bluuebunny/crossref_metadata_2025_split huggingface dataset:
Accounting for carbon capture solvent cost and energy demand in the energy system
Authors: Chanal Vincent , Humpage Samuel , Millinger Markus 
Published: February 2025

Abstract
Technical carbon dioxide removal through bioenergy with carbon capture or direct air capture plays a role in virtually all climate mitigation scenarios. Both of these technologies rely on the use of chemical solvents or sorbents in order to capture CO$_2$. Lately, concerns have surfaced about the cost and energy implications of producing solvents and sorbents at scale. Here, we show that the production of chemical sorbents could have significant implications on system cost, energy use and material use depending on how much they are consumed. Among the three chemical sorbents investigated, namely monoethanolamine (MEA) for post-combustion carbon capture, potassium hydroxide for liquid direct air capture and polyethylenimine-silica (PEI) for solid sorbent direct air capture, we found that the production of the compound for solid sorbent direct air capture represent the highest uncertainties for the system. At the high range of solid sorbent consumption, total energy system cost increased by up to 6.5\%, while effects for other options were small to negligible. Scale-up of material production capacities was also substantial for MEA and PEI. Implications of sorbent consumption for carbon capture technologies should be considered more thoroughly in scenarios relying on direct air capture using a solid sorbent.
Research on current assisted flexible mold micro-forming process based on single channel
Authors: Zhao Qingjuan , Wang Gui , Sun Jinchao , Zhang Ruoyu , Zhou Lejia , Qu Yunfei 
Published: February 2025

Abstract
Aiming at the problems such as poor forming accuracy and serious thickness thinning in sheet metal bulging, a method of current-assisted flexible mold forming was proposed. The single channel flexible mold forming experiment was carried out with 304 stainless steel sheet as the experimental material. Firstly, the microstructure change of the sheet under the action of current was analyzed. Then, the flexible mold bulging law of stainless steel sheet was explored from two aspects of current intensity and pressure holding time. Finally, the difference between the traditional rigid mold and the flexible mold is compared. The experimental results show that with the increase of the pretreatment current, the fibrous distribution in the thickness direction of the sheet is alleviated, the work hardening is weakened, the bulging depth of the flexible mold is gradually increased, and the wall thickness distribution is more uniform. When the current is 25A, the bulging depth of the rolled sheet increases from 841um to 903um, an increase of about 7.4%. The thinning rate of rounded corners was reduced from the initial 30.05% to 12.74%. When the pressure holding time is increased from 1.5s to 3.5s, the wall thickness thinning in each area is improved, and the thinning at the rounded corner is reduced to about 10.66%. Under the same experimental parameters, the bulging of flexible mold is better than that of rigid mold, the single channel profile is clearer, the surface roughness is lower, and the forming performance is better.
Mechanical field assisted additive manufacturing of ultrahigh strength aluminum alloy
Authors: Liu Wenjie , Shen Shengnan , Meng Jinlong , Xiao Jiafeng , Li Hui , Du Hejun , Yin Qianxing , Tan Chaolin 
Published: February 2025

Abstract
Additive manufacturing of aluminum (Al) alloys has attracted significant attention in the aerospace industry. However, achieving ultrahigh strength (> 500 MPa) Al alloys remains challenging due to their intrinsic poor printability. Here, we report a novel hybrid additive manufacturing (HAM) approach to process ultrahigh strength AlMgSc alloy, which combines laser powder bed fusion (LPBF) with interlayer ultrasonic shot peening (USP). The results show that the interlayer ultrasonic shot peening depth reached ~700 µm, leading to almost full density and residual stress convection from tension to compression. The HAM method promotes equiaxed grain formation and refines grain due to grain recrystallizations. Interestingly, the HAM followed by aging treatment tailors the hierarchically multi-gradient structures, inhibits Mg element intragranular segregation and promotes the multi-nanoprecipitates (e.g., Al3(Sc, Zr) and Al6Mn) precipitation. Remarkably, the HAM followed by aging treatment achieves yield strength of 609 MPa and break elongation of 7.5 %, demonstrating ultrahigh strength and good ductility compared with other Al alloys manufactured by LPBF and forging as reported in the literature. The multi-strengthening mechanisms in this AlMgSc alloy are also investigated. The high-density Al3(Sc, Zr) precipitates are the main strengthening contributor, and unique hetero-deformation induced (HDI) strengthening (originates from the heterogeneous microstructures) further enhances the strength of the material. This work highlights a new way to process complex-structured ultrahigh strength Al alloy components by hybrid additive manufacturing.
Machine Learning Enhanced Metal 3D Printing: High Throughput Optimization and Material Transfer Extensibility
Authors: Zhang Yuanjie , Lin Cheng , Tian Yuan , Gao Jianbao , Song Bo , Zhang Hao , Wang Min , Song Kechen , Deng Binghui , Xue Dezhen , Yao Yonggang , Shi Yusheng , Fu Kun Kelvin 
Published: February 2025

