bluuebunny/crossref_metadata_2025_split huggingface dataset:
Straightforward microwave-assisted synthesis of ultrasmall gold nanoparticles acnhored on reduced graphene oxide for enhanced antibacterial application
Authors: Fathurrohman Pandji Zamzami , Kunarti Eko Sri , Wijayanti Nastiti , Santosa Sri Juari 
Published: June 2024

AbstractGraphene derivative materials, such as graphene oxide (GO) and reduced graphene oxide (rGO), have garnered significant attention from scientists for over two decades due to their distinctive characteristics and versatile applications across various fields, particularly in biomedical applications. Incorporating gold nanoparticles (AuNPs) into rGO sheets as rGO-Au nanocomposites further enhances its performance in biomedical applications. This study presents a rapid and efficient method for synthesizing ultrasmall AuNPs anchored on reduced graphene oxide (rGO-Au) using microwave irradiation and ascorbic acid. The optimum microwave treatment was 4 min, ensuring the highest GO reduction degree. Structural characterization by TEM reveals a distinctive architecture with ultrasmall AuNPs (average size of 2.2 nm) distributed on the rGO sheets. Interestingly, while the synthesized rGO-Au did not exhibit any antibacterial activities against both Escherichia coli and Staphylococcus aureus in disk diffusion assays, it demonstrated bacteriostatic effect at remarkably low concentrations when assessed by optical density measurement. The effective concentration of rGO-Au to inhibit E. coli growth was determined to be 2.5 ppm, while for S. aureus, it was 5 ppm, resulting in growth inhibition of 53.1% and 50.0%, respectively. These findings provide a straightforward synthesis route for rGO-Au nanocomposites and underscore the importance of AuNPs’ size and quantity in modulating antibacterial properties.
Sub-global equilibrium method for identification of elastic parameters based on digital image correlation results
Authors: Nowak Marcin , Szeptyński Paweł , Musiał Sandra , Maj Michał 
Published: June 2024

AbstractIn this work, a new, simple method is presented, which enables identification of material properties of solids basing on the digital image correlation (DIC) measurements. It may be considered as a simplified alternative of low computational complexity for the well-known finite element model updating (FEMU) method and virtual fields method (VFM). The idea of the introduced sub-global equilibrium (SGE) method is to utilize the fundamental concept and definition of internal forces and its equilibrium with appropriate set of external forces. This makes the method universal for the use in the description of a great variety of continua. The objective function is the measure of imbalance, namely the sum of squares of residua of equilibrium equations of external forces and internal forces determined for finite-sized part of the sample. It is then minimized with the use of the Nelder–Mead downhill simplex algorithm. The efficiency of the proposed SGE method is shown for two types of materials: 310 S austenitic steel and carbon-fiber-reinforced polymer (CFRP). The proposed method was also verified based on FE analysis showing error estimation.
Exploiting the margin: How capitalism fuels AI at the expense of minoritized groups
Authors: Colón Vargas Nelson 
Published: June 2024

AbstractThis paper explores the intricate relationship between capitalism, racial injustice, and artificial intelligence (AI), arguing that AI acts as a contemporary vehicle for age-old forms of exploitation. By linking historical patterns of racial and economic oppression with current AI practices, this study illustrates how modern technology perpetuates and deepens societal inequalities. It specifically examines how AI is implicated in the exploitation of marginalized communities through underpaid labor in the gig economy, the perpetuation of biases in algorithmic decision-making, and the reinforcement of systemic barriers that prevent these groups from benefiting equitably from technological advances. Furthermore, the paper discusses the role of AI in extending and intensifying the social, economic, and psychological burdens faced by these communities, highlighting the problematic use of AI in surveillance, law enforcement, and mental health contexts. The analysis concludes with a call for transformative changes in how AI is developed and deployed. Advocating for a reevaluation of the values driving AI innovation, the paper promotes an approach that integrates social justice and equity into the core of technological design and policy. This shift is crucial for ensuring that AI serves as a tool for societal improvement, fostering empowerment and healing rather than deepening existing divides.
How do short-term and long-term factors impact the aboveground biomass of grassland in Northern China?
Authors: Zhu Xiaoyu , An Yi , Qin Yifei , Li Yutong , Shao Changliang , Xu Dawei , Yan Ruirui , Zhou Wenneng , Xin Xiaoping 
Published: June 2024

