bluuebunny/crossref_metadata_2025 huggingface dataset:
Rapid and Robust Identification of Sepsis Using SeptiCyte RAPID in a Heterogeneous Patient Population
Authors: Balk Robert , Esper Annette M. , Martin Greg S. , Miller Russell R. , Lopansri Bert K. , Burke John P. , Levy Mitchell , Rothman Richard E. , D’Alessio Franco R. , Sidhaye Venkataramana K. , Aggarwal Neil R. , Greenberg Jared A. , Yoder Mark , Patel Gourang , Gilbert Emily , Parada Jorge P. , Afshar Majid , Kempker Jordan A. , van der Poll Tom , Schultz Marcus J. , Scicluna Brendon P. , Klein Klouwenberg Peter M. C. , Liebler Janice , Blodget Emily , Kumar Santhi , Mei Xue W. , Navalkar Krupa , Yager Thomas D. , Sampson Dayle , Kirk James T. , Cermelli Silvia , Davis Roy F. , Brandon Richard B.
Published: October 2024

Background/Objective: SeptiCyte RAPID is a transcriptional host response assay that discriminates between sepsis and non-infectious systemic inflammation (SIRS) with a one-hour turnaround time. The overall performance of this test in a cohort of 419 patients has recently been described [Balk et al., J Clin Med 2024, 13, 1194]. In this study, we present the results from a detailed stratification analysis in which SeptiCyte RAPID performance was evaluated in the same cohort across patient groups and subgroups encompassing different demographics, comorbidities and disease, sources and types of pathogens, interventional treatments, and clinically defined phenotypes. The aims were to identify variables that might affect the ability of SeptiCyte RAPID to discriminate between sepsis and SIRS and to determine if any patient subgroups appeared to present a diagnostic challenge for the test. Methods: (1) Subgroup analysis, with subgroups defined by individual demographic or clinical variables, using conventional statistical comparison tests. (2) Principal component analysis and k-means clustering analysis to investigate phenotypic subgroups defined by unique combinations of demographic and clinical variables. Results: No significant differences in SeptiCyte RAPID performance were observed between most groups and subgroups. One notable exception involved an enhanced SeptiCyte RAPID performance for a phenotypic subgroup defined by a combination of clinical variables suggesting a septic shock response. Conclusions: We conclude that for this patient cohort, SeptiCyte RAPID performance was largely unaffected by key variables associated with heterogeneity in patients suspected of sepsis.
RETRACTED: Alrubaiq, A.; Alharbi, T. Developing a Cybersecurity Framework for e-Government Project in the Kingdom of Saudi Arabia. J. Cybersecur. Priv. 2021, 1, 302–318
Authors: Alrubaiq Abdullah , Alharbi Talal
Published: October 2024

The journal retracts the article titled “Developing a Cybersecurity Framework for e-Government Project in the Kingdom of Saudi Arabia” [...]
Helicopters Turboshaft Engines Neural Network Modeling under Sensor Failure
Authors: Vladov Serhii , Sachenko Anatoliy , Sokurenko Valerii , Muzychuk Oleksandr , Vysotska Victoria
Published: October 2024

This article discusses the development of an enhanced monitoring and control system for helicopter turboshaft engines during flight operations, leveraging advanced neural network techniques. The research involves a comprehensive mathematical model that effectively simulates various failure scenarios, including single and cascading failure, such as disconnections of gas-generator rotor sensors. The model employs differential equations to incorporate time-varying coefficients and account for external disturbances, ensuring accurate representation of engine behavior under different operational conditions. This study validates the NARX neural network architecture with a backpropagation training algorithm, achieving 99.3% accuracy in fault detection. A comparative analysis of the genetic algorithms indicates that the proposed algorithm outperforms others by 4.19% in accuracy and exhibits superior performance metrics, including a lower loss. Hardware-in-the-loop simulations in Matlab Simulink confirm the effectiveness of the model, showing average errors of 1.04% and 2.58% at 15 °C and 24 °C, respectively, with high precision (0.987), recall (1.0), F1-score (0.993), and an AUC of 0.874. However, the model’s accuracy is sensitive to environmental conditions, and further optimization is needed to improve computational efficiency and generalizability. Future research should focus on enhancing model adaptability and validating performance in real-world scenarios.
Advanced Supply Chain Management Using Adaptive Serial Cascaded Autoencoder with LSTM and Multi-Layered Perceptron Framework
Authors: Deka Aniruddha , Das Parag Jyoti , Saikia Manob Jyoti
Published: October 2024

