bluuebunny/crossref_metadata_2025_split huggingface dataset:
Microstructure Evolution and Precipitation Strengthening Behaviour of Additively Manufactured High-speed Steels
Authors: Zhang H , Venero D A , Park J , Petegem S V , Özsoy A , Soundarapandiyan G , Robertson S , Zhang X , Chen B 
Published: August 2024

Abstract
Additively manufactured (AM) high-speed steels were investigated, focusing specifically on the microstructure evolution during post-treatment in S390 steel and the rapid solidification process in M50 steel. An improved understanding of the processing-microstructure-property relationship for AM high-speed steel is achieved through a combination of post-mortem microstructure characterisation on precipitates and in-situ tracking of phase evolution. Quantitative characterisation of primary carbides and nanoprecipitates highlights the strengthening through nanoprecipitates that contribute to the exceedingly high hardness of 921 HV. Phase evolution during tempering was examined through in-situ synchrotron diffraction and ex-situ small-angle neutron scattering, revealing primary carbide growth by 60 nm within 2 minutes and nanoparticle precipitation with a size of 1.4 nm after 60-minute tempering. Additionally, the microstructure evolution of AM M50 steel was investigated by operando synchrotron diffraction, unveiling cooling rates in the order of 105 K/s during liquid-solid transformation. After printing, the carbon content of 0.47 wt.% in the matrix was derived from the martensite tetragonality. The insights gained serve as a valuable guide for designing future steel groups and developing heat treatment procedures tailored for the AM process.
Applying lab-based DCT to reveal and quantify the 3D grain structure of a miniature chess rook produced by binder jetting
Authors: Sun J , Bachmann F , Oddershede J , Lauridsen E 
Published: August 2024

Abstract
Imaging the 3D grain microstructure of additively manufactured (AM) metal samples non-destructively is key to a better understanding of the material performance. Recent advances of lab-based diffraction contrast tomography (DCT) enable non-destructively mapping the spatial distribution of crystallographic orientations in the bulk of certain types of metal AM parts. Combining these 3D texture measurements with traditional absorption contrast tomography (ACT) gives unprecedented insights into materials structure, such as the spatial distribution of porosities and the relationship between microstructural anisotropies and the build direction. Here, the combination of ACT and DCT is exemplified for a metal AM sample produced by binder jetting. This application highlights some of the recent technical progress enabling 3D mapping of metal AM structures and leads to a discussion of remaining challenges for lab-based DCT in the metal AM field.
Revisiting the Theory of Spinodal Strengthening: Implications for Inhomogeneous Additive and Irradiated Structural Alloys
Authors: Civiero Riccardo , El-Azab Anter 
Published: August 2024

Abstract
Composition fluctuations are commonly observed in additive manufactured alloys, high entropy alloys and irradiated alloys. These fluctuations, which arise due to thermodynamic and/or kinetic factors, influence the mechanical strength of alloys. The classical theory of spinodal strengthening in alloys with coherency stress arising due to the spinodal long-range composition fluctuations has been developed by Cahn, Kato and others. We present the motivations for revisiting Cahn’s theory to account for the concurrent solid solution strengthening in spinodally strengthened alloys by taking into consideration the effect of the solute friction along with the internal coherency stress. We briefly expose the model we developed to achieve the aforementioned aim and discuss some findings.
Effect of multi-pass shot peening on the microstructure of LPBF AlSi10Mg alloy
Authors: Snopiński P , Yu T , Zhang X , Juul Jensen D 
Published: August 2024

Abstract
In this study, we investigated the effect of multi-pass shot peening (SP) on the microstructural evolution of a Laser Powder Bed Fusion AlSi10Mg alloy. Characterization techniques included optical microscopy, scanning electron microscopy, and electron backscatter diffraction (EBSD). The results revealed that multi-pass SP induces a gradient microstructure with notable alterations in the grain structure extending to a depth of approximately 45 μm. EBSD analysis revealed that the SP treatment induced grain refinement and formation of subgrains (average distances between boundaries vary from 3.6 μm in the un-deformed area to 0.4 μm near the heavily deformed surface area). It is discussed how this refined microstructure following SP may lead to substantial improvements in mechanical properties and fatigue strength, and thus hold promises for increased performance of critical components across various industrial applications.
Plasmon–phonon gain in CdHgTe structures with near-surface HgTe quantum wells
Authors: Ya Aleshkin V , Rudakov A O , Dubinov A A , Morozov S V 
Published: August 2024

