bluuebunny/crossref_metadata_2025_split huggingface dataset:
How megacities can achieve carbon peak through structural adjustments: an input–output perspective
Authors: Yang Yang , Wang Yiqi , Ji Junping , Wang Dong , Huang Qisheng , He Daojing 
Published: September 2024

Abstract
There is still a huge gap between the emissions pathways of megacities and the pathways to meeting the targets set by the Paris agreement. Compared with technological emission reductions, structural emission reduction can provide cities with more stable and sustainable carbon-peaking solutions. This study constructs a scenario-based input–output optimization model, adopting a novel carbon emission accounting method for purchased electricity that considers shared responsibility, and systematically evaluates the decarbonization paths of megacities and their impacts on economic growth, energy consumption, and carbon emissions. The results show that (a) through industry substitution and manufacturing restructuring, Shenzhen is projected to peak at 57.68 MtCO2 emissions in 2026, with a 10.57% energy and a 19.55% carbon reduction by 2030. (b) Shenzhen can achieve its carbon emission peak target through the energy transition while accepting a loss of 0.97%–3.23% of GDP, requiring the maximum economic concession of 16.45% from the transportation sector (S10) in the early stage of transformation, while 12.24% from the extractive industry (S2) in the later stage. (c) The comprehensive structure adjustment proved to be more effective than other mitigation approaches, capable of achieving high-quality economic growth of 6.4% during the study period while reaching a peak target of 53.55 million tons of CO2 by 2026. (d) The emission reduction effect of the power sector was the most significant among all the scenarios, with emission reduction rates between 6.26% and 35.63%, and the cumulative emission reduction potential reached 38.1–110.6 MtCO2. The priority for emission reduction in the power sector is the coal phase-out plan, which is essential for achieving these significant reductions. This study provides an important reference for megacities facing similar challenges, especially those in developing countries, to achieve a stable and sustainable carbon peak pathway through structural adjustment.
Hardening mechanism and thermal-solid coupling model of laminar plasma surface hardening of 65 Mn steel
Authors: CAO 曹 Xiuquan 修全 , WANG 王 Lin 林 , XU 徐 Haoming 浩铭 , HU 胡 Guangzhong 光忠 , LI 李 Chao 超 
Published: September 2024

Abstract
In the present work, the laminar plasma surface hardening method is employed to enhance the service life of metal components fabricated from 65 Mn steel. The mechanical and wear behaviors of the laminar plasma surface hardened 65 Mn steel were analyzed. The martensite transition transformation of the temperature of the laminar plasma-hardened 65 ferrite Mn steel was determined by a thermal-solid coupling model. Based on the orthogonal experimental results, the optimal hardening parameters were confirmed. The scanning velocity, quenching distance and arc current are 130 mm/min, 50 mm and 120 A, respectively. The pearlites and ferrites are transformed into martensites in the hardened zone, while the ratio of martensite in the heat-affected zone decreases with the increase in the hardening depth. Compared to the untreated 65 Mn steel, the average hardness increases from 220 HV0.2 to 920 HV0.2 in the hardened zone and the corresponding absorbed power increases from 118.7 J to 175.5 J. At the same time, the average coefficient of friction (COF) decreases from 0.763 to 0.546, and the wear rate decreases from 5.39×10−6 mm3/(N·m) to 2.95×10−6 mm3/(N·m), indicating that the wear resistance of 65 Mn steel could be significantly improved by using laminar surface hardening. With the same hardening parameters, the depth and width of the hardened zone predicted by the thermal-solid coupling model are 1.85 mm and 11.20 mm, respectively, which are in accordance with the experimental results; depth is 1.83 mm and width is 11.15 mm. In addition, the predicted hardness distributions of the simulation model are in accordance with the experimental results. These results indicate that the simulation model could effectively predict the microstructure characteristics of 65 Mn steel.
Insulating behaviour in room temperature rhombohedral LiNiO2 cathodes is driven by dynamic correlation
Authors: Banerjee H , Aichhorn M , Grey C P , Morris A J 
Published: September 2024