Abstract
Metal 3D printing holds great promise for future digitalized manufacturing. However, the intricate interplay between laser and metal powders poses a significant challenge for conventional trial-and-error optimization. Meanwhile, the ‘optimized’ yet fixed parameters largely limit possible extensions to new designs and materials. Herein, we report a high throughput design coupled with machine learning (ML) guidance to eliminate the notorious cracks and porosities in metal 3D printing for improved corrosion resistance and overall performance. The high throughput methodologies are mostly on obtaining the printed samples and their structural and physical properties, while ML is used for data analysis by model building for prediction (optimization), and understanding. For 316L stainless steel, we concurrently printed 54 samples with different parameters and subjected them to parallel tests to generate an extensive dataset for ML analysis. An ensemble learning model outperformed the other five single learners while Bayesian active learning recommended optimal parameters that could reduce porosity from 0.57% to below 0.1%. Accordingly, the ML-recommended samples showed higher tensile strength (609.28 MPa) and elongation (50.67%), superior anti-corrosion (Icorr = 4.17×10−8A/cm2), and stable alkaline oxygen evolution for >100 hours (at 500 mA/cm2). Remarkably, through the correlation analysis of printing parameters and targeted properties, we find that the influence of hardness on corrosion resistance is second only to porosity. We then expedited optimization in AlSi7Mg using the learned knowledge and feed hardness and relative density, thus demonstrating the method’s general extensibility and efficiency. Our strategy can significantly accelerate the optimization of metal 3D printing and facilitate adaptable design to accommodate diverse materials and requirements.
Spectral sparse random feature decomposition and its application in rotating machinery composite fault diagnosis
Authors: Liu Zhijun , Zhou Jun , Wu Xing , tao liu 
Published: February 2025

Abstract
Sparse random mode decomposition (SRMD) is a new signal decomposition method that integrates sparse random feature models with clustering methods. The method firstly represents the input signal as a series of sparse random feature points in time-frequency space, then employs clustering algorithms to cluster these sparse feature points into different modes, and finally decomposes the signal into a series of modes. Due to its excellent signal decomposition capability, SRMD has been applied in various fields, including mechanical fault diagnosis, biological signal processing, and image processing. However, the performance of SRMD is constrained by its own hyperparameters, and the results are strongly influenced by the clustering method. To overcome these shortcomings, the spectral sparse random feature decomposition (SSRFD) is proposed. In the process of representing signal as sparse random features, we design the fault characteristic frequency amplitude energy ratio (FCFAER) index and employ zebra optimization algorithm (ZOA) to select two key parameters: window length and relative error coefficient. Thus, an optimal sparse spectrum representation of the signal is obtained to alleviate the effects of SRMD hyperparameters; in the process of mode separation, the sparse random feature correlation spectrum (SRFCS) is proposed, which indicates the frequency ranges of the sparse random feature points corresponding to different modes within the sparse spectrum of the signal. Lastly, the automatic division of SRFCS is realized through parameterless scale space division, so that the sparse random features can be reasonably classified and clustered into modes respectively, and the separation of different modes in the signal can be realized without using the clustering method. Finally, the viability and usefulness of the proposed method are proved through composite fault data from the rolling bearings and the RV reducer gears in rotating machinery. The results show that the method has good composite fault characteristics separation and extraction capability.
YOLOv8-ADDA: An Enhanced Algorithm for Real-Time Traffic Sign Detection
Authors: Zheng Xiaolong , Guan Zhiwei , Chen Qiang , Lu Xiaofeng , Xia Longqing 
Published: February 2025

