bluuebunny/crossref_metadata_2025_split huggingface dataset:
Enhancing durability and sustainable preservation of Egyptian stone monuments using metabolites produced by Streptomyces exfoliatus
Authors: Abd-Elhalim Basma T. , Hemdan Bahaa A. , El-Sayed Salwa M. , Ahmed Mahgoub A. , Maan Sodaf A. , Abu-Hussien Samah H. 
Published: June 2023

AbstractDespite their threatens for Egyptian stone monuments, A few studies focused on using biocontrol agents against deteriorative fungi and bacteria instead of using chemical assays that leave residuals leading to human toxicity and environmental pollution. This work aims to isolate and identify fungal and bacterial isolates that showed deteriorative activities from stone monuments in Temple of Hathor, Luxor, Egypt, as well as determine the inhibitory activity of metabolites produced by Streptomyces exfoliatus SAMAH 2021 against the identified deteriorative fungal and bacterial strains. Moreover, studying the spectral analysis, toxicological assessment of metabolites produced by S. exfoliatus SAMAH 2021 against health human cell fibroblast, and colorimetric measurements on the selected stone monuments. Ten samples were collected from Temple of Hathor, Luxor, Egypt. Three fungal isolates and one bacterial isolate were obtained and identified as A. niger isolate Hathor 2, C. fioriniae strain Hathor 3, P. chrysogenum strain HATHOR 1, and L. sphaericus strain Hathor 4, respectively. Inhibitory potential of the metabolites in all concentrations used (100–25%) against the recommended antibiotics (Tetracycline 10 µg/ml and Doxycycline (30 µg/ml) showed an inhibitory effect toward all tested deteriorative pathogens with a minimum inhibition concentration (MIC) of 25%. Cytotoxicity test confirmed that microbial filtrate as the antimicrobial agent was safe for healthy human skin fibroblast with IC50 of < 100% and cell viability of 97%. Gas chromatography analysis recorded the existence of thirteen antimicrobial agents, Cis-vaccenic acid; 1,2-Benzenedicarboxylic acid; ç-Butyl-ç-butyrolactone and other compounds. Colorimetric measurements confirmed no color or surface change for the limestone-treated pieces. The use of the metabolite of microbial species antimicrobial as a biocontrol agent raises contemporary issues concerning the bio-protection of the Egyptian monuments to reduce chemical formulas that are toxic to humans and pollute the environment. Such serious problems need further investigation for all kinds of monuments.
Paleoamerican exploitation of extinct megafauna revealed through immunological blood residue and microwear analysis, North and South Carolina, USA
Authors: Moore Christopher R. , Kimball Larry R. , Goodyear Albert C. , Brooks Mark J. , Daniel I. Randolph , West Allen , Taylor Sean G. , Weber Kiersten J. , Fagan John L. , Walker Cam M. 
Published: June 2023

AbstractPrevious immunological studies in the eastern USA have failed to establish a direct connection between Paleoamericans and extinct megafauna species. The lack of physical evidence for the presence of extinct megafauna begs the question, did early Paleoamericans regularly hunt or scavenge these animals, or were some megafauna already extinct? In this study of 120 Paleoamerican stone tools from across North and South Carolina, we investigate this question using crossover immunoelectrophoresis (CIEP). We find immunological support for the exploitation of extant and extinct megafauna, including Proboscidea, Equidae, and Bovidae (possibly Bison antiquus), on Clovis points and scrapers, as well as possible early Paleoamerican Haw River points. Post-Clovis points tested positive for Equidae and Bovidae but not Proboscidea. Microwear results are consistent with projectile usage, butchery, fresh- and dry hide scraping, the use of ochre-coated dry hides for hafting, and dry hide sheath wear. This study represents the first direct evidence of the exploitation of extinct megafauna by Clovis and other Paleoamerican cultures in the Carolinas and more broadly, across the eastern United States, where there is generally poor to non-existent faunal preservation. Future CIEP analysis of stone tools may provide evidence on the timing and demography of megafaunal collapse leading to eventual extinction.
Possible seasonal and diurnal modulation of Gammarus pulex (Crustacea, Amphipoda) drift by microsporidian parasites
Authors: Prati Sebastian , Enß Julian , Grabner Daniel S. , Huesken Annabell , Feld Christian K. , Doliwa Annemie , Sures Bernd 
Published: June 2023