Supply chain management is essential for businesses to handle uncertainties, maintain efficiency, and stay competitive. Financial risks can arise from various internal and external sources, impacting different supply chain stages. Companies that effectively manage these risks gain a deeper understanding of their procurement activities and implement strategies to mitigate financial threats. This paper explores financial risk assessment in supply chain management using advanced deep learning techniques on big data. The Adaptive Serial Cascaded Autoencoder (ASCA), combined with Long Short-Term Memory (LSTM) and Multi-Layered Perceptron (MLP), is used to evaluate financial risks. A data transformation process is used to clean and prepare financial data for analysis. Additionally, Sandpiper Galactic Swarm Optimization (SGSO) is employed to optimize the deep learning model’s performance. The SGSO-ASCALSMLP-based financial risk prediction model demonstrated superior accuracy compared to traditional methods. It outperformed GRU (gated recurrent unit)-ASCALSMLP by 3.03%, MLP-ASCALSMLP by 7.22%, AE-LSTM-ASCALSMLP by 10.7%, and AE-LSTM-MLP-ASCALSMLP by 10.9% based on F1-score performance. The SGSO-ASCALSMLP model is highly efficient in predicting financial risks, outperforming conventional prediction techniques and heuristic algorithms, making it a promising approach for enhancing financial risk management in supply chain networks.
A-C/Au Film with Low Humidity Sensitivity of Friction by Forming Au Transfer Film
Authors: Pei Lulu , Ji Li , Li Hongxuan , Cai Haichao , Xue Yujun
Published: October 2024

Amorphous carbon is recognized as an excellent lubricating material; however, its tribological properties are significantly influenced by humidity. To elucidate the mechanism underlying this humidity dependence and to propose a novel enhancement method, we investigated and compared the tribological properties of hydrogenated amorphous carbon (a-C:H) and amorphous carbon/gold (a-C/Au) composite films. First, the friction coefficient of these carbon films under different humidity conditions was tested using a rotational ball-on-disk tribometer. Subsequently, we analyzed the morphology and structure of the sliding interface employing optical microscopy (OM), Raman spectroscopy, transmission electron microscopy (TEM), and high-resolution transmission electron microscopy (HRTEM). Finally, first-principle calculations were carried out to calculate the adsorption energy of water molecules on different surfaces. The results indicate that the friction coefficient of a-C:H film and the area of transfer film increase with the increase of humidity. This phenomenon can be attributed to the fact that water molecules enhance the interaction between the a-C:H film and steel counterfaces. Notably, in contrast, the friction coefficient of a-C/Au film demonstrates low sensitivity to humidity due to the formation of an Au transfer film that exhibits weak interaction with water molecules. These findings provide a promising strategy for developing environment-adaptive amorphous carbon films and play an important role in promoting the development of intelligent lubricating film.
An Investigation of Oxides of Tantalum Produced by Pulsed Laser Ablation and Continuous Wave Laser Heating
Authors: Auner Alexander W. , Crowhurst Jonathan C. , Weisz David G. , Dai Zurong , Knight Kimberly B.
Published: October 2024

Recent progress has seen multiple Ta2O5 polymorphs generated by different synthesis techniques. However, discrepancies arise when these polymorphs are produced in widely varying thermodynamic conditions and characterized using different techniques. This work aimed to characterize and compare Ta2O5 particles formed at high and low temperatures using nanosecond pulsed laser ablation (PLA) and continuous wave (CW) laser heating of a local area of tantalum in either air or an 18O2 atmosphere. Scanning electron microscopy (SEM) and Raman spectroscopy of the micrometer-sized particles generated by PLA were consistent with either a localized amorphous Ta2O5 phase or a similar, but not identical, crystalline β-Ta2O5 phase. The Raman spectrum of the material formed at the point of CW laser impingement was in good agreement with the previously established ceramic “H-Ta2O5” phase. TEM and electron diffraction analysis of these particles indicated the phase structure matched an oxygen-vacated superstructure of monoclinic H-Ta2O5. Further from the point of laser impingement, CW heating produced particles with a Raman spectrum that matched β-Ta2O5. We confirmed that the high-temperature ceramic phase characterized in previous work by Raman spectroscopy was the same monoclinic phase characterized in different work by TEM and could be produced by direct laser heating of metal in air.
Prediction of Mechanical Properties of Rare-Earth Magnesium Alloys Based on Convolutional Neural Networks
Authors: Cheng Mei , Jia Xiya , Zhang Zhimin
Published: October 2024