Abstract
Existing deep learning-based traffic sign recognition methods often face challenges such as low accuracy, slow detection response, and limited applicability in real-world scenarios. This paper proposes an improved model based on YOLOv8, aiming to enhance detection accuracy and reduce model complexity. To achieve this, the Adaptive Downsampling (ADown) method is integrated into the Backbone Conv module, effectively reducing input feature dimensions and minimizing redundant parameters. Additionally, the Deformable Attention Transformer (DAT) mechanism is incorporated into the C2f module, dynamically adjusting the attention range to capture more relevant visual features. Furthermore, Wise and Efficient IoU (Wise-EIoU) is employed as the loss function to improve classification performance in object detection tasks.&#xD;The proposed algorithm is evaluated on the Roadsign and CCTSDB2021 datasets, achieving significant performance improvements. On the Roadsign dataset, the model achieves a precision of 94.9%, with mAP50 and mAP50:95 reaching 97.1% and 85.9%, respectively, surpassing the YOLOv8n benchmark by 2.7% and 4.2% on the same metrics. The number of model parameters is reduced to 2.79M, reflecting a 7.5% decrease compared to YOLOv8n. To verify its practical applicability, experiments are conducted on the PIX miniature intelligent vehicle platform. The proposed model achieves an inference speed of 59 FPS, representing a&#xD;15.6% improvement over the baseline, demonstrating its suitability for real-time traffic sign detection tasks. These results validate the effectiveness of the YOLOv8-ADDA model in improving detection accuracy and reducing computational complexity.&#xD;
Hospitalized Pediatric Patients: Risk Factors Related to the Development of Immobility-Related and Medical Device-Related Pressure Injuries
Authors: Nie Ann Marie , Delmore Barbara 
Published: February 2025

GENERAL PURPOSE
To review risk factors for the development of medical device-related and immobility-related pressure injuries in hospitalized pediatric patients.

TARGET AUDIENCE
This continuing education activity is intended for physicians, physician assistants, nurse practitioners, and registered nurses with an interest in skin and wound care.

LEARNING OBJECTIVES/OUTCOMES
After participating in this educational activity, the participant will be better able to:
1. Describe trends in pressure injuries (PIs) for hospitalized pediatric patients as summarized in current literature.
2. Identify risk factors predictive of medical device-related and immobility-related PIs in hospitalized pediatric patients.
3. Summarize the methodology used to understand risk factors for developing PIs in the hospitalized pediatric patient population.

ABSTRACT

OBJECTIVE
To determine the pressure injury (PI) risk factors associated with medical devices and immobility in varied ages of the pediatric population and determine if there is an association between medical devices, immobility, and PI development.

METHODS
A retrospective study was performed on an established PI database with medical records reviewed for accuracy. The sample consisted of 799 children who developed a PI at a pediatric hospital in the upper Midwestern US. Multivariate logistic analyses were conducted to determine PI risk factors associated with medical devices and immobility in the pediatric population by age.

RESULTS
Five risk factors were predicative of a medical device-related PI for the entire sample; additional risk factors were specific to individual ages. Conversely, only one risk factor was statistically significant for predicting immobility-related PI in the total sample: decreased sensory perception (P = .035). Immobility was not associated with the development of medical device-related PIs.

CONCLUSIONS
Medical devices and immobility remain a major concern in relation to their propensity to cause PIs in hospitalized pediatric patients. Although this vulnerable population is beginning to garner more attention in the literature, the standard is to use adult PI risk factors for the pediatric population. Adult risk factors do not always equally translate to the hospitalized pediatric patient; however, clinicians use this “measuring stick” because research extricating the differences between these populations is limited. Understanding the unique PI risk factors in the pediatric population is key to preventing PIs among these patients.
Operation and Practice of the Scott-Munro Model: Risk Assessment of Intraoperatively Acquired Pressure Injuries
Authors: Wu Yanjun , Chen Yuting , Kong Weina , He Caiqin , Li Dongxue 
Published: February 2025

ABSTRACT

OBJECTIVE
To evaluate the feasibility and effectiveness of the Scott-Munro (S-M) model in the dynamic assessment of intraoperatively acquired pressure injuries (IAPIs) in adults.