Abstract
The work is devoted to the study of plasmon–phonon gain in CdHgTe/HgTe structures with quantum wells (QWs) located near the boundary of the structure with vacuum/air (near-surface QWs). The issue of the influence of the distance between QWs on the plasmon–phonon gain has been studied. It has been shown that a decrease in the distance from the nearest QW to the structure boundary leads to an increase in the phase velocity of the generated plasmon–phonon and a decrease in the power absorbed by phonons in the barriers. This leads to a decrease in the threshold concentration of nonequilibrium carriers required to begin of plasmon–phonon gain under conditions of optical excitation.
Synthesis, characterization, and gas-sensing application of Cd0.5Zn0.5NdxFe2–xO4 nanoparticles
Authors: Korek Hani , Habanjar Khulud , Elsharkawy Sherif G , Awad R 
Published: August 2024

Abstract
Fabrication of Cd0.5Zn0.5NdxFe2–xO4 nanoparticles, with x = 0.00, 0.01, 0.02, 0.04, 0.06, and 0.08, has been carried out using a wet chemical co-precipitation method. The effect of the rare earth Nd3+ doping on the prepared ferrites was structurally investigated using x-ray diffraction (XRD) along with Rietveld refinement. The results indicate great crystallinity in the FCC Fd3m spinel structure of Cd0.5Zn0.5NdxFe2–xO4 nanoparticles. The lattice parameter increases with the increase of doping concentration from 8.5378 until 8.5432 Å and the crystallite size obtained using Debye-Sherrer, Williamson–Hall, Size-strain plot (SSP), and Halder-Wagner (H-W) methods, decreases until the solubility limit of the materials is at x = 0.04. By using transmission electron microscopy (TEM), the morphological analysis reveals the spherical shape of the samples with minor agglomeration with the aid of using a Polyvinylpyrrolidone (PVP) capping agent. The grain size ranges from 14.37 to 15.24 nm. Raman spectroscopy verifies the incorporation of Nd3+ in the octahedral sites and the decrease in particle size. The elemental composition was verified using x-ray photoelectron spectroscopy (XPS). The magnetic properties were studied using a vibrating sample magnetometer (VSM) and it shows superparamagnetic behavior with a decrease in the saturation magnetization from 2.207 to 1.918 emu g−1 and an increase in coercivity from 7.194 to 14.397 G. The prepared materials were tested as liquefied petroleum gas (LPG) sensors by studying their sensitivity, selectivity, optimum working temperature, response, and recovery times. Nd3+ doping shows a great increase in LPG sensing sensitivity 4 to 20 times than the pure samples. The doping concentration also decreases the response and recovery times.
RobMedNAS: searching robust neural network architectures for medical image synthesis
Authors: Zhang Jinnian , Chen Weijie , Joshi Tanmayee , Uyanik Meltem , Zhang Xiaomin , Loh Po-Ling , Jog Varun , Bruce Richard , Garrett John , McMillan Alan 
Published: August 2024

Abstract
Investigating U-Net model robustness in medical image synthesis against adversarial perturbations, this study introduces RobMedNAS, a neural architecture search strategy for identifying resilient U-Net configurations. Through retrospective analysis of synthesized CT from MRI data, employing Dice coefficient and mean absolute error metrics across critical anatomical areas, the study evaluates traditional U-Net models and RobMedNAS-optimized models under adversarial attacks. Findings demonstrate RobMedNAS’s efficacy in enhancing U-Net resilience without compromising on accuracy, proposing a novel pathway for robust medical image processing.
Enhancing quantum annealing accuracy through replication-based error mitigation*
Authors: Djidjev Hristo N 
Published: August 2024