AbstractThe aboveground biomass (AGB) of grassland, a crucial indicator of productivity, is anticipated to widespread changes in key ecosystem attributes, functions and dynamics. Variations in grassland AGB have been extensively documented across various spatial and temporal scales. However, a precise method to disentangle long-term effects from short-term effects on grassland AGB and assess the attribution of explanatory factors for AGB change remains elusive. This study aimed to quantify the impact of key climatic factors, soil properties, and grazing intensity on grassland AGB changes, utilizing data spanning the 1980s and the 2000s in Northern China. The Co-regression model was explored to separate the long-term effects and short-term effects of grassland AGB, while the Generalized Linear Model (GLM) was utilized to analyze the contributions of key variables to AGB. This approach effectively avoids issues related to regression to the mean and mathematical coupling. The results revealed that the influence of climatic variables, soil texture and grazing intensity on grassland AGB changes could be decomposed into long-term, short-term and random effects. Long-term effects explained 73.6% of AGB variation, whereas short-term effect only accounted for 5.9% of AGB change. Additionally, the short-term effect was divided into direct and indirect effects, with the direct effect explaining 1.3% of AGB variation, and the indirect effect explained 4.6% of AGB dynamics. The relative importance of key variables in grassland AGB was assessed, identifying soil parameters and precipitation as the main driving factors in the study area. This study introduces a robust methodology to enhance model performance in distinguishing long-term and short-term effects on grassland AGB, contributing to the sustainable development of grassland ecology in similar regions.
Using dialogue-centered approaches to community-engaged research: an application of dialectical inquiry
Authors: Sanders Catherine E. , Borron Abigail , Lamm Alexa J. , Harrell Ellen , Worley Barbara 
Published: June 2024

AbstractRural communities across the United States experience increased risk and prevalence of chronic diseases associated with both individual and community-based factors. Thus, there is a need for rural capacity development for chronic disease prevention. Traditional health promotion and intervention approaches often focus on diet-related health disparities from a positivist, evidence-based paradigm. To counter positivist bias within health promotion research, a hybridized approach is proposed using a critical-constructivist paradigm incorporating dialectical thinking, appreciative inquiry, and dialectical inquiry to address cultural and structural barriers, as well as community-based social norms, through evaluation of community-based health promotion interventions. Three dialectical models were identified through interviews with community coalition members: social ties, infrastructure, and worldviews, examining underlying assumptions and counter assumptions. By revealing the dialectic assumptions and counter assumptions within project implementation, practitioners can engage in constructive dialogue with communities to determine more effective and culturally responsive pathways for project development.
Changes in the spatial variability of extreme precipitation characteristics across Peninsular India
Authors: Dash Subhasmita , Sreya T. U. , Maity Rajib 
Published: June 2024

AbstractThrough a comprehensive analysis, this study portrays the changing spatial variability of extreme precipitation characteristics as a consequence of a gradually warming climate in peninsular India. In particular, it emphasizes the coastal areas that are under increased exposure to frequent extreme events in the recent past. Different extreme precipitation characteristics are considered, and the change points are identified based on their trend, mean and standard deviation. Changes in the spatiotemporal variability of extreme precipitation characteristics are identified through empirical orthogonal functions (EOFs). Our findings illustrate the occurrence of discernible changes almost all over the region with varying time points (1970 to 2011), and the extremes with higher thresholds exhibit more prominent changes. More importantly, a notable disparity in extreme indices expressing intensity is observed between the eastern and western coastal regions: change points for the eastern coastal areas (the Bay of Bengal side) predominantly emerged in the post-1980s, in contrast to the pre-1980s points across the western coastal (the Arabian Sea side) regions. Furthermore, after 2001, the spatial coverage of the western region notably expanded, as indicated by a significant increase in wet extremes, including those at the southernmost tip of India. Concurrently, extreme dry events significantly decreased across most of southern India during this period. On the other hand, the intensification of precipitation has become more prominent towards the Bay of Bengal side than towards the Arabian Sea side. This may be attributed to the increased cyclonic activity in the Bay of Bengal. Overall, the findings of this study will aid in understanding the evolving spatial pattern of extreme precipitation indices and will contribute to better management of extreme events and related hazards across peninsular India.
Buffering of Aerosol‐Cloud Adjustments by Coupling Between Radiative Susceptibility and Precipitation Efficiency
Authors: Song Ci , McCoy Daniel T. , Eidhammer Trude , Gettelman Andrew , McCoy Isabel L. , Watson‐Parris Duncan , Wall Casey J. , Elsaesser Gregory , Wood Robert 
Published: June 2024