METHODS
This study included 8,254 patients who underwent surgery between October 2022 and September 2023. The S-M model was applied for the dynamic risk assessment of IAPIs. The first cycle was set as the baseline from October 1, 2022, to December 31, 2022, and cycles were set every 3 months thereafter. Each cycle was compared with the first cycle and the previous cycle, in terms of IAPI incidence, actual assessment rate of IAPIs in high-risk patients, and accuracy of IAPI assessment in high-risk patients.

RESULTS
The incidences of IAPIs in the four cycles were 0.52%, 0.27%, 0.09%, and 0.13%, respectively. The third and fourth cycles both differed significantly from the first cycle (P < .05). The actual assessment rates of IAPIs in high-risk patients in the four cycles were 13.01%, 47.20%, 90.96%, and 95.67%, respectively (P < .05). Similarly, the accuracy of the assessment of IAPIs in high-risk patients was 38.04%, 67.37%, 89.93%, and 86.58%, respectively, in the four cycles (P < .05).

CONCLUSIONS
The S-M model can reduce the incidence of IAPIs, dynamically and effectively evaluate IAPIs, and provide a basis for the management and prevention of IAPIs.
Systemic Lymphoma Masquerading as Birdshot Chorioretinopathy
Authors: Wei Elizabeth Y. , Popovic Marko M. , Christakis Panos G. 
Published: February 2025

Purpose:
To report a rare case of systemic lymphoma causing a birdshot-like chorioretinopathy (BSCR) in a histocompatibility leukocyte antigen (HLA)-A29 negative patient.

Methods:
A 58-year-old man presented with a one year history of blurry vision and intermittent floaters. He had evidence of bilateral choroidal birdshot-like lesions which appeared atrophic without any vitritis. He had a history of low-grade B-cell lymphoma and chronic myeloid leukemia, both of which were diagnosed >10 years prior to presentation and treated with chemotherapy.

Results:
The differential diagnosis of these birdshot-like lesions included autoimmune, neoplastic, and infectious etiologies. Work-up revealed a negative HLA-A29, and negative results for syphilis and tuberculosis. Magnetic resonance imaging (MRI) revealed enhancement of the trigeminal and oculomotor nerve cisternal segments but no overt evidence of malignancy. Full field electroretinogram (ffERG) and multifocal electroretinogram (mfERG) tests were within normal limits. Serial follow-up clinical examinations, retinal imaging, ffERG and mfERG demonstrated no disease progression. Two years after his initial consultation, he developed a paraspinal mass which was biopsied and found to be diffuse large B-cell lymphoma (DLBCL) and was treated with chemotherapy.

Conclusion:
Clinicians should consider BSCR masquerade syndromes in patients that present with birdshot-like choroidal lesions with negative HLA-A29, history of lymphoma, or atypical characteristics. In this case, we suspect the patient’s past low-grade B-cell lymphoma and chemotherapy resulted in the chronic choroidal findings. It is unclear whether choroidal involvement predisposes a patient to high-grade transformation to DLBCL. His ocular findings remained inactive throughout the treatment of his DLBCL.
Where is the pain? Spatial patterns of pain co-occurrence in a population-based study of 4833 pain drawings incorporating network analysis
Authors: Evans David William , Liew Bernard Xian Wei , Andersen Johan Hviid , Mose Søren 
Published: February 2025