AbstractIn lotic freshwater ecosystems, the drift or downstream movement of animals (e.g., macroinvertebrates) constitutes a key dispersal pathway, thus shaping ecological and evolutionary patterns. There is evidence that macroinvertebrate drift may be modulated by parasites. However, most studies on parasite modulation of host drifting behavior have focused on acanthocephalans, whereas other parasites, such as microsporidians, have been largely neglected. This study provides new insight into possible seasonal and diurnal modulation of amphipod (Crustacea: Gammaridae) drift by microsporidian parasites. Three 72 h drift experiments were deployed in a German lowland stream in October 2021, April, and July 2022. The prevalence and composition of ten microsporidian parasites inGammarus pulexclade E varied seasonally, diurnally, and between drifting and stationary specimens ofG. pulex. Prevalence was generally higher in drifting amphipods than in stationary ones, mainly due to differences in host size. However, for two parasites, the prevalence in drift samples was highest during daytime suggesting changes in host phototaxis likely related to the parasite’s mode of transmission and site of infection. Alterations in drifting behavior may have important implications forG. pulexpopulation dynamics and microsporidians’ dispersal. The underlying mechanisms are more complex than previously thought.
The interactive effects of extreme temperatures and PM2.5 pollution on mortalities in Jiangsu Province, China
Authors: Zhou Lian , Wang Yuning , Wang Qingqing , Ding Zhen , Jin Hui , Zhang Ting , Zhu Baoli 
Published: June 2023

AbstractExposure to extreme temperatures or fine particles is associated with adverse health outcomes but their interactive effects remain unclear. We aimed to explore the interactions of extreme temperatures and PM2.5 pollution on mortalities. Based on the daily mortality data collected during 2015–2019 in Jiangsu Province, China, we conducted generalized linear models with distributed lag non-linear model to estimate the regional-level effects of cold/hot extremes and PM2.5 pollution. The relative excess risk due to interaction (RERI) was evaluated to represent the interaction. The relative risks (RRs) and cumulative relative risks (CRRs) of total and cause-specific mortalities associated with hot extremes were significantly stronger (p < 0.05) than those related to cold extremes across Jiangsu. We identified significantly higher interactions between hot extremes and PM2.5 pollution, with the RERI range of 0.00–1.15. The interactions peaked on ischaemic heart disease (RERI = 1.13 [95%CI: 0.85, 1.41]) in middle Jiangsu. For respiratory mortality, RERIs were higher in females and the less educated. The interaction pattern remained consistent when defining the extremes/pollution with different thresholds. This study provides a comprehensive picture of the interactions between extreme temperatures and PM2.5 pollution on total and cause-specific mortalities. The projected interactions call for public health actions to face the twin challenges, especially the co-appearance of hot extremes and PM pollution.
Mechanical characteristics analysis and control algorithm for floating raft system with mass variation
Authors: Shi Liang , Cheng Guanghui , Bu Wenjun 
Published: June 2023

AbstractThe ship floating raft system adopts the integrated design of large liquid tanks and rafts, which can optimize the arrangement in the cabin and increase the intermediate mass of the system to achieve efficient vibration isolation of equipment. One of the major challenges is that the change of liquid mass in the tank will cause displacement of the raft, which will change the modal characteristics of the system and affect the stability of the vibration isolation system performance. This paper establishes a mechanical analysis model of a floating raft system under time-varying liquid mass conditions. Taking a ship variable mass floating raft system as the research object, the effect of mass change on the characteristics of raft displacement, isolator load distribution, and modal frequency of the vibration isolation system is analyzed. The analysis shows that when the liquid tank goes from full load to no-load state, its mass change accounts for 40% of the total mass of the raft, which will cause a large displacement of the raft and change the low order modal frequency of the system, bringing the risk of equipment safety and vibration isolation performance degradation. Therefore, an adaptive variable load control method is proposed to realize the raft attitude balance and load equalization optimization under the variable mass condition of the floating raft air spring system. The test results show that the proposed control method can automatically adapt to the large mass gradual change from full load to no load of the liquid tank on the raft, and control the displacement of the raft structure from about 10 mm to 1.5 mm, which effectively ensures the stability of the air spring system performance.
Enhancing heat transfer in solar-powered ships: a study on hybrid nanofluids with carbon nanotubes and their application in parabolic trough solar collectors with electromagnetic controls
Authors: Obalalu A. M. , Memon M. Asif , Olayemi O. A. , Olilima J. , Fenta Amsalu 
Published: June 2023