Abstract
Inspired by the experimental finding of a paramagnetic insulating state in rhombohedral LiNiO2, a lithium-ion battery cathode of great interest, we calculate the electronic, magnetic, and optical properties of LiNiO2 employing a range of single-particle and many-body methods. Within density-functional theory (DFT) using the generalized-gradient approximation (GGA), meta-GGA, and hybrid functionals, we obtain a ferromagnetic half-metallic ground state for rhombohedral LiNiO2, as has been seen previously. Self-consistent GW calculations including self-interaction corrections beyond DFT for various flavours show an electronic band gap albeit with a small quasiparticle peak at the Fermi energy. Moving beyond this, room temperature state-of-the-art dynamical mean-field theory (DMFT) calculations on rhombohedral LiNiO2 show for the first time a gap of combined Mott and charge-transfer character. The paramagnetic insulating state has a band gap of ~0.6 eV, in excellent agreement with experiments and is in sharp contrast to DFT calculations that require the presence of an extra structural symmetry breaking in the form of Jahn–Teller distortions to open a gap. We observe Ni to be in a +2 state in a d
8L configuration, with a charge-transfer ligand hole in O p, and identify the ligand hole state from the DMFT DOS. We further show that whereas DFT shows the presence of an unphysical metallic Drude peak in the optical absorption spectra, DMFT calculations capture the correct form of the optical absorption spectra, and have an excellent match with the calculated band gap as well. Our results clarify that at room temperature, it is the charge transfer gap with a Mott character that causes rhombohedral LiNiO2’s insulating nature; a structural distortion is not required.
Experimental investigation into friction stir welding of AA6061-T6 and magnesium AZ31B alloy using copper backing plate
Authors: Maniyar D G , Gadakh V S , Badheka V J , Jagtap K B , Mane S S , Dethe S M 
Published: September 2024

Abstract
Aluminium-magnesium alloys are lightweight and possess superior properties, making them ideal for applications in aerospace, railway, automotive, and marine structures. However, these alloys are challenging to fabricate using traditional fusion welding due to various metallurgical issues. This study investigates the feasibility of joining 3 mm thick dissimilar alloys of aluminium AA6061-T6 and magnesium AZ31B using the friction stir welding (FSW) process with copper as a backing plate. The effects of FSW process parameters, including tool rotational speed (380, 545, 765 rpm), weld speed (20, 31.5, 50 mm min−1), and tilt angle (1°, 2°, 3°), on tensile properties were examined using Taguchi-based grey relational analysis. Temperatures were recorded during the FSW process under different conditions on both sides of the joint. The highest tensile strength of 130.72 MPa, with a joint efficiency of 67.85%, was achieved at a tool rotational speed of 765 rpm, a welding speed of 50 mm min−1, and a tilt angle of 2°. Analysis of variance (ANOVA) for the grey relational grade indicated that the tilt angle had the highest percentage contribution of 43.60%. This study demonstrates the significant influence of FSW parameters on the mechanical properties of aluminium-magnesium joints and highlights the optimal conditions for achieving high joint strength and efficiency.
Equivariant tensor network potentials
Authors: Hodapp M , Shapeev A 
Published: September 2024

Abstract
Machine-learning interatomic potentials (MLIPs) have made a significant contribution to the recent progress in the fields of computational materials and chemistry due to the MLIPs’ ability of accurately approximating energy landscapes of quantum-mechanical models while being orders of magnitude more computationally efficient. However, the computational cost and number of parameters of many state-of-the-art MLIPs increases exponentially with the number of atomic features. Tensor (non-neural) networks, based on low-rank representations of high-dimensional tensors, have been a way to reduce the number of parameters in approximating multidimensional functions, however, it is often not easy to encode the model symmetries into them. In this work we develop a formalism for rank-efficient equivariant tensor networks (ETNs), i.e. tensor networks that remain invariant under actions of SO(3) upon contraction. All the key algorithms of tensor networks like orthogonalization of cores and DMRG-based algorithms carry over to our equivariant case. Moreover, we show that many elements of modern neural network architectures like message passing, pulling, or attention mechanisms, can in some form be implemented into the ETNs. Based on ETNs, we develop a new class of polynomial-based MLIPs that demonstrate superior performance over existing MLIPs for multicomponent systems.
Uncovering obscured phonon dynamics from powder inelastic neutron scattering using machine learning
Authors: Su Yaokun , Li Chen 
Published: September 2024