Rare-earth magnesium alloys exhibit higher comprehensive mechanical properties compared to other series of magnesium alloys, effectively expanding their applications in aerospace, weapons, and other fields. In this work, the tensile strength, yield strength, and elongation of a Mg-Gd-Y-Zn-Zr rare-earth magnesium alloy under different process conditions were determined, and a large number of microstructure observations and analyses were carried out for the tensile specimens; a prediction model of the corresponding mechanical properties was established by using a convolutional neural network (CNN), in which the metallographic diagram of the rare-earth magnesium alloy was taken as the input, and the corresponding tensile strength, yield strength, elongation, and three mechanical properties were taken as the output. The stochastic gradient descent (SGD) algorithm was used for parameter optimization and experimental validation, and the results showed that the average relative errors of the tensile strength and yield strength prediction results were 1.90% and 3.14%, respectively, which were smaller than the expected error of 5%.
Influence of Centerline Segregation Region on the Hydrogen Embrittlement Susceptibility of API 5L X80 Pipeline Steels
Authors: Lima dos Santos Mathews , Filgueira de Almeida Arthur , de Sousa Figueiredo Guilherme Gadelha , da Silva Marcos Mesquita , Maciel Theophilo Moura , Santos Tiago Felipe Abreu , de Santana Renato Alexandre Costa
Published: October 2024

The influence of the centerline segregation region (CSR) on the hydrogen embrittlement (HE) of two different API 5L X80 pipeline steel plates was investigated. The novelty of this work was to establish relationships between the CSR, microstructure, and distribution of localized fragile particles on HE susceptibility and on fracture morphology. This work intended to establish a relationship between centerline segregation and HE susceptibility in high-strength low-alloy steels submitted to inhomogeneous transformations. Microscopy, hydrogen permeation, and slow strain rate (SSR) tests were used to investigate hydrogen-related degradation. The solution used on the charging cell of the permeation tests—and on the SSR test cell—was 0.5 mol L−1 H2SO4 + 10 mg L−1 As2O3, and in the oxidation cell, 0.1 M NaOH was used as a solution. The CSR led the thicker plate to present the highest HE index (0.612) in analyses carried out in the mid-thickness; however, the same plate showed the lowest HE index in near-surface tests. The presence of hydrogen changed the fracture morphology from ductile to a brittle and ductile feature; this occurred due to the interaction with localized fragile particles and the significant reduction of the shear stress necessary for the dislocation movement.
Preparation and Characterization of Ni-Mn-Ga-Cu Shape Memory Alloy with Micron-Scale Pores
Authors: Wang Kunyu , Wang Zhiqiang , Li Yunlong , Zhu Jie , Ding Zhiyi
Published: October 2024

Porous Ni-Mn-Ga shape memory alloys (SMAs) were prepared by powder metallurgy using NaCl as a pore-forming agent with an average pore size of 20–30 μm. The microstructure, phase transformation, superelasticity, and elastocaloric properties of the porous alloys were investigated. The prepared porous alloy had a uniform pore distribution and interconnected microchannels were formed. Cu doping can effectively improve the toughness of a porous alloy, thus improving the superelasticity. It was found that porous Ni-Mn-Ga-Cu SMAs have a flat stress plateau, which exhibits a maximum elongation of 5% with partially recoverable strain and a critical stress for martensite transformation as low as about 160 MPa. In addition, an adiabatic temperature change of 0.6 K was obtained for the prepared porous alloy at a strain of 1.2% at about 150 MPa. This work confirms that the introduction of porous structures into polycrystalline Ni-Mn-Ga SMAs is an effective way to reduce costs and improve performance, and provides opportunities for engineering applications.
Editorial for the Special Issue on Nanomaterials for Micro/Nanodevices
Authors: Idrisi Amir Hussain
Published: October 2024

The Special Issue of Micromachines, titled “Nanomaterials for Micro/Nanodevices”, comprehensively examines the intersection of nanotechnology and micro/nanodevices [...]
A Lightweight SPI-Flash Controller Based on AMBA AHB-Lite Bus
Authors: Li Bingzheng , Wang Weike , Chu Hanbing , Liu Zixuan , Wang Wei
Published: October 2024