AbstractThe aim of this research is to explore the use of solar-powered ships (SPS) as a means to reduce greenhouse gas emissions and fossil fuel dependency in the maritime industry. The study focuses on improving the heat transfer efficiency in SPS by employing hybrid nanofluids (HNF) containing carbon nanotubes (CNTs). Additionally, a novel approach utilizing renewable energy and electromagnetic control is proposed to enhance the performance of SPS. The research implements the non-Newtonian Maxwell type and Cattaneo–Christov heat flux model in parabolic trough solar collectors used for ships. The study conducts theoretical experiments and simulations to evaluate the thermal conductivity and viscosity of the CNT-based HNF. Various properties, including solar thermal radiation, viscous dissipation, slippery velocity, and porous media, are assessed to determine the effectiveness of thermal transport in SPS. The research employs similarity variables to simplify the complex partial differential equations into ordinary differential equations and solves them using the Chebyshev collocation spectral method. The results indicate that the MWCNT-SWCNT/EO hybrid nanofluid significantly improves the thermal conductivity, thereby enhancing heat transfer. The HNF exhibits an efficiency rate of approximately 1.78% with a minimum efficiency rate of 2.26%.
An integrative review on the acceptance of artificial intelligence among healthcare professionals in hospitals
Authors: Lambert Sophie Isabelle , Madi Murielle , Sopka Saša , Lenes Andrea , Stange Hendrik , Buszello Claus-Peter , Stephan Astrid 
Published: June 2023

AbstractArtificial intelligence (AI) in the domain of healthcare is increasing in prominence. Acceptance is an indispensable prerequisite for the widespread implementation of AI. The aim of this integrative review is to explore barriers and facilitators influencing healthcare professionals’ acceptance of AI in the hospital setting. Forty-two articles met the inclusion criteria for this review. Pertinent elements to the study such as the type of AI, factors influencing acceptance, and the participants’ profession were extracted from the included studies, and the studies were appraised for their quality. The data extraction and results were presented according to the Unified Theory of Acceptance and Use of Technology (UTAUT) model. The included studies revealed a variety of facilitating and hindering factors for AI acceptance in the hospital setting. Clinical decision support systems (CDSS) were the AI form included in most studies (n = 21). Heterogeneous results with regard to the perceptions of the effects of AI on error occurrence, alert sensitivity and timely resources were reported. In contrast, fear of a loss of (professional) autonomy and difficulties in integrating AI into clinical workflows were unanimously reported to be hindering factors. On the other hand, training for the use of AI facilitated acceptance. Heterogeneous results may be explained by differences in the application and functioning of the different AI systems as well as inter-professional and interdisciplinary disparities. To conclude, in order to facilitate acceptance of AI among healthcare professionals it is advisable to integrate end-users in the early stages of AI development as well as to offer needs-adjusted training for the use of AI in healthcare and providing adequate infrastructure.
Generalized precursor prediction boosts identification rates and accuracy in mass spectrometry based proteomics
Authors: Scott Aaron M. , Karlsson Christofer , Mohanty Tirthankar , Hartman Erik , Vaara Suvi T. , Linder Adam , Malmström Johan , Malmström Lars 
Published: June 2023

AbstractData independent acquisition mass spectrometry (DIA-MS) has recently emerged as an important method for the identification of blood-based biomarkers. However, the large search space required to identify novel biomarkers from the plasma proteome can introduce a high rate of false positives that compromise the accuracy of false discovery rates (FDR) using existing validation methods. We developed a generalized precursor scoring (GPS) method trained on 2.75 million precursors that can confidently control FDR while increasing the number of identified proteins in DIA-MS independent of the search space. We demonstrate how GPS can generalize to new data, increase protein identification rates, and increase the overall quantitative accuracy. Finally, we apply GPS to the identification of blood-based biomarkers and identify a panel of proteins that are highly accurate in discriminating between subphenotypes of septic acute kidney injury from undepleted plasma to showcase the utility of GPS in discovery DIA-MS proteomics.
SENP2 restrains the generation of pathogenic Th17 cells in mouse models of colitis
Authors: Yang Tsan-Tzu , Chiang Ming-Feng , Chang Che-Chang , Yang Shii-Yi , Huang Shih-Wen , Liao Nan-Shih , Shih Hsiu-Ming , Hsu Wei , Lin Kuo-I 
Published: June 2023