AbstractAerosol‐cloud interactions (ACI) in warm clouds are the primary source of uncertainty in effective radiative forcing (ERF) during the historical period and, by extension, inferred climate sensitivity. The ERF due to ACI (ERFaci) is composed of the radiative forcing due to changes in cloud microphysics and cloud adjustments to microphysics. Here, we examine the processes that drive ERFaci using a perturbed parameter ensemble (PPE) hosted in CAM6. Observational constraints on the PPE result in substantial constraints in the response of cloud microphysics and macrophysics to anthropogenic aerosol, but only minimal constraint on ERFaci. Examination of cloud and radiation processes in the PPE reveal buffering of ERFaci by the interaction of precipitation efficiency and radiative susceptibility.
Donor human milk versus infant formula for low-risk infants: a systematic review
Authors: McClintock Thomas , Fiddes Catherine , Harris Shalee , Embleton Nicholas , Lin Luling , Bloomfield Frank H. , Muelbert Mariana 
Published: June 2024

Abstract

Background
There is an increasing acceptance and use of donor human milk (DHM) in healthy infants. This review investigates the benefits and risks of mothers’ own milk (MOM) supplementation with DHM compared to infant formula (IF) in moderate-late preterm (MLP) and early term (ET) infants.

Methods
MEDLINE, EMBASE, CINAHL, Scopus, Cochrane CENTRAL and clinical trial registries were searched for studies published up to September 2023. The primary outcome was rates of exclusive breastfeeding (EBF). Certainty of evidence was assessed using GRADE framework. RoB1 and EPHPP were used to assess risk of bias for controlled trials and observational studies, respectively.

Results
Eleven studies involving total of 10,147 infants and six ongoing trials were identified. Studies were of low quality, and the certainty of evidence was assessed as very low. Three studies suggested benefits of DHM compared to IF on EBF at discharge, while two suggested no difference. No clear effect was observed on EBF duration, any breastfeeding, hypoglycemia and morbidity. No health risks were reported.

Conclusion
The effect of supplementing MOM with DHM instead of IF on EBF and other health outcomes is unclear. High-quality studies are required to determine the potential benefits or risks of DHM supplementation in this population.

Impact

We identified 11 relevant studies reporting on supplementation of mothers’ own milk (MOM) with donor human milk (DHM) compared to infant formula (IF). Studies were of low quality, had heterogeneous outcome definitions and were geographically limited; all except two were observational studies.

Limited evidence showed no clear difference on rates of exclusive breastfeeding and other health outcomes. No potential risks were reported.

The increasing acceptance and use of DHM in healthy infants highlights the need for future high-quality studies.
Social interaction-induced fear memory reduction: exploring the influence of dopamine and oxytocin receptors on memory updating
Authors: Arellano Perez Angel David , Kautzmann Aline Sartori , de Oliveira Alvares Lucas 
Published: June 2024

AbstractIt has been well established that a consolidated memory can be updated during the plastic state induced by reactivation. This updating process opens the possibility to modify maladaptive memory. In the present study, we evaluated whether fear memory could be updated to less-aversive level by incorporating hedonic information during reactivation. Thus, male rats were fear conditioned and, during retrieval, a female was presented as a social rewarding stimulus. We found that memory reactivation with a female (but not a male) reduces fear expression within-session and in the test, without presenting reinstatement or spontaneous recovery. Interestingly, this intervention impaired extinction. Finally, we demonstrated that this emotional remodeling to eliminate fear expression requires the activation of dopamine and oxytocin receptors during retrieval. Hence, these results shed new lights on the memory updating process and suggests that the exposure to natural rewarding information such as a female during retrieval reduces a previously consolidated fear memory.
A machine learning contest enhances automated freezing of gait detection and reveals time-of-day effects
Authors: Salomon Amit , Gazit Eran , Ginis Pieter , Urazalinov Baurzhan , Takoi Hirokazu , Yamaguchi Taiki , Goda Shuhei , Lander David , Lacombe Julien , Sinha Aditya Kumar , Nieuwboer Alice , Kirsch Leslie C. , Holbrook Ryan , Manor Brad , Hausdorff Jeffrey M. 
Published: June 2024