The utilization of SPI-Flash in embedded systems is widespread, primarily serving as program storage during the boot process. As a result, the boot process is influenced to some extent by the SPI-Flash controller. This paper presents a lightweight SPI-Flash controller that simplifies the boot process design by establishing a direct connection between the SPI-Flash and AHB-lite bus interface, enabling rapid program execution in RAM instead of directly from the SPI-Flash. Additionally, the controller can function as a bare-metal program downloader for testing the boot process functionality during FPGA-based SoC (system-on-chip) prototype verification. The system-level simulation and FPGA verification results demonstrate that the proposed SPI-Flash controller successfully achieves its intended functional impact in operations to target the Micron N25Q256A SPI-Flash chip, boot process design, and bare-metal program download. The synthesis results under the SMIC 180 nm 1P8M technology process indicate that this SPI-Flash controller exhibits remarkable performance, power consumption, and area utilization. The source code of the proposed lightweight SPI-Flash controller has been uploaded to GitHub as an open-source project.
A Review of Mineral Prospectivity Mapping Using Deep Learning
Authors: Sun Kang , Chen Yansi , Geng Guoshuai , Lu Zongyue , Zhang Wei , Song Zhihong , Guan Jiyun , Zhao Yang , Zhang Zhaonian
Published: October 2024

Mineral resources are of great significance in the development of the national economy. Prospecting and forecasting are the key to ensure the security of mineral resources supply, promote economic development, and maintain social stability. The methods for prospecting prediction have evolved from qualitative to quantitative prediction, from empirical research to mathematical analysis. In recent years, deep learning algorithms have gradually entered the attention of geologists due to their robust learning and simulation ability in the application of prospecting prediction. Deep learning algorithms can effectively analyze and predict data, which have great significance in improving the efficiency and accuracy of mineral exploration. However, there are not many specific examples of their application in mineral exploration prediction, and researchers have not yet conducted a comprehensive discussion on the advantages, disadvantages, and accuracy of deep learning algorithms in mineral prospectivity mapping applications. This paper reviews and discusses the application of deep learning in prospecting prediction, highlighting the challenges faced by deep learning in the application of prospecting prediction in data preprocessing, data enhancement, system parameter adjustment, and accuracy evaluation, and puts forward specific suggestions for research in these aspects. The purpose of this paper is to provide a reference for the application of deep learning to researchers and practitioners in the field of prospecting prediction.
Determination of Plasmalogen Molecular Species in Hen Eggs
Authors: Miyazawa Taiki , Higuchi Ohki , Sogame Ryosuke , Miyazawa Teruo
Published: October 2024

(1) Background: Plasmalogens are vinyl ether-type glycerophospholipids that are characteristically distributed in neural tissues and are significantly reduced in the brains of individuals with dementia compared to those in healthy subjects, suggesting a link between plasmalogen deficiency and cognitive decline. Hen eggs are expected to be a potential source of dietary plasmalogens, but the details remain unclear. (2) Methods: We evaluated the fresh weight, dry weight, total lipid, neutral lipids, glycolipids, and phospholipids in the egg yolk and egg white of hen egg. Then, the molecular species of plasmalogens were quantified using HPLC-ESI-MS/MS. (3) Results: In egg yolk, the total plasmalogen content was 1292.1 µg/100 g fresh weight and predominantly ethanolamine plasmalogens (PE-Pls), specifically 18:0/22:6-PE-Pls, which made up 75.6 wt% of the total plasmalogen. In egg white, the plasmalogen content was 31.4 µg/100 g fresh weight and predominantly PE-Pls, specifically 18:0/20:4-PE-Pls, which made up 49.6 wt% of the total plasmalogen. (4) Conclusions: Plasmalogens were found to be more enriched in egg yolk than in egg white. It was found that humans are likely to ingest almost 0.3 mg of total plasmalogens from one hen egg. These findings highlight the importance of plasmalogens in the daily diet, and it is recommended to explore the impact of long-term dietary plasmalogen intake to assess its effect on human health. This provides a viewpoint for the development of new food products.
The Neuroprotective Role of Cyanobacteria with Focus on the Anti-Inflammatory and Antioxidant Potential: Current Status and Perspectives
Authors: Rodrigues Flávia , Reis Mariana , Ferreira Leonor , Grosso Clara , Ferraz Ricardo , Vieira Mónica , Vasconcelos Vitor , Martins Rosário
Published: October 2024

