bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hydride Formation Pressures and Kinetics in Individual Pd Nanoparticles with Systematically Varied Levels of Plastic Deformation
Authors: Langhammer Christoph , Andersson Carl , Zimmermann Jonathan , Fritzsche Joachim , Rabkin Eugen 
Published: December 2024

Abstract

Pd nanoparticles, together with bulk and thin film Pd, constitute the archetype model system for metal-hydrogen interactions. The density of defects in Pd nanoparticles, such as grain boundaries and dislocations, combined with their size, shape, composition and lattice strain, dictate their hydrogen sorption kinetics and thermodynamics. Despite decades of research and its relevance in applications, such as solid-state hydrogen storage, hydrogen sensors, hydrogen embrittlement, and hydrogen separation membranes, a coherent picture of the intricate interplay between defects, strain and Pd nanoparticle hydrogen sorption properties is missing. Here, we employ a combination of single particle nanocompression, single particle plasmonic nanoimaging and high-resolution cross-sectional single particle TEM imaging to investigate hydrogen absorption kinetics and hydride phase formation pressures in a nanofabricated array of Pd nanoparticles on sapphire substrate with systematically varied levels of plastic deformation – and thus defects and strain. We not only show a clear deformation-level dependent trend of both the kinetics and the hydride formation pressure, but also reveal their complex evolution upon hydrogen cycling. We discuss how these results provide a quantitative view of the impact of plastic deformation on nanoscale metal hydrides, and how they reveal the surface and bulk morphology of Pd nanoparticles upon repeated hydrogen cycling.
CIDEA promotes lipid deposition through focal adhesion pathway in goat intramuscular preadipocytes
Authors: Shao Peng , Li Qi , Liao Yu , Wang Yong , Lin Yaqiu , Xiang Hua , Du Zhanyu , Zhang Changhui , Zhu Jiangjiang , Huang Lian 
Published: December 2024

Abstract

Intramuscular fat (IMF) content determines the quality of goat meat, and is strongly associated with the number and volume of adipocytes, which is regulated by the comprehensive effect of proliferation and adipogenesis of intramuscular preadipocytes. Cell death-inducing DNA fragmentation factor alpha (DFFA)-like effector (CIDE) proteins has emerged as lipid droplets (LDs)-related proteins, implying the important roles in lipid homeostasis. However, the mechanism through which CIDEA, one member of CIDE family, regulates intramuscular fat deposition remains unclear. To address this, we dysregulated CIDEA in intramuscular preadipocytes and resolved the effect and mechanism of CIEDA in adipogenesis through RT-PCR, Western blot, triglyceride and LDs determinations, CCK-8 and RNA-seq. It was found that CIDEA increased LDs and triglyceride contents and inhibited cell proliferation. Lipid metabolism-related genes PPARγ, C/EBPα, SREBP1c, PLIN1, TIP47, ADFP, DGAT1, ACC, FASN, ACSL1, FABP3 were upregulated after CIDEA overexpression. Moreover, lipolysis and β oxidation genes HSL, ACOX1, CPT1B and proliferation marker genes CDK1 were upregulated. Differentially expressed genes in RNA-seq results were selected and enriched in the apelin and focal adhesion signaling pathways. Specifically, CIDEA regulated the activation of focal adhesion kinase and AKT signaling proteins, but not p38 signaling. To this end, we did the rescue assay and found that suppressing focal adhesion kinase signaling pathway with PF573228 reversed the lipid droplets and triglyceride contents increase induced by CIDEA overexpressing and further decreased their contents in CIDEA interfering group. In summary, this study reveals that CIDEA promotes lipid deposition in intramuscular preadipocytes through the focal adhesion pathway and inhibiting the cell proliferation. These works clarify the functional role and downstream signaling pathway of CIDEA in intramuscular fat deposition and provide theoretical support for improving meat quality through manipulating phenotype-related key genes.
EDM ECM composite processes of high-quality small hole with large aspect ratio using surface protection and low-voltage assistance
Authors: Chen Haisheng , Yang Xuguang , Yue Xiaoming 
Published: December 2024