Abstract
Quantum annealers like those manufactured by D-Wave Systems are designed to find high quality solutions to optimization problems that are typically hard for classical computers. They utilize quantum effects like tunneling to evolve toward low-energy states representing solutions to optimization problems. However, their analog nature and limited control functionalities present challenges to correcting or mitigating hardware errors. As quantum computing advances towards applications, effective error suppression is an important research goal. We propose a new approach called replication based mitigation (RBM) based on parallel quantum annealing (QA). In RBM, physical qubits representing the same logical qubit are dispersed across different copies of the problem embedded in the hardware. This mitigates hardware biases, is compatible with limited qubit connectivity in current annealers, and is well-suited for currently available noisy intermediate-scale quantum annealers. Our experimental analysis shows that RBM provides solution quality on par with previous methods while being more flexible and compatible with a wider range of hardware connectivity patterns. In comparisons against standard QA without error mitigation on larger problem instances that could not be handled by previous methods, RBM consistently gets better energies and ground state probabilities across parameterized problem sets.
The effect of uncertainty in humidity and model parameters on the prediction of contrail energy forcing
Authors: Platt John C , Shapiro Marc L , Engberg Zebediah , McCloskey Kevin , Geraedts Scott , Sankar Tharun , Stettler Marc E J , Teoh Roger , Schumann Ulrich , Rohs Susanne , Brand Erica , Van Arsdale Christopher 
Published: August 2024

Abstract
Previous work has shown that while the net effect of aircraft condensation trails (contrails) on the climate is warming, the exact magnitude of the energy forcing per meter of contrail remains uncertain. In this paper, we explore the skill of a Lagrangian contrail model (CoCiP) in identifying flight segments with high contrail energy forcing. We find that skill is greater than climatological predictions alone, even accounting for uncertainty in weather fields and model parameters. We estimate the uncertainty due to humidity by using the ensemble ERA5 weather reanalysis from the European Centre for Medium-Range Weather Forecasts (ECMWF) as Monte Carlo inputs to CoCiP. We unbias and correct under-dispersion on the ERA5 humidity data by forcing a match to the distribution of in situ humidity measurements taken at cruising altitude. We take CoCiP energy forcing estimates calculated using one of the ensemble members as a proxy for ground truth, and report the skill of CoCiP in identifying segments with large positive proxy energy forcing. We further estimate the uncertainty due to model parameters in CoCiP by performing Monte Carlo simulations with CoCiP model parameters drawn from uncertainty distributions consistent with the literature. When CoCiP outputs are averaged over seasons to form climatological predictions, the skill in predicting the proxy is 44%, while the skill of per-flight CoCiP outputs is 84%. If these results carry over to the true (unknown) contrail EF, they indicate that per-flight energy forcing predictions can reduce the number of potential contrail avoidance route adjustments by 2x, hence reducing both the cost and fuel impact of contrail avoidance.
Effect of pile driving induced ground vibrations and stress distribution to close settlements: a case study
Authors: Ongen Tugce , Yetkin Mustafa Emre , Kilinc Mehmet Emre 
Published: August 2024

Abstract
The pile method, applied in the foundational operations of construction to enhance soil-bearing capacity, is utilized in locations with insufficient soil support. Its purpose is to reinforce the foundation and improve soil stability before constructing a structure. In this study, vibrations occurring during the application of Vibrex-type piles for foundation reinforcement in a construction project located in the Konak district of Izmir Province were measured at various distances from the measurement points. The study further explored the influence of pile application on soil stability, considering the geomechanical properties of the site’s soil structure. The analysis of the study’s graph indicates that stress and vibration velocity remains at optimal levels, suggesting favorable working conditions.
JefiAtten: an attention-based neural network model for solving Maxwell’s equations with charge and current sources
Authors: Sun Ming-Yan , Xu Peng , Zhang Jun-Jie , Du Tai-Jiao , Wang Jian-Guo 
Published: August 2024

Abstract
We present JefiAtten, a novel neural network model employing the attention mechanism to solve Maxwell’s equations efficiently. JefiAtten uses self-attention and cross-attention modules to understand the interplay between charge density, current density, and electromagnetic fields. Our results indicate that JefiAtten can generalize well to a range of scenarios, maintaining accuracy across various spatial distribution and handling amplitude variations. The model showcases an improvement in computation speed after training, compared to traditional integral methods. The adaptability of the model suggests potential for broader applications in computational physics, with further refinements to enhance its predictive capabilities and computational efficiency. Our work is a testament to the efficacy of integrating attention mechanisms with numerical simulations, marking a step forward in the quest for data-driven solutions to physical phenomena.
Evaluation of glucose-lowering medications in older people: a comprehensive systematic review and network meta-analysis of randomized controlled trials
Authors: Pan Ssu-Yu , Su En-Lin , Huang Chi-Jung , Chuang Shao-Yuan , Chiang Chern-En , Chen Chen-Huan , Cheng Hao-Min 
Published: August 2024

Abstract

Background
Type 2 diabetes mellitus (T2DM) is increasingly being diagnosed in older adults. Our objective is to assess the advantages and potential drawbacks of different glucose-lowering medications in this specific population.