AbstractFreezing of gait (FOG) is a debilitating problem that markedly impairs the mobility and independence of 38-65% of people with Parkinson’s disease. During a FOG episode, patients report that their feet are suddenly and inexplicably “glued” to the floor. The lack of a widely applicable, objective FOG detection method obstructs research and treatment. To address this problem, we organized a 3-month machine-learning contest, inviting experts from around the world to develop wearable sensor-based FOG detection algorithms. 1,379 teams from 83 countries submitted 24,862 solutions. The winning solutions demonstrated high accuracy, high specificity, and good precision in FOG detection, with strong correlations to gold-standard references. When applied to continuous 24/7 data, the solutions revealed previously unobserved patterns in daily living FOG occurrences. This successful endeavor underscores the potential of machine learning contests to rapidly engage AI experts in addressing critical medical challenges and provides a promising means for objective FOG quantification.
Discovery of atomic clock-like spin defects in simple oxides from first principles
Authors: Davidsson Joel , Onizhuk Mykyta , Vorwerk Christian , Galli Giulia 
Published: June 2024

AbstractVirtually noiseless due to the scarcity of spinful nuclei in the lattice, simple oxides hold promise as hosts of solid-state spin qubits. However, no suitable spin defect has yet been found in these systems. Using high-throughput first-principles calculations, we predict spin defects in calcium oxide with electronic properties remarkably similar to those of the NV center in diamond. These defects are charged complexes where a dopant atom — Sb, Bi, or I — occupies the volume vacated by adjacent cation and anion vacancies. The predicted zero phonon line shows that the Bi complex emits in the telecommunication range, and the computed many-body energy levels suggest a viable optical cycle required for qubit initialization. Notably, the high-spin nucleus of each dopant strongly couples to the electron spin, leading to many controllable quantum levels and the emergence of atomic clock-like transitions that are well protected from environmental noise. Specifically, the Hanh-echo coherence time increases beyond seconds at the clock-like transition in the defect with 209Bi. Our results pave the way to designing quantum states with long coherence times in simple oxides, making them attractive platforms for quantum technologies.
Nucleic acid mediated activation of a short prokaryotic Argonaute immune system
Authors: Kottur Jithesh , Malik Radhika , Aggarwal Aneel K. 
Published: June 2024

AbstractA short prokaryotic Argonaute (pAgo) TIR-APAZ (SPARTA) defense system, activated by invading DNA to unleash its TIR domain for NAD(P)+ hydrolysis, was recently identified in bacteria. We report the crystal structure of SPARTA heterodimer in the absence of guide-RNA/target-ssDNA (2.66 Å) and a cryo-EM structure of the SPARTA oligomer (tetramer of heterodimers) bound to guide-RNA/target-ssDNA at nominal 3.15–3.35 Å resolution. The crystal structure provides a high-resolution view of SPARTA, revealing the APAZ domain as equivalent to the N, L1, and L2 regions of long pAgos and the MID domain containing a unique insertion (insert57). Cryo-EM structure reveals regions of the PIWI (loop10-9) and APAZ (helix αN) domains that reconfigure for nucleic-acid binding and decrypts regions/residues that reorganize to expose a positively charged pocket for higher-order assembly. The TIR domains amass in a parallel-strands arrangement for catalysis. We visualize SPARTA before and after RNA/ssDNA binding and uncover the basis of its active assembly leading to abortive infection.
The role of CO2 in the genesis of Dabie-type porphyry molybdenum deposits
Authors: Jiang Zi-Qi , Shang Lin-Bo , Williams-Jones A. E. , Wang Xin-Song , Zhang Li , Ni Huai-Wei , Hu Rui-Zhong , Bi Xian-Wu 
Published: June 2024