Neurodegenerative diseases are linked to the process of neurodegeneration. This can be caused by several mechanisms, including inflammation and accumulation of reactive oxygen species. Despite their high incidence, there is still no effective treatment or cure for these diseases. Cyanobacteria have been seen as a possible source for new compounds with anti-inflammatory and antioxidant potential, such as polysaccharides (sacran), phycobiliproteins (phycocyanin) and lipopeptides (honaucins and malyngamides), which can be interesting to combat neurodegeneration. As a promising case of success, Arthrospira (formerly Spirulina) has revealed a high potential for preventing neurodegeneration. Additionally, advantageous culture conditions and sustainable production of cyanobacteria, which are allied to the development of genetic, metabolic, and biochemical engineering, are promising. The aim of this review is to compile and highlight research on the anti-inflammatory and antioxidant potential of cyanobacteria with focus on the application as neuroprotective agents. Also, a major goal is to address essential features that brand cyanobacteria as an ecoefficient and economically viable option, linking health to sustainability.
Silver Nanoparticles in Therapeutics and Beyond: A Review of Mechanism Insights and Applications
Authors: Eker Furkan , Duman Hatice , Akdaşçi Emir , Witkowska Anna Maria , Bechelany Mikhael , Karav Sercan
Published: October 2024

Silver nanoparticles (NPs) have become highly promising agents in the field of biomedical science, offering wide therapeutic potential due to their unique physicochemical properties. The unique characteristics of silver NPs, such as their higher surface-area-to-volume ratio, make them ideal for a variety of biological applications. They are easily processed thanks to their large surface area, strong surface plasmon resonance (SPR), stable nature, and multifunctionality. With an emphasis on the mechanisms of action, efficacy, and prospective advantages of silver NPs, this review attempts to give a thorough overview of the numerous biological applications of these particles. The utilization of silver NPs in diagnostics, such as bioimaging and biosensing, as well as their functions in therapeutic interventions such as antimicrobial therapies, cancer therapy, diabetes treatment, bone repair, and wound healing, are investigated. The underlying processes by which silver NPs exercise their effects, such as oxidative stress induction, apoptosis, and microbial cell membrane rupture, are explored. Furthermore, toxicological concerns and regulatory issues are discussed, as well as the present difficulties and restrictions related to the application of silver NPs in medicine.
Double-Layer Metasurface Integrated with Micro-LED for Naked-Eye 3D Display
Authors: Sun Qinyue , Tian Zhenhuan , Xu Chuangcheng , Yu Angsu , Li Feng , Yun Feng
Published: October 2024

Naked-eye 3D micro-LED display combines the characteristics of 3D display with the advantages of micro-LED. However, the 3D micro-LED display is still at the conceptual stage, limited by its intrinsic emission properties of large divergence angle and non-coherence, as well as difficulties in achieving large viewing angles with high luminous efficiency. In this work, we propose a double-layer metasurface film integrating functions of collimation with multiple deflections, constituting a micro-LED naked-eye 3D display system. The system is characterized through numerical simulations using the 3D finite-difference time-domain method. The simulation results show that the double-layer metasurface film restricts 90% of the emitted light of the micro-LED to the vicinity of the 0° angle, improving its spatial coherence. Subsequently, a large-angle, low-crosstalk outgoing from −45° to 45° is achieved, while providing a deflection efficiency of over 80% and a pixel density of up to 605. We believe this design provides a feasible approach for realizing naked-eye 3D micro-LED displays with a large field of view, low crosstalk, and high resolution.
Comparison of Dietary Supplementation with Krill Oil, Fish Oil, and Astaxanthin on an Experimental Ethanol-Induced Gastric Ulcer Model: A Biochemical and Histological Study
Authors: Sarıyer Esra Tansu , Baş Murat , Çolak Hatice , Özkan Yenal Naziye , Unay Demirel Özlem , Yüksel Meral
Published: October 2024