AbstractThe molecular mechanisms contributing to the regulation of Th17-mediated inflammation remain underexplored. We here report a SUMO-specific protease (SENP)2-mediated pathway induced in pathogenic Th17 cells that restricts the pathogenesis of inflammatory colitis. SENP2 regulates the maturation of small ubiquitin-like modifiers (SUMO) and recycles SUMO from the substrate proteins. We find higher levels of SENP2 in pathogenic Th17 cells. By deleting Senp2 in T-cell lineages in mice, we demonstrate that the lack of Senp2 exacerbates the severity of experimental colitis, which is linked to elevated levels of GM-CSF+IL-17A+ pathogenic Th17 cells and more severe dysbiosis of the intestinal microbiome. Adoptive transfer experiments demonstrate the cell-autonomous effect of Senp2 in restraining Th17 differentiation and colitis. The enzymatic activity of SENP2 is important for deSUMOylation of Smad4, which reduces Smad4 nuclear entry and Rorc expression. Our findings reveal a SENP2-mediated regulatory axis in the pathogenicity of Th17 cells.
Retrosynthetic planning with experience-guided Monte Carlo tree search
Authors: Hong Siqi , Zhuo Hankz Hankui , Jin Kebing , Shao Guang , Zhou Zhanwen 
Published: June 2023

AbstractIn retrosynthetic planning, the huge number of possible routes to synthesize a complex molecule using simple building blocks leads to a combinatorial explosion of possibilities. Even experienced chemists often have difficulty to select the most promising transformations. The current approaches rely on human-defined or machine-trained score functions which have limited chemical knowledge or use expensive estimation methods for guiding. Here we propose an experience-guided Monte Carlo tree search (EG-MCTS) to deal with this problem. Instead of rollout, we build an experience guidance network to learn knowledge from synthetic experiences during the search. Experiments on benchmark USPTO datasets show that, EG-MCTS gains significant improvement over state-of-the-art approaches both in efficiency and effectiveness. In a comparative experiment with the literature, our computer-generated routes mostly matched the reported routes. Routes designed for real drug compounds exhibit the effectiveness of EG-MCTS on assisting chemists performing retrosynthetic analysis.
Topological invariance in whiteness optimisation
Authors: Haataja Johannes S. , Jacucci Gianni , Parton Thomas G. , Schertel Lukas , Vignolini Silvia 
Published: June 2023

AbstractMaximizing the scattering of visible light within disordered nano-structured materials is essential for commercial applications such as brighteners, while also testing our fundamental understanding of light-matter interactions. The progress in the research field has been hindered by the lack of understanding how different structural features contribute to the scattering properties. Here we undertake a systematic investigation of light scattering in correlated disordered structures. We demonstrate that the scattering efficiency of disordered systems is mainly determined by topologically invariant features, such as the filling fraction and correlation length, and residual variations are largely accounted by the surface-averaged mean curvature of the systems. Optimal scattering efficiency can thus be obtained from a broad range of disordered structures, especially when structural anisotropy is included as a parameter. These results suggest that any disordered system can be optimised for whiteness and give comparable performance, which has far-reaching consequences for the industrial use of low-index materials for optical scattering.
Many-body quantum chaos in stroboscopically-driven cold atoms
Authors: Dağ Ceren B. , Mistakidis Simeon I. , Chan Amos , Sadeghpour H. R. 
Published: June 2023