Abstract

Traditional machining methods face many problems in machining small holes with large aspect ratio on the difficult-to-machine materials. At present, EDM ECM composite processes is still one of the most promising methods to achieve high-efficiency, high-quality and high-precision machining of deep and small holes on difficult-to-machine materials. In this study, small holes with large aspect ratio were machined using axial-radial composite electrolytic tube electrodes. However, due to the unstable state of the working fluid under high pressure in the EDM ECM composite processes, the inlet machining surface was severely corroded by stray corrosion. After the tube electrode penetrated the workpiece, the working fluid was missing, resulting in a recast layer remaining on the hole wall at the outlet of the hole. Furthermore, as the hole depth increased, the electrolysis time of the hole wall surface decreased accordingly, resulting in large diameter differences between the inlet and outlet of micro hole. In order to realize the high-quality and high-precision machining of small holes with large aspect ratio, this study proposed a EDM ECM composite processes of high-quality small hole with large aspect ratio using the surface protection and low-voltage assistance among the high-voltage pulses. Experimental results show that small holes with almost zero taper (less than 0.01°) can be successfully machined by using the surface protection and low-voltage assistance. The workpiece surface at the inlet of deep hole was smooth and no obvious traces of stray corrosion was found. In addition, there was no EDM residue on the hole wall surface at the outlet of deep hole, and the line roughness Ra of the hole wall surface was less than 0.2 µm. The method proposed in this study has a broad application prospect for machining high-quality and high-precision small holes with large aspect ratio on difficult-to-machine materials.
Assessing the Performance of Domain-Specific Models for Plant Leaf Disease Classification: A Comprehensive Benchmark of Transfer-Learning on Open Datasets
Authors: Richter David J. , Kim Kyungbaek 
Published: December 2024

Abstract

Agriculture and its yields are indispensable to human life all over the planet. It is an essential part of many countries’ economies and without it the world’s population can not be fed. As such, guaranteeing harvest with minimal loss is a primary objective. One factor that heavily contributes to loss in crop harvesting are plant diseases, which often affect crops and their leaves. A plant’s leaf often carries symptoms that indicate whether or not a plant is infected, but traditional manual approaches to identifying these symptoms are tedious and laborious. Additionally the process of manually spotting diseases can be rather slow in a field where urgency and fast identification are very important. The sooner a disease gets identified, the sooner countermeasures can be carried out. To improve both the accuracy with which diseases can be recognized, as well as increasing the speed at which this can be carried out, deep learning methods have proven useful. Recently the field of plant disease recognition has seen a big uptick in the application of various convolutional neural network (CNN) models for the automatic classification of diseases. There exist many different highly-capable models at this time. There also exists a range of plant leaf disease classification image datasets containing different plants and diseases. However, there seems to be no consensus on which model is best suited to handle this task and the same can be said for the datasets. To the best of our knowledge, prior work has used a wide range of different models with different datasets in the way of feasibility studies, but without comprehensively identifying which models are best used in this field. In this work we test a large number of state-of-the-art CNN models on a wide range of openly available datasets to asses their performance and to identify models that are best suited for this field, in order to be able to built better models, and even new foundation models, based on these findings. 23 models have been tested on 18 datasets, both using transfer-learning and transfer-learning with additional fine-tuning added, for 5 iterations each. Transfer-learning allows models to utilize knowledge obtained from other previous tasks to be used for new tasks, reducing training time and lowering the need for training data. The experiments result in a total of 4,140 having been trained for this work. All results will be compared and contextualized in order to find the best models architecture for plant leaf disease classification as well as assessing which datasets are well suited for this task.
TVET as a catalyst for productivity growth in the textile and garment sector: evidence from Ethiopian textile and garment sector, pre-war context
Authors: Wubet Gebretsadik Gebru 
Published: December 2024

