI tool’s errors could impact a patient’s diagnosis, management and prognosis. We instead suggest assessing and reporting AI tool errors from a pathological and clinical stance, demonstrating how this is done in studies on human pathologist errors, and giving examples where available from pathology and radiology. Although this seems a significant task, we discuss ways to move towards this approach in terms of study design, guidelines and regulation. This Perspective seeks to initiate broader consideration of the assessment of AI tool errors in histopathology and across diagnostic specialities, in an attempt to keep patient safety at the forefront of AI tool development and facilitate safe clinical deployment.
A multifunctional display based on photo-responsive perovskite light-emitting diodes
Authors: Bao Chunxiong , Yuan Zhongcheng , Niu Wenxiao , Yang Jie , Wang Zijian , Yu Tao , Wang Jianpu , Gao Feng 
Published: April 2024

AbstractCurrent display screens are typically only used for information display, but can have a range of different sensors integrated into them for functions such as touch control, ambient light sensing and fingerprint sensing. Photo-responsive light-emitting diodes (LEDs), which can display information and respond to light excitation, could be used to develop future ultra-thin and large screen-to-body ratio screens. However, photo-response is difficult to achieve with conventional display technologies. Here, we report a multifunctional display that uses photo-responsive metal halide perovskite LEDs as pixels. The perovskite LED display can be simultaneously used as a touch screen, ambient light sensor and image sensor (including for fingerprint drawing) without integrating any additional sensors. The light-to-electricity conversion efficiency of the pixels also allow the display to act as a photovoltaic device that can charge the equipment.
Genetic associations of risk behaviours and educational achievement
Authors: Arellano Spano Michelle , Morris Tim T. , Davies Neil M. , Hughes Amanda 
Published: April 2024

AbstractRisk behaviours are common in adolescent and persist into adulthood, people who engage in more risk behaviours are more likely to have lower educational attainment. We applied genetic causal inference methods to explore the causal relationship between adolescent risk behaviours and educational achievement. Risk behaviours were phenotypically associated with educational achievement at age 16 after adjusting for confounders (−0.11, 95%CI: −0.11, −0.09). Genomic-based restricted maximum likelihood (GREML) results indicated that both traits were heritable and have a shared genetic architecture (Risk $${{{{{{\boldsymbol{h}}}}}}}^{{{{{{\boldsymbol{2}}}}}}}$$

h

2

= 0.18, 95% CI: −0.11,0.47; education $${{{{{{\boldsymbol{h}}}}}}}^{{{{{{\boldsymbol{2}}}}}}}$$

h

2

= 0.60, 95%CI: 0.50,0.70). Consistent with the phenotypic results, genetic variation associated with risk behaviour was negatively associated with education ($${{{{{{\boldsymbol{r}}}}}}}_{{{{{{\boldsymbol{g}}}}}}}$$

r

g

= −0.51, 95%CI: −1.04,0.02). Lastly, the bidirectional MR results indicate that educational achievement or a closely related trait is likely to affect risk behaviours PGI (β=−1.04, 95% CI: −1.41, −0.67), but we found little evidence that the genetic variation associated with risk behaviours affected educational achievement (β=0.00, 95% CI: −0.24,0.24). The results suggest engagement in risk behaviour may be partly driven by educational achievement or a closely related trait.