Background/Objectives: Despite advances in ulcer treatment research, the search for new, safe, and effective strategies for preventing and treating ulcer diseases persists. Methods: In this study, the protective effects of dietary supplementation with krill oil (KO), fish oil (FO), and astaxanthin (ASX) on an ethanol-induced gastric ulcer model were compared during biochemical and histological observations. Sprague–Dawley (n = 64) rats randomly divided into four groups—normal control (vehicle), KO, FO, and ASX groups—received the supplements via the orogastric route at a rate of 2.5% (v/w) of their daily feed consumption for 4 weeks. Then, ulcer induction was performed with ethanol. Results: The ulcer group showed increased levels of malondialdehyde (MDA), chemiluminescence (CL), and myeloperoxidase (MPO) activity and decreased levels of glutathione in the gastric tissues. While KO, FO, and ASX supplementation decreased chemiluminescence levels in the ulcer group, only ASX supplementation decreased MDA levels and MPO activity. Conclusions: In conclusion, supplementation with KO or FO has a similar protective effect against ethanol-induced ulcer damage, as it inhibits ROS formation and reduces lipid peroxidation. However, ASX supplementation has a higher protective effect than KO or FO supplementations against experimental ethanol-induced gastric lesions in rats, as it inhibits ROS formation and reduces neutrophil infiltration and lipid peroxidation.
Cardiovascular Health and Diet Quality among Vegetarians, Vegans and Omnivores: Insights from a Large Urban Population in Poland
Authors: Grygorczuk Oliwia , Mrozik Martyna , Lipert Anna , Kamińska Sylwia , Białas Adam , Drygas Wojciech , Rębowska Ewa , Łęgocki Stanisław , Jegier Anna , Szmigielska Katarzyna , Kwaśniewska Magdalena
Published: October 2024

Background/Objectives: Dietary habits are among the most significant determinants of health. The aim of this study was to assess the nutritional quality and cardiovascular profiles of individuals following plant-based diet. Methods: The study population comprised 199 individuals (136 women, 63 men; mean age 33.9  ±  8.9 years) including vegans (VG; n = 50), vegetarians (VN; n = 101) and omnivores (OV; n = 48). In this analysis the following procedures were assessed: a questionnaire interview, anthropometric and blood pressure measurements, and a blood sample collection. Dietary patterns were evaluated using the Food Frequency Questionnaire and a 24-h dietary recall. Results: Vegans exhibited the lowest protein intake relative to the other groups (p < 0.05) and a significantly higher intake of polyunsaturated fatty acids and lower intake of cholesterol compared to VN and OV (p < 0.05). Vegans had significantly lower levels of serum cholesterol, LDL cholesterol, and triglycerides, fasting glucose and high-sensitivity C-reactive protein (p < 0.05). No cases of overweight or obesity were observed among VN and VG participants. No instances of impaired fasting glucose or elevated blood pressure were noted among vegans. Hypercholesterolemia was identified in 56.2% of OV, 26.7% in VN and 16.0% in VG (p < 0.05), elevated blood pressure was recorded in one vegetarian and in 6.2% of OV participants. Conclusions: Our research indicates that plant-based diets are associated with a better cardiovascular profile compared to traditional diets. Moreover, suboptimal intake of essential nutrients, underscores the need for more effective public health interventions and improved nutrition education regardless of dietary patterns.
Epigenetic Regulation in Myocardial Fibroblasts and Its Impact on Cardiovascular Diseases
Authors: Komal Sumra , Gao Yuan , Wang Zhi-Mo , Yu Qing-Wen , Wang Pei , Zhang Li-Rong , Han Sheng-Na
Published: October 2024

Myocardial fibroblasts play a crucial role in heart structure and function. In recent years, significant progress has been made in understanding the epigenetic regulation of myocardial fibroblasts, which is essential for cardiac development, homeostasis, and disease progression. In healthy hearts, cardiac fibroblasts (CFs) play a crucial role in synthesizing the extracellular matrix (ECM) when in a dormant state. However, under pathological and environmental stress, CFs transform into activated fibroblasts known as myofibroblasts. These myofibroblasts produce an excess of ECM, which promotes cardiac fibrosis. Although multiple molecular mechanisms are associated with CF activation and myocardial dysfunction, emerging evidence highlights the significant involvement of epigenetic regulation in this process. Epigenetics refers to the heritable changes in gene expression that occur without altering the DNA sequence. These mechanisms have emerged as key regulators of myocardial fibroblast function. This review focuses on recent advancements in the understanding of the role of epigenetic regulation and emphasizes the impact of epigenetic modifications on CF activation. Furthermore, we present perspectives and prospects for future research on epigenetic modifications and their implications for myocardial fibroblasts.
Establishment of a Genetic Transformation and Gene Editing Method by Floral Dipping in Descurainia sophia
Authors: Jia Tianjiao , Yang Hua , Zhou Dingding , Zhao Sanzeng , Wang Jianyong , Zhang Tao , Huang Mingkun , Kong Danyu , Liu Yi
Published: October 2024