Abstract
The study of phonon dynamics is pivotal for understanding material properties, yet it faces challenges due to the irreversible information loss inherent in powder inelastic neutron scattering spectra and the limitations of traditional analysis methods. In this study, we present a machine learning framework designed to reveal obscured phonon dynamics from powder spectra. Using a variational autoencoder, we obtain a disentangled latent representation of spectra and successfully extract force constants for reconstructing phonon dispersions. Notably, our model demonstrates effective applicability to experimental data even when trained exclusively on physics-based simulations. The fine-tuning with experimental spectra further mitigates issues arising from domain shift. Analysis of latent space underscores the model’s versatility and generalizability, affirming its suitability for complex system applications. Furthermore, our framework’s two-stage design is promising for developing a universal pre-trained feature extractor. This approach has the potential to revolutionize neutron measurements of phonon dynamics, offering researchers a potent tool to decipher intricate spectra and gain valuable insights into the intrinsic physics of materials.
Qualitative analysis of hydroponic container farm adoption, use, and benefits in the U.S.
Authors: Kaminski Alexa G , Babbitt Callie W 
Published: September 2024

Abstract
The impacts of climate change, population growth, and resource constraints on conventional agriculture have sparked interest in controlled environment agriculture (CEA) technology. The hydroponic container farm (HCF) is a type of small-scale CEA infrastructure increasingly being adopted by cities, businesses, and nonprofits. Yet there is still significant uncertainty about HCF use, potential value to the food system, and broader sustainability benefits and tradeoffs. This research uses semi-structured interviews with farmers operating HCFs across the U.S. and grounded theory analysis to characterize HCF use, outcomes, benefits, and challenges. Results show that HCFs contribute direct benefits as food system infrastructure through food production, particularly in urban regions where conventional agriculture is infeasible, but also provide indirect benefits through education, workforce development, and broader social impact. Despite wide differences in the ways organizations use HCFs, we identified universal factors that moderate successful outcomes, including municipal zoning and permitting regulations, relationships between the HCF farmer and partners, the business model under which the HCF operates, and the design and cost of hydroponic technology. This study begins to characterize the social and economic tradeoffs that HCFs generate and provides use case data for future quantifications of environmental impact.
Coupling human dynamics with the physics of climate: a path towards Human Earth Systems Models
Authors: Tapiador Francisco J , Navarro Andrés 
Published: September 2024

Abstract
Climate models are fundamental tools for the study of global change. They are used not only to test scientific hypotheses about the physical processes operating in planetary atmospheres, but also to advise society about expected changes in the climate of our planet. Current Earth System Models have begun to incorporate biological, chemical and geological processes (biogeochemical cycles, water chemistry) as feedback between the surface and the atmosphere. However, due to the many challenges involved, the integration of ‘human dynamics’ remains to be fully addressed. This perspective outlines a path towards two-way feedback Human Earth Systems Models. Major challenges in the plan include how to deal with the uncertainty inherent in human behavior and our interaction with the environment, the limits of predictability, and the scale of computational resources required to model human behavior with sufficient accuracy (i.e. close to observed measurements) and precision (i.e. with low dispersion). This paper provides a roadmap towards a tool that could revolutionize Earth system modeling by fully integrating the physical and human systems.
Health impacts of excessive heat in Multnomah County, OR, 2021
Authors: Haggerty Brendon , DiLeo Kimberly , Nonnamaker Max , Thompson Jason , Walters Jaime 
Published: September 2024

Abstract
Human-induced climate change is leading to increased extreme weather events, such as the heat dome that occurred in Multnomah County, OR, in June 2021. Certain groups are at increased risk from excessive heat events, such as the very young and very old, persons without stable housing, and persons with certain health comorbidities. Our review of three data sources (deaths, hospitalizations, and emergency department visits) showed large increases in all three measures in the summer of 2021. Further, two-thirds of identified heat deaths occurred in or near neighborhoods that ranked among the most vulnerable to extreme heat. Despite thoughtful planning, a recently updated heat response plan, and an unprecedented mobilization of resources, we documented severe health impacts due to this heat event. We recommend that local health jurisdictions and emergency responders increase readiness for such events by interrogating existing plans and tailoring them not to events of expected severity, but to a worst case scenario that exceeds historic experiences.
The Fragile Ground of New England, 1638–1755
Authors: Brickhouse Anna 
Published: September 2024