Abstract

Background: Productivity is essential for economic growth and competitiveness. This study assesses the effect of strategic organizational changes and vocational skills development programs on productivity in the textile and garment industry in Ethiopia by using the Primary Transformation Model.
Objective: the objective of this study is to quantify the effects of strategic decisions and implementation practices on productivity, providing empirical evidence and practical insights for enhancing productivity in the sector.
Methods: A multiple linear regression analysis was conducted to assess the impacts of various factors on productivity. The PTM framework was employed to systematically analyze the relationships between competitive priorities, strategic decisions and implementation practices. Findings: the analysis revealed that strategic organizational changes significantly improve productivity: β = 1.546, p < 0.001. Further, investments in pre-employment VSD programs for middle-skilled employees (β = 2.110, p < 0.05) and higher-skilled employees (β = 1.497, p < 0.05), and in-employment VSD programs for higher-skilled employees with two programs (β = 1.305) and three programs (β = 1.231), p < 0.05, lead to significant gains in productivity.
Conclusions and Recommendations: These results bring out clearly the importance of strategic decisions and implementation practices for driving productivity and, hence, provide relevant insights for policymakers and industry stakeholders who seek to advance productivity and competitiveness in the sector.
Impact of aging endocrine milieu on prostate stromal-epithelial interactions
Authors: Nagesh A. Muni , Choudhury Ankit Roy , Devi Nandana , Gupta Surabhi , Chaturvedi PradeepKumar , Kumar Neeraj , Pandey Deepak 
Published: December 2024

Abstract

The interplay between stromal and epithelial interactions is pivotal in the development and maintenance of various organs, including the prostate, an essential accessory gland in the male reproductive system. The prostate gland's development and physiology are intricately tied to the localized concentrations of sex steroids, specifically androgens and estrogens. Perturbations in this hormonal balance, often associated with aging, have been implicated in prostatic diseases such as hyperplasia and cancer. In this study, we investigated the influence of estradiol (E2) and dihydrotestosterone (DHT) on prostate cells’ interactions and acinar morphogenesis. Increasing E2:DHT ratios were found to enhance stromal proliferation without a concurrent increase in epithelial cell population. Stromal conditioned medium (CM) promoted aberrant epithelial growth via elevated mitogenic factors, ERα/AR expression, and BAX downregulation. Notable expression of CK05 marker suggests basal cell involvement. Additionally, CM stimulated acinar branching and expansion in prostatospheres, mimicking early cancerous acinar changes. These findings illuminate the complex interplay between hormonal ratios and stromal-epithelial crosstalk, offering valuable insights into potential mechanisms underlying age-related prostate pathologies.
An Efficient Deepfake Detection System Using ConvoReinAutoNet and GeoFisherNet
Authors: ALkhorem Azan Hamad 
Published: December 2024

Abstract

This study suggests a hybrid optimization model and a new deep learning technique to create an effective deepfake detection system. During the preprocessing stage, deepfake database images are improved by employing Gaussian Filter and Histogram Equalization and are ready for analysis. The recently proposed Improved Local Ternary Patterns (I-LTP) approach collects textural and temporal information for feature extraction. The advanced GeoFisherNet, which effectively integrates spatial and temporal properties, is then utilized to fuse these data. The Marine Predator Customized White Shark Optimizer (MCWO), a hybrid approach that combines the White Shark Optimization Algorithm (WSO) and Marine Predator Algorithm (MPA), is used to find the most discriminative features during the feature selection phase. Lastly, ConvoReinAutoNet (CRAN), a revolutionary deep learning architecture that combines Convolutional Neural Networks (CNN), Deep Reinforcement Learning (DRL), and Autoencoders, is applied to the fused and optimized features in the classification phase to make precise detection decisions. The Python implementation of the suggested system shows better detection efficiency and accuracy of two data splits (70% and 80%) are 98.78% and 99.42% than the current methods.
Diagnosis-Treatment Analysis of Tongue Flap Necrosis and Shedding Caused by Vascular Crisis after Tongue Replantation in a Patient with Acute Transient Psychotic Disorder: A case report
Authors: Shi Yongle , Diao Yanjun , Liu Xian 
Published: December 2024