AbstractPorphyry-type molybdenum deposits, many of which are in China, supply most of the World’s molybdenum. Of particular importance are the molybdenum deposits located in the Qinling-Dabie region that are responsible for more than half of China’s molybdenum production. A feature that distinguishes this suite of deposits from the better-known Climax and Endako sub-types of porphyry molybdenum deposits is their formation from CO2-rich magmatic-hydrothermal fluids. The role of CO2, if any, in the transport of molybdenum by these fluids, however, is poorly understood. We conducted experiments on the partitioning of molybdenum between H2O-CO2, H2O-NaCl, and H2O-NaCl-CO2 fluids and a felsic melt at 850 °C and 100 and 200 MPa. Here we show that the exsolution of separate (immiscible) brine and vapor leads to the very high brine DMo values needed for efficient extraction of Mo from the magmas forming Dabie-type porphyry molybdenum deposits.
Demonstration of charge-hold-vent (CHV) and no-vent-fill (NVF) in a simulated propellent storage tank during tank-to-tank cryogen transfer in microgravity
Authors: Chung J. N. , Dong Jun , Wang Hao , Han Huang Bo , Hartwig Jason 
Published: June 2024

AbstractThe space exploration from a low earth orbit to a high earth orbit, then to Moon, Mars, and possibly asteroids and moons of other planets is one of the biggest challenges for scientists and engineers for the new millennium. The enabling of in-space cryogenic rocket engines and the Lower-Earth-Orbit (LEO) cryogenic fuel depots for these future manned and robotic space exploration missions begins with the technology development of advanced cryogenic thermal-fluid management systems for the propellant transfer line and storage tank system. One of the key thermal-fluid management operations is the chilldown and filling of the propellant storage tank in space. As a result, highly energy efficient, breakthrough concepts for quenching heat transfer to conserve and minimize the cryogen consumption during chilldown have become the focus of engineering research and development, especially for the deep-space mission to Mars. In this paper, we introduce such thermal transport concepts and demonstrate their feasibilities in space for cryogenic propellant storage tank chilldown and filling in a simulated space microgravity condition on board an aircraft flying a parabolic trajectory. In order to maximize the storage tank chilldown thermal efficiency for the least amount of required cryogen consumption, the breakthrough quenching heat transfer concepts developed include the combination of charge-hold-vent (CHV) and no-vent-hold (NVF). The completed flight experiments successfully demonstrated the feasibility of the concepts and discovered that spray cooling combined with hold and vent is more efficient than the pure spray cooling for storage tank chilldown in microgravity. In microgravity, the data shows that the CHV thermal efficiency can reach 39.5%. The CHV efficiency in microgravity is 6.9% lower than that in terrestrial gravity. We also found that pulsing the spray can increase CHV efficiency by 6.1% in microgravity.
Quantum computing quantum Monte Carlo with hybrid tensor network for electronic structure calculations
Authors: Kanno Shu , Nakamura Hajime , Kobayashi Takao , Gocho Shigeki , Hatanaka Miho , Yamamoto Naoki , Gao Qi 
Published: June 2024

AbstractQuantum computers have a potential for solving quantum chemistry problems with higher accuracy than classical computers. Quantum computing quantum Monte Carlo (QC-QMC) is a QMC with a trial state prepared in quantum circuit, which is employed to obtain the ground state with higher accuracy than QMC alone. We propose an algorithm combining QC-QMC with a hybrid tensor network to extend the applicability of QC-QMC beyond a single quantum device size. In a two-layer quantum-quantum tree tensor, our algorithm for the larger trial wave function can be executed than preparable wave function in a device. Our algorithm is evaluated on the Heisenberg chain model, graphite-based Hubbard model, hydrogen plane model, and MonoArylBiImidazole using full configuration interaction QMC. Our algorithm can achieve energy accuracy (specifically, variance) several orders of magnitude higher than QMC, and the hybrid tensor version of QMC gives the same energy accuracy as QC-QMC when the system is appropriately decomposed. Moreover, we develop a pseudo-Hadamard test technique that enables efficient overlap calculations between a trial wave function and an orthonormal basis state. In a real device experiment by using the technique, we obtained almost the same accuracy as the statevector simulator, indicating the noise robustness of our algorithm. These results suggests that the present approach will pave the way to electronic structure calculation for large systems with high accuracy on current quantum devices.