Abstract
Puritan elites interpreted the seismic events of their moment by writing global earthquake histories that could accommodate an emerging culture of mastery and slavery sanctified by the idea of just war. Early New England earthquakes also reminded Puritans that those who had already inhabited the land long before their arrival understood earthquake in the New World in ways that they could not. Earthquake struck at the tenuously settled ground of colonial occupation and land enclosure; it emblematized the continual problem of settler security and the specific threat of Native agency. The Black and Indigenous specters who appeared during the Salem witch trials always had earthquake at their fingertips; earthquake thus required interpretive vigilance on the part of those with most power, lest other meanings take hold. This earthquake vigilance introduced a settler colonial Enlightenment: a culture of frantic knowledge production that had no confidence in the stability of the earth or in the security of settler polities and psyches.
The Undeceiving Earth
Authors: Brickhouse Anna 
Published: September 2024

Abstract
This chapter explores the writings of Herman Melville, whose entire oeuvre grapples with the southernizing geographies of Western theology and philosophy. Mardi is read as an allegory of global-colonial modernity that continually re-enacts the foundational Columbian narrative of La Navidad. The chapter then examines “The Town-Ho’s Story” in Moby-Dick for its self-consciously located diegesis set in Peru, the staging ground for an earthquake-whale’s assault on the colonial foundations of modern Western philosophy. Melville returned to this violent foundation in The Piazza Tales. The conclusion takes up Melville’s later writings, from The Confidence-Man to Timoleon, to show how the rending of the earth continues after the Civil War to foreground the predatory basis of optimism and the racial and geographic underpinnings of theodicy in a global-colonial world. Melville takes earthquake to be a quintessential figure for undeception, antithetical to the nineteenth-century invention of US-America as a denial of ongoing forms of conquest and coloniality in the here and now.
The significance of CD49f expression in pediatric B-cell acute lymphoblastic leukemia
Authors: Hunyadi Anna , Kriston Csilla , Szalóki Gábor , Péterffy Borbála , Egyed Bálint , Szepesi Ágota , Timár Botond , Erdélyi Dániel J , Csanádi Krisztina , Kutszegi Nóra , Márk Ágnes , Barna Gábor 
Published: September 2024

Abstract

Objectives
CD49f is an adhesion molecule present on malignant lymphoblasts in B-cell acute lymphoblastic leukemia; it is associated with a poor prognosis. CD49f expression has been proposed as a marker for measurable residual disease (MRD) marker, but this marker has yet to be implemented in clinical practice.

Methods
In this study, we used flow cytometry to detect CD49f expression by leukemic blasts in paired bone marrow and cerebrospinal fluid samples at diagnosis and bone marrow at day 15 of treatment.

Results
At diagnosis, 93% of bone marrow and 100% of cerebrospinal fluid lymphoblasts expressed CD49f. The intensity of CD49f expression statistically significantly increased during treatment (P &lt; .001). In MRD-negative end-of-treatment samples, only a small population of hematogones expressed CD49f. Interestingly, the intensity of CD49f expression varied among the different groups of recurrent genetic abnormalities. The ETV6::RUNX1 fusion and ETV6::RUNX1 combined with the high hyperdiploid group were associated with increased expression, whereas the Philadelphia-like group showed low CD49f expression. The lower CD49f expression at diagnosis predicted a lower MRD rate at day 15 of treatment.