Abstract

Objectives：
Previous research on tongue amputations caused by acute transient psychotic disorder has mainly focused on emergency management after injury, such as achieving haemostasis and ensuring airway patency. However, the aspects of observation, care and functional training of the tongue flap after replantation are lacking.
Materials and Methods:
This study presents a case of flap necrosis following replantation of a self-inflicted tongue amputation in a patient with acute transient psychotic disorder.
Results:
After careful pre-operative assessment, the patient was found to be suitable for tongue reimplantation surgery. The surgery was successfully performed exactly 7 hours after the onset of the injury. However, a number of factors led to inactivation and spontaneous detachment of the reimplanted tongue flap 7 days postoperatively. These factors included the patient's compromised general condition, which was a direct consequence of the persistent primary disease, and the limitations of the multidisciplinary approach to wound management. Two weeks after surgery, treatment of the patient's acute transient psychotic disorder was remarkably effective, meeting the criteria for discharge from the psychiatric unit. Three weeks after the operation, the patient presented with restricted tongue movement and pronounced articulation difficulties. However, 3 months after surgery, the length of the fractured tongue had increased and there was a significant improvement in both tongue mobility and the degree of dysarthria, indicating a positive progression in the patient's recovery process.
Conclusions:
We believe that the crucial aspects of postoperative care after replantation include reducing the incidence of vascular crises, increasing the survival rate of the tongue, and improving the quality of life of the patient.
Clinical Relevance:
The key points in the management and care of a patient with acute transient psychotic disorder who has suffered non-suicidal self-injury resulting in a bitten tongue include perioperative assessment for tongue replantation, particularly assessment for vascular crisis, ongoing management and functional training after tongue replantation, and management of the primary illness.
Shear wave elastography imaging in the assessment of skin stiffness in Egyptian patients with systemic sclerosis/scleroderma
Authors: Habib Asmaa , Baz Ahmed , Abbas Nasra , Osama Dina 
Published: December 2024

Abstract

Background: The modified Rodnan skin score (mRSS) is a commonly used tool for the evaluation of skin involvement in scleroderma patients, however, it has many fallacies such as low objectivity and lack of inter-observer. In recent years, shear-wave elastography (SWE) proved to be an important assessment tool in the quantification of skin involvement in systemic sclerosis patients. In this study, we aimed to evaluate ultrasound and elastography findings in patients with systemic sclerosis and to clarify the effectiveness of elastosonography in the assessment of disease severity.
Methods: This prospective analytical study was conducted on 25 clinically diagnosed patients of scleroderma who subjected to shear wave elastography referred from Rheumatology and Rehabilitation Department, Faculty of Medicine, in our University to the Diagnostic Radiology department, they were compared with 25 age and sex matched healthy controls.
Results: High statistically significant difference (p-value < 0.001) was found in skin stiffness by elastography in cases group (median = 15 and inter-quartile range (IQR) = 11 – 21.5) when compared with control group (median = 10.5, IQR = 9.5 – 11.5), there was discrimination between cases group and control group was at a cut off level of > 13.6, with 58% sensitivity, 94% specificity.
Conclusions: The shear wave elastography helped in early skin stiffness detection and assessment in scleroderma/systemic sclerosis patients, with less influence of clinical features and greater sensitivity and specificity.
Prevalence of Depression in Childhood-Onset Systemic Lupus Erythematosus: A Systematic Review and Meta-Analysis
Authors: Xiao-Jing Xia , Min Pan 
Published: December 2024

Abstract

Objective: Childhood-onset systemic lupus erythematosus (cSLE) is frequently associated with psychological symptoms, particularly depression. However, there remains a lack of quantitative evidence regarding the prevalence and disease course of depression based on the currently available evidence. In this context, we conducted the first systematic review and meta-analysis addressing this important issue.
Methods:Three medical databases, including PubMed, Embase, Cochrane Library were utilized in this study. We included studies that reported on cSLE patients experiencing depression for a meta-analysis. STATA software were employed to synthesize the results as well as to assess heterogeneity and publication bias.
Results: Totally 12 eligible studies encompassing 652 cSLE patients were incorporated into this meta-analysis. Each of the publications included exhibited commendable methodological rigor, with Newcastle-Ottawa scores no less than 6. The pooled results with 12 articles indicated that the prevalence of depression among cSLE patients was 32.6% (95% CI: 0.25-0.40, Z=8.656, P<0.001). Subsequent subgroup analysis indicated that the prevalence of depression varied according to the different screening tools used: it was found to be 26% with CDI (95% CI: 0.18-0.34, P=0.023, I²=61.8%), 41% with PHQ-9 (95% CI: 0.20-0.63, P<0.001, I²=90.7%), and 37% with other tools such as BSI, BDI, and CES-D (95% CI: 0.21-0.53, P=0.031, I²=71.3%). Furthermore, the Egger’s test indicates that publication bias is insignificant among the studies included.
Conclusions: The prevalence of depression in patients with cSLE is slightly higher compared with adult SLE patients. It is noteworthy that screening rates for depression vary significantly among different assessment tools. There exists an urgent need to establish a consensus aimed at standardizing diagnostic criteria for depression through screening, thereby providing valuable guidance for clinical and nursing practice.
Optimizing mathematical models for the efficacy and precise regimens of meropenem in RICU patients: a real-world prospective study
Authors: Hou Jingjing , Zhao Yichang , Luo Hong , Li Jinhua , Xiao Yiwen , Gong Hui , Ma Rui , Cai Hualin , Zhang Bikui , Yan Miao 
Published: December 2024