Descurainia sophia L. Webb ex Prantl is used in traditional medicine globally. However, the lack of an efficient and reliable genetic transformation system has seriously limited the investigation of gene function and further utilization of D. sophia. In this study, a highly efficient, time-saving, and cost-effective Agrobacterium tumefaciens-mediated genetic transformation system has been developed in D. sophia. In this method, the transformation was accomplished by simply dipping developing D. sophia inflorescences for 45 s into an Agrobacterium suspension (OD600 = 0.6) containing 5% sucrose and 0.03% (v/v) Silwet L-77. Treated plants were allowed to set seeds which were then plated on a selective medium with hygromycin B (HygB) to screen transformants. Additionally, the CRISPR/Cas9 genomic editing system was validated by targeting phytoene desaturase (PDS) gene using this floral dip method, and mutant plants with the expected albino phenotype could be obtained in 2.5 months. This genetic transformation and targeted editing system will be a valuable tool for routine investigation of gene function and further exploitation in D. sophia.
A Contact Mechanics Model for Surface Wear Prediction of Parallel-Axis Polymer Gears
Authors: Muratović Enis , Pervan Nedim , Muminović Adil , Delić Muamer
Published: October 2024

As surface wear is one of the major failure mechanisms in many applications that include polymer gears, lifetime prediction of polymer gears often requires time-consuming and expensive experimental testing. This study introduces a contact mechanics model for the surface wear prediction of polymer gears. The developed model, which is based on an iterative numerical procedure, employs a boundary element method (BEM) in conjunction with Archard’s wear equation to predict wear depth on contacting tooth surfaces. The wear coefficients, necessary for the model development, have been determined experimentally for Polyoxymethylene (POM) and Polyvinylidene fluoride (PVDF) polymer gear samples by employing an abrasive wear model by the VDI 2736 guidelines for polymer gear design. To fully describe the complex changes in contact topography as the gears wear, the prediction model employs Winkler’s surface formulation used for the computation of the contact pressure distribution and Weber’s model for the computation of wear-induced changes in stiffness components as well as the alterations in the load-sharing factors with corresponding effects on the normal load distribution. The developed contact mechanics model has been validated through experimental testing of steel/polymer engagements after an arbitrary number of load cycles. Based on the comparison of the simulated and experimental results, it can be concluded that the developed model can be used to predict the surface wear of polymer gears, therefore reducing the need to perform experimental testing. One of the major benefits of the developed model is the possibility of assessing and visualizing the numerous contact parameters that simultaneously affect the wear behavior, which can be used to determine the wear patterns of contacting tooth surfaces after a certain number of load cycles, i.e., different lifetime stages of polymer gears.
Study of Styrene Butadiene Rubber Reinforced by Polybutadiene Liquid Rubber-Modified Silica
Authors: Liao Qing , Tang Xiao , Tang Jiao , Tang Jiaxiang , Xia Housheng , Sheng Zhongyi , Zhou Jianping , Niu Junfeng
Published: October 2024

The dispersion of silica in rubber systems and its interaction with rubber are two key factors in the preparation of rubber composites with excellent properties. In view of this, silica modified with terminal isocyanate-based polybutadiene liquid rubber (ITPB) is used to improve the dispersion effect of silica in rubber and enhance its interaction with the rubber matrix to improve the rubber’s performance. The impact of different modification conditions on the dispersion of silica and the properties of modified silica-filled rubber composites were studied by changing the amount of ITPB and the modification method of silica, including blending and chemical grafting. The experimental results show that ITPB is successfully grafted onto silica, and the use of modified silica improves the cross-linking density of rubber, promotes the rate of rubber vulcanization, and overcomes the shortcomings of the delayed vulcanization of silica itself. When the ratio of ITPB liquid rubber to silica equals 1:20, the comprehensive performance of rubber is the best, the ITPB-modified silica has a better dispersion effect in rubber, and the rolling resistance is slightly improved, with tensile strength reaching 12.6 MPa. The material demonstrates excellent overall performance and holds promise for applications in the rail, automotive, and electrical fields.
PVC/CNT Electrospun Composites: Morphology and Thermal and Impedance Behavior
Authors: Briesemeister Marcio , Gómez-Sánchez John A. , Bertemes-Filho Pedro , Pezzin Sérgio Henrique
Published: October 2024