AbstractIn quantum chaotic systems, the spectral form factor (SFF), defined as the Fourier transform of two-level spectral correlation function, is known to follow random matrix theory (RMT), namely a ‘ramp’ followed by a ‘plateau’ in late times. Recently, a generic early-time deviation from RMT, so-called the ‘bump’, was shown to exist in random quantum circuits as toy models for many-body quantum systems. We demonstrate the existence of ‘bump-ramp-plateau’ behavior in the SFF for a number of paradigmatic and stroboscopically-driven 1D cold-atom models: spinless and spin-1/2 Bose-Hubbard models, and nonintegrable spin-1 condensate with contact or dipolar interactions. We find that the scaling of the many-body Thouless time tTh —the onset of RMT—, and the bump amplitude are more sensitive to variations in atom number than the lattice size regardless of the hyperfine structure, the symmetry classes, or the choice of driving protocol. Moreover, tTh scaling and the increase of the bump amplitude in atom number are significantly slower in spinor gases than interacting bosons in 1D optical lattices, demonstrating the role of locality. We obtain universal scaling functions of SFF which suggest power-law behavior for the bump regime in quantum chaotic cold-atom systems, and propose an interference measurement protocol.
Integration of urban science and urban climate adaptation research: opportunities to advance climate action
Authors: Lobo José , Aggarwal Rimjhim M. , Alberti Marina , Allen-Dumas Melissa , Bettencourt Luís M. A. , Boone Christopher , Brelsford Christa , Broto Vanesa Castán , Eakin Hallie , Bagchi-Sen Sharmistha , Meerow Sara , D’Cruz Celine , Revi Aromar , Roberts Debra C. , Smith Michael E. , York Abigail , Lin Tao , Bai Xuemei , Solecki William , Pataki Diane , Tapia Luís Bojorquez , Rockman Marcy , Wolfram Marc , Schlosser Peter , Gauthier Nicolas 
Published: June 2023

AbstractThere is a growing recognition that responding to climate change necessitates urban adaptation. We sketch a transdisciplinary research effort, arguing that actionable research on urban adaptation needs to recognize the nature of cities as social networks embedded in physical space. Given the pace, scale and socioeconomic outcomes of urbanization in the Global South, the specificities and history of its cities must be central to the study of how well-known agglomeration effects can facilitate adaptation. The proposed effort calls for the co-creation of knowledge involving scientists and stakeholders, especially those historically excluded from the design and implementation of urban development policies.
Band gap predictions of double perovskite oxides using machine learning
Authors: Talapatra Anjana , Uberuaga Blas Pedro , Stanek Christopher Richard , Pilania Ghanshyam 
Published: June 2023

AbstractThe compositional and structural variety inherent to oxide perovskites spawn wide-ranging applications. In perovskites, the band gap Eg, a key material parameter for these applications, can be optimally controlled by varying the composition. Here, we implement a hierarchical screening process in which two cross-validated and predictive machine learning models for band gap classification and regression, trained using exhaustive datasets that span 68 elements of the periodic table, are applied sequentially. The classification model separates wide band gap materials, with Eg ≥ 0.5 eV, from materials which have zero or relatively small band gaps, namely Eg < 0.5 eV, and the second regression model quantitatively predicts the gap value of the wide band gap compounds. The study down-selects 13,589 cubic oxide perovskite compositions that are predicted to be experimentally formable, thermodynamically stable, and have a wide band gap. Of these, a subset of 310 compounds, which are predicted to be stable and formable with a confidence greater than 90%, are identified for further investigation. Our models are methodically analyzed via performance metrics and inter-dependence of model features to gain physical insight into the band gap prediction problem. Design maps to identify the variation of band gap with substitution of different elements are also presented.
Enhancing resilience by reducing critical load loss via an emergent trading framework considering possible resources isolation under typhoon
Authors: Wu Yingjun , Liu Chengjun , Lin Zhiwei , Ru Yingtao , Huang Tao 
Published: June 2023

AbstractLeveraging distributed resources to enhance distribution network (DN) resilience is an effective measure in response to natural disasters. However, the willingness and economy of distributed resources are typically ignored. To address this issue, this paper proposes an emergent trading framework that uses parking lots (PLs) as resources to provide power support to critical loads (CLs) in a blackout due to typhoons. In this trading framework, an evolutionary Stackelberg game‐based trading model is established to consider maximizing all stakeholders’ economic benefits, considering possible resources isolation under typical fault scenarios caused by typhoons, and a benefit allocation mechanism is proposed for all stakeholders to motivate all stakeholders to participate in the trading. This framework allows that critical loads could reduce their load loss, parking lots could receive adequate compensation to stimulate them to participate in the trading, and distribution utility could ensure its economic benefits. Furthermore, an iterative evolutionary‐Stackelberg solution set‐up is applied to obtain the equilibria of the proposed framework. Simulation results on the modified IEEE 69‐bus test system and IEEE 123‐bus test system reveal the validity of the proposed method.