Methods
A network meta-analysis was conducted to identify randomized controlled trials that examined patient-centered outcomes in adults aged ≥65 years with T2DM. We searched PubMed, Cochrane CENTRAL, and Embase up to September 23, 2023. Quality of eligible studies were assessed using the Cochrane RoB 2.0 tool.

Results
A total of 22 trials that involved 41 654 participants were included, incorporating sodium-glucose cotransporter-2 (SGLT2) inhibitors, glucagon-like peptide-1 receptor agonists (GLP-1RAs), dipeptidyl peptidase-4 (DPP-4) inhibitors, metformin, sulfonylureas (SU) and acarbose. Our findings reveal that GLP-1RAs reduce the risk of major adverse cardiovascular events (risk ratio [RR], 0.83; 95% confidence interval [CI], 0.71 to 0.97) and body weight (mean difference [MD], −3.87 kg; 95% CI, −5.54 to −2.21). SGLT2 inhibitors prevent hospitalization for heart failure (RR, 0.66; 95% CI, 0.57 to 0.77), renal composite outcome (RR, 0.69; 95% CI, 0.53 to 0.89), and reduce body weights (MD, −1.85 kg; 95% CI, −2.42 to −1.27). SU treatment increases the risk of any hypoglycaemia (RR, 4.19; 95% CI, 3.52 to 4.99) and severe hypoglycaemia (RR, 7.06; 95% CI, 3.03 to 16.43). GLP-1RAs, SGLT2 inhibitors, metformin, SU and DPP-4 inhibitors are effective in reducing glycaemic parameters. Notably, the number of treatments needed decreases in most cases as age increases.

Conclusions
Novel glucose-lowering medications with benefits that outweigh risks should be prioritized for older patients with diabetes.
Potential roles for artificial intelligence in clinical microbiology from improved diagnostic accuracy to solving the staffing crisis
Authors: Graf Erin , Soliman Amr , Marouf Mohamed , Parwani Anil V , Pancholi Preeti 
Published: August 2024

Abstract

Objectives
This review summarizes the current and potential uses of artificial intelligence (AI) in the current state of clinical microbiology with a focus on replacement of labor-intensive tasks.

Methods
A search was conducted on PubMed using the key terms clinical microbiology and artificial intelligence. Studies were reviewed for relevance to clinical microbiology, current diagnostic techniques, and potential advantages of AI in routine microbiology workflows.

Results
Numerous studies highlight potential labor, as well as diagnostic accuracy, benefits to the implementation of AI for slide-based and macroscopic digital image analyses. These range from Gram stain interpretation to categorization and quantitation of culture growth.

Conclusions
Artificial intelligence applications in clinical microbiology significantly enhance diagnostic accuracy and efficiency, offering promising solutions to labor-intensive tasks and staffing shortages. More research efforts and US Food and Drug Administration clearance are still required to fully incorporate these AI applications into routine clinical laboratory practices.
What’s Past is Prologue: Democracy in the Age of Originalism
Authors: Kirsch Geoffrey R 
Published: August 2024

Abstract
This essay reviews three recent books grappling with the history and meaning of US constitutional democracy, written in a time when an originalist, conservative Supreme Court serves as the Constitution’s final arbiter. Democracies in America: Keywords for the Nineteenth Century and Today, edited by D. Berton Emerson and Gregory Laski, and The Nation That Never Was: Reconstructing America’s Story, by Kermit Roosevelt III, strive to appropriate originalist methods toward progressive ends. By contrast, Cass R. Sunstein’s How to Interpret the Constitution evinces a pragmatic skepticism of any such historically bound modes of interpretation. The tension between these approaches, I suggest, has shaped US constitutional discourse since the nineteenth century.
Management of Serious Adverse Events Following Deoxycholic Acid Injection for Submental and Jowl Fat Reduction: A Systematic Review and Management Recommendations
Authors: Shridharani Sachin M , Kennedy MacKenzie L 
Published: August 2024