Conclusions
We concluded that CD49f can be used as an MRD marker and possible prognostic factor in B-cell acute lymphoblastic leukemia.
Examining Food-Specific and General Inhibitory Control and Working Memory as Moderators of Relations Between Emotion Regulation Difficulties and Eating Pathology in Adults With Overweight/Obesity: A Preregistered, Cross-Sectional Study
Authors: Barnhart Wesley R , Braden Abby L , Buelow Melissa T 
Published: September 2024

Abstract

Objective
Empirical research and theory support the interaction of executive functions (e.g., inhibitory control, working memory) and emotion regulation in guiding goal-oriented behavior; however, applications to eating pathology (e.g., binge eating) are limited. Such research is scant with adults with overweight/obesity (AwO/O), a population reporting high levels of binge eating, emotion regulation difficulties, and deficits in inhibitory control and working memory. We tested interactions between emotion regulation and executive functioning in relation to eating pathology in AwO/O while considering stimuli-specific deficits (e.g., food-specific deficits) in behavioral task performance.

Method
AwO/O (N = 204; MBMI = 32.11; Mage = 38.30 [SD = 12.16]) completed a preregistered, online study assessing demographics and emotion regulation difficulties (Difficulties in Emotional Regulation Scale), inhibitory control (go/no-go task, food and general stimuli), working memory (N-Back Task, food and general stimuli), binge eating (Binge Eating Scale), and disordered eating (Eating Disorder Examination-Questionnaire).

Results
There was limited evidence of moderation in models examining food-specific and general inhibitory control and working memory, emotion regulation difficulties, and binge eating. Preliminary support was found for emotion regulation difficulties to be more strongly associated with more disordered eating in AwO/O reporting more food-specific and general working memory deficits. Consistent, positive associations between emotion regulation difficulties and eating pathology were observed.

Conclusions
Among adults with AwO/O, emotion regulation difficulties are closely related to eating pathology, regardless of performance on working memory and inhibitory control tasks. Clinicians and researchers working with AwO/O may consider how emotion regulation difficulties and working memory deficits work together to influence disordered eating.
Variable calling of m6A and associated features in databases: a guide for end-users
Authors: Song Renhua , J Sutton Gavin , Li Fuyi , Liu Qian , Wong Justin J-L 
Published: September 2024

Abstract
N6-methyladenosine (m$^{6}$A) is a widely-studied methylation to messenger RNAs, which has been linked to diverse cellular processes and human diseases. Numerous databases that collate m$^{6}$A profiles of distinct cell types have been created to facilitate quick and easy mining of m$^{6}$A signatures associated with cell-specific phenotypes. However, these databases contain inherent complexities that have not been explicitly reported, which may lead to inaccurate identification and interpretation of m$^{6}$A-associated biology by end-users who are unaware of them. Here, we review various m$^{6}$A-related databases, and highlight several critical matters. In particular, differences in peak-calling pipelines across databases drive substantial variability in both peak number and coordinates with only moderate reproducibility, and the inclusion of peak calls from early m$^{6}$A sequencing protocols may lead to the reporting of false positives or negatives. The awareness of these matters will help end-users avoid the inclusion of potentially unreliable data in their studies and better utilize m$^{6}$A databases to derive biologically meaningful results.
Enhancing clinical genomic accuracy with panelGC: a novel metric and tool for quantifying and monitoring GC biases in hybridization capture panel sequencing
Authors: Cheng Xuanjin , Goktas Murathan T , Williamson Laura M , Krzywinski Martin , Mulder David T , Swanson Lucas , Slind Jill , Sihvonen Jelena , Chow Cynthia R , Carr Amy , Bosdet Ian , Tucker Tracy , Young Sean , Moore Richard , Mungall Karen L , Yip Stephen , Jones Steven J M 
Published: September 2024

Abstract
Accurate assessment of fragment abundance within a genome is crucial in clinical genomics applications such as the analysis of copy number variation (CNV). However, this task is often hindered by biased coverage in regions with varying guanine–cytosine (GC) content. These biases are particularly exacerbated in hybridization capture sequencing due to GC effects on probe hybridization and polymerase chain reaction (PCR) amplification efficiency. Such GC content–associated variations can exert a negative impact on the fidelity of CNV calling within hybridization capture panels. In this report, we present panelGC, a novel metric, to quantify and monitor GC biases in hybridization capture sequencing data. We establish the efficacy of panelGC, demonstrating its proficiency in identifying and flagging potential procedural anomalies, even in situations where instrument and experimental monitoring data may not be readily accessible. Validation using real-world datasets demonstrates that panelGC enhances the quality control and reliability of hybridization capture panel sequencing.