Abstract

Background
It is inadequate to direct evaluation of meropenem pharmacokinetic targets and clinical efficacy. This study aimed to investigate the predictors of meropenem clinical effectiveness and to optimize dosing regimens precisely in the Department of Respiratory and Intensive Care Unit (RICU).
Methods
Patients with severe pneumonia using meropenem in RICU were included. Blood samples were assayed using two-dimensional high-performance liquid chromatography. Logistic regression analysis was conducted to identify predictors of efficacy. Population pharmacokinetics analysis was performed to optimize dosing regimens.
Results
396 meropenem concentrations from 111 patients were measured. The joint predictor of total protein, platelet, Cpeak, and APACHE Ⅱ score had a good predictive performance on the clinical efficacy (P < 0.001). Model-based simulation suggested to administer 2000 mg of meropenem every 8 hours at a 2-hour infusion for the patient with a minimum inhibitory concentration (MIC) of 8 mg/L and a creatinine clearance (CrCL) of 30 ml/min, or at 3-hour infusion for the patient with a MIC of 4 mg/L and a CrCL of 60 ml/min, respectively, which could achieve a probability of target attainment (PTA), with 100% of the time between doses at which the free fraction concentration remains above MIC (%fT > MIC) ≥ 80%. And only at specific MICs and pharmacodynamic targets, did PTAs of the prolonged infusion be significantly different (P < 0.05).
Conclusion
High Cpeak caused potential unfavorable outcomes. 2000 mg of meropenem every 8 hours with 2-hour or 3-hour infusion was recommended for patients with severe pneumonia in RICU. The benefits of prolonged infusion were limited.
Art impacts in museums compared to digital encounters
Authors: Darda Kohinoor M. , Gonzalez Vicente Estrada , Christensen Alexander P. , Bobrow Isabella , Krimm Amy , Nasim Zuha , Cardillo Eileen R. , Perthes William , Chatterjee Anjan 
Published: December 2024

Abstract

As cultural consumption increasingly moves to a digital space, it is crucial to understand the evolving landscape of art consumption both in and outside of a physical museum context. The current study delves into this contrast, seeking to understand how art is perceived and appreciated in museums and on a digital medium (like a computer screen). Across two experiments at the Barnes Foundation and Penn Museum in Philadelphia, Pennsylvania, we explored how the aesthetic engagement of paintings and artifacts is influenced by the physical context in which an artwork is encountered and by the characteristics of the viewer. Our findings suggest that the cognitive and emotional impacts of artworks on viewers, as well as the viewers’ overall aesthetic experiences are comparable across physical museum spaces and digital platforms. However, participants reported gaining more understanding from art viewed in museums, compared to participants who viewed art in the lab. Art experience and openness to experience influenced aesthetic impacts and ratings differently in the museum and in the lab. Overall, routes to broader valuations of liking were more similar than different between the museum and lab contexts, whereas patterns of impacts that might lead to new knowledge or understanding gained differed between museum and lab contexts. As digital technologies are increasingly integrated into diverse processes in museums such as collections management, curation, exhibitions, and education and learning, our research highlights how museums can leverage digital expansion to achieve their missions as centers of learning and education.