Abstract

Pivotal Phase 3 randomized control trials have demonstrated a favorable safety profile for ATX-101 in submental fat (SMF) reduction; however, in real-world settings, several serious adverse events (SAEs) have been reported, most of which are procedure related and avoidable. Current understanding of the management of uncommon AEs and SAEs is based on the aesthetic surgeon's discretion, and overzealous protocols for sclerosis agents are being applied for ATX-101-induced arterial injury. This review focuses on showcasing the management of SAEs reported previously and updating it with personal clinical experiences with ATX-101 for SMF and jowl fat reduction. Along with adherence to the standard procedures for ATX-101 administration, the authors recommend investigating other potential causes of SMF accumulation and jowling mechanism, appropriate demarcation of the surface area to determine the number of vials, and assessment of the fat pad thickness to determine the number of required treatment cycles for optimal therapeutic outcomes. Surgery is preferable for jowling caused by compartment displacement (ptosis), whereas fat-reducing treatments such as ATX-101 are contraindicated for jowling caused by subcutaneous tissue atrophy. Some proactive measures that can be employed to prevent AEs include avoiding intradermal injections to prevent skin ulceration/necrosis, injecting lidocaine to check for smile asymmetry as an indication of marginal mandibular nerve proximity, administering 1 to 2 mm deeper injections in males to prevent alopecia, employing good aseptic techniques to prevent abscess formation, injecting 1 product at a time using correctly labeled syringes, and confirming the diagnosis of pyoderma gangrenosum before treating it as an infection.

Level of Evidence: 3
Exploration correlates with dietary choosiness and avoidance learning style in a generalist predator
Authors: Kuo Chi-Yun , Chen Yu-Hsi , Meng Ai-Ching , Wu Yu-Zhe , Yang Shan-Yu , Yeh Ching-Ning 
Published: August 2024

Abstract
The hypothesis of slow–fast syndromes predicts a correlation between personality type and learning style; fast explorers would have a more proactive (fast but inflexible) learning style whereas slow explorers would be more reactive (slow but flexible) learners. Empirical evidence for this personality-cognition coupling remains inconclusive and heavily biased toward birds. Moreover, most studies did not examine the personality-cognition correlation when the cognitive task is discerning food quality, a scenario directly related to energy acquisition that underpins the evolution of slow–fast syndromes. In this study, we examined the exploration–cognition correlation in the context of avoidance learning in an opportunistic predator—the common sun skink Eutropis multifasciata. We quantified exploration tendencies of individuals in an unfamiliar environment and compared foraging behaviors when lizards associated prey color and taste during the initial learning trials and subsequent reverse learning trials, where the color–taste associations were switched. We found that fast explorers were less choosy and modified their foraging behaviors less with experience, conforming to a more proactive cognitive style. In contrast, slow explorers were reactive learners and were able to change foraging behaviors in both learning and reverse learning phases, even though the ability to do so depended on the color–taste treatment. Contrary to conventional predictions, the proactive–reactive learning styles in our focal species were not differentiated by a learning speed-flexibility trade-off. Our findings offer nuanced support to the slow–fast syndromes and suggest that the two types of exploration–cognition correlations could be different responses to fast-changing environmental predictability.
Publication-ready single nucleotide polymorphism visualization with snipit
Authors: O’Toole Áine , Aziz Ammar , Maloney Daniel 
Published: August 2024

Abstract

Summary
Snipit is an analysis and visualization tool designed for summarizing single nucleotide polymorphisms in sequences in comparison to a reference sequence. This tool efficiently catalogues nucleotide and amino acid differences, enabling clear comparisons through customizable, publication-ready figures. With features such as configurable colour palettes, customizable record sorting, and the ability to output figures in multiple formats, snipit offers a user-friendly interface for researchers across diverse disciplines. In addition, snipit includes a specialized recombi-mode for illustrating recombination patterns, which can highlight otherwise often difficult-to-detect relationships between sequences.

Availability and implementation
Snipit is an open-source python-based tool that is hosted on GitHub under a GNU-GPL 3.0 licence (https://github.com/aineniamh/snipit). It can be installed from PyPi using pip. Source code and additional documentation can be found on the GitHub repository.