Abstract
Spatial pain patterns are widely used as diagnostic tools, yet population-level estimates, such as the prevalence of pain in specific body regions and likelihood of their co-occurrence, are lacking. Despite this, bilateral limb pain is considered relatively uncommon. Baseline data from a population-based Danish cohort were analysed. Twenty-one pain drawing regions, coded as binary “pain”/“no-pain” variables, were entered into an Ising model. Conditional dependencies between pairs of painful regions were quantified, while accounting for the pain state of other regions. Four-week prevalence of pain was also calculated for body regions. Of 4833 analysed pain drawings, 34.7% (1676) reported bilateral (upper or lower) limb pain and 32.3% (1561) reported symmetrical (mirrored) bilateral limb pain. Strongest positive edge weights of the Ising model were between mirrored contralateral regions; the strongest being between left and right hips (mean: 3.86, 95% confidence interval: 3.84-3.87). Next strongest edge weights were between spatially adjacent ipsilateral regions; the strongest being between the right hip and right buttock (mean: 2.72, 95% confidence interval: 2.71-2.74). Negative edge weights, indicating inhibitory relationships, were consistently seen between nonmirrored contralateral regions, the strongest being between regions adjacent to their mirrored contralateral counterparts. In conclusion, bilateral limb pain, particularly in mirrored regions, is more prevalent than previously thought. Pain co-occurrence is facilitated between mirrored contralateral regions and, to a lesser degree, between adjacent ipsilateral regions. An inhibitory effect occurs between nonmirrored contralateral regions, diminishing with increasing distance from the mirrored region. Potential inhibition between mirrored contralateral regions is likely overshadowed by the more dominant facilitation.
Development and Psychometric Testing of a Tool to Measure Nursing Care Intensity for Stroke Patients
Authors: Ferrara Amalia , Iovino Paolo , Magni Valentina , Dibuono Maria Rosa , Brunelli Tiziana , Mastrorocco Rosaria , Favilla Cinzia , Giacomelli Silvia , Cerchia Pio , Rasero Laura 
Published: February 2025

ABSTRACT

BACKGROUND: Nurses play a crucial role in the care of stroke patients improving health outcomes. However, stroke nursing care is complex, and an instrument available to monitor the patient dependence over time and an efficient management of care would be beneficial for the stroke care units. The purpose of this study is to develop and psychometrically test an instrument to measure nursing care intensity for patients admitted to stroke units. METHODS: A 3-step process was implemented. First, item generation was performed based on an established theory. Second, content validity was assessed on the generated pool of items, and finally, the instrument was tested on a sample of 1200 stroke patients at admission and discharge time points, to test its psychometric properties. RESULTS: Item generation was driven by the theory of Roper-Logan-Tierney, and a total of 13 items were derived. Content validity led to the elimination of 5 items. The final instrument, the Chart of Nursing Assessment in Stroke (STROKE-CNA), was made of 8 items. Confirmatory factor analysis had a supportive fit (root mean square error of approximation = 0.077, comparative fit index = 0.99), indicating structural validity. Scores of the instrument at admission were significantly lower than at discharge (P < .001, Cohen d = 1.42), indicating longitudinal validity. The changes in STROKE-CNA scores between admission and discharge were positively correlated with the corresponding changes in scores on the Scandinavia Stroke Scale (r = 0.57, P < .001), confirming adequate responsiveness. The STROKE-CNA scores were negatively correlated with age (admission: r = −0.22, P < .001; discharge: r = −0.28, P < .001), indicating convergent validity. Internal consistency was adequate at 0.93, and interrater reliability was optimal, with Cohen kappa ranging between 0.61 and 0.99. CONCLUSIONS: The STROKE-CNA has promising validity and reliability when used for assessing nursing care complexity of patients admitted to stroke units.
Global systematic mapping of Vibrio species pathogenicity: A PRISMA-guided cluster-based analysis
Authors: Onohuean Hope , Nwodo Uchechukwu U. 
Published: February 2025

Background:
A systematic global map on toxigenesis and genomic virulence of Vibrio spp. was analyzed for research progress to identify the emerging research patterns for establishing a database for designing future interventions.

Method:
The databases (Web of Science and Scopus) were analyzed with Voxviewer software to map the global scale of Vibrio spp. or virulence toxin/genes publications and standardized using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) strategies.

Results:
The results identified 1162 (Web of Science n = 620, Scopus n = 542), while 314 studies qualified for inclusion and were significantly analyzed on virulence toxin/genes. By co-citation analysis, 4-thematic clusters were developed from 6420 citations and a total reference of 9062. Cluster #1 (pathogenesis & virulence factors) and cluster #4 (host response factors) generated the utmost publications and citations (n = 40, 643) and the least (n = 7, 85) interest by the researcher. Whereas 8-thematic clusters were developed by bibliographic coupling technique analysis, cluster#1 and cluster#8 generated the utmost (n = 78, 1684) and least (n = 7, 81) publications and citations interest by the researcher.

Conclusions:
Our findings suggest that Vibrio toxigenesis and virulence factors are a complex field requiring an interdisciplinary approach consisting of interconnected perspectives that have important consequences for academics and policymakers.