Due to their mechanical robustness and chemical resistance, composite electrospun membranes based on polyvinyl chloride (PVC) are suitable for sensor applications. Aiming to improve the electrical characteristics of these membranes, this work investigated the effects of the addition of carbon nanotubes (CNTs) to PVC electrospun membranes, in terms of morphology and thermal and impedance behavior. Transmission electron microscopy images evidenced that most of the nanotubes were encapsulated within the fibers and oriented along them, while field-emission scanning electron micrographs revealed that the membranes consisted of uniform fibers with an average diameter of 339 ± 31 nm, regardless of the addition of the carbon nanotubes. With respect to the neat resin, the addition of nanotubes caused a significant lowering of the glass transition temperature (up to 20 °C) and a marked change in the second degradation step of PVC. Nyquist plots from electrical impedance spectra showed a charge transfer resistance (RCT) of 38 and 40 MΩ for neat PVC and PVC/CNT 3 wt.% membranes, respectively, indicating that, in the dry state, the encapsulation of CNTs in the fibers and the high porosity of the membranes prevented the formation of a percolation network, increasing the electrical resistance. In the wet state, however, there was a greater change in the impedance behavior, decreasing the resistance RCT to 4.5 and 1.1 MΩ, for neat PVC and PVC/CNT 3 wt.% membranes, respectively. The results of this study, showing a significant variation in impedance behavior between dry and wet membranes, are relevant for the development of various types of sensors based on PVC composites.
Towards Photocrosslinkable Lyotropic Blends of Organosolv Lignin and Hydroxypropyl Cellulose for 3D Printing by Direct Ink Writing
Authors: Yapa Mehmet-Talha , Lalevée Jacques , Laborie Marie-Pierre
Published: October 2024

Polymer blends containing up to 70% organosolv lignin content and lyotropic cellulose derivatives have been established as “lignin inks” for direct ink writing of fully biobased 3D parts. However, a fast-crosslinking mechanism is needed to improve throughput and design space. In this paper, UV-photocrosslinkable organosolv lignin/hydroxypropyl cellulose inks are formulated through doping with common photocrosslinkers. The most potent photocrosslinkers for neat hydroxypropyl cellulose, lignin and their blends are determined through a series of DOEs. Hydroxypropyl cellulose is significantly more amenable to photocrosslinking than organosolv lignin. The optimal photocrosslinkable ink formulations are printable and exhibit up to 70% gel content, although thermal post-curing remains essential. Chemical, thermal, and mechanical investigations of the photocrosslinked 3D parts evidence efficient crosslinking of HPC through its hydroxyl groups, while lignin appears internally plasticized and/or degraded during inefficient photocrosslinking. Despite this, photocrosslinkable inks exhibit improved tensile properties, shape flexibility, and fidelity. The heterogeneous crosslinking and residual creep highlight the need to further activate lignin for homogeneous photocrosslinking in order to fully exploit the potential of lignin inks in DIW.
Daily Streamflow Forecasting Using AutoML and Remote-Sensing-Estimated Rainfall Datasets in the Amazon Biomes
Authors: Bodini Matteo
Published: October 2024

Reliable streamflow forecasting is crucial for several tasks related to water-resource management, including planning reservoir operations, power generation via Hydroelectric Power Plants (HPPs), and flood mitigation, thus resulting in relevant social implications. The present study is focused on the application of Automated Machine-Learning (AutoML) models to forecast daily streamflow in the area of the upper Teles Pires River basin, located in the region of the Amazon biomes. The latter area is characterized by extensive water-resource utilization, mostly for power generation through HPPs, and it has a limited hydrological data-monitoring network. Five different AutoML models were employed to forecast the streamflow daily, i.e., auto-sklearn, Tree-based Pipeline Optimization Tool (TPOT), H2O AutoML, AutoKeras, and MLBox. The AutoML input features were set as the time-lagged streamflow and average rainfall data sourced from four rain gauge stations and one streamflow gauge station. To overcome the lack of training data, in addition to the previous features, products estimated via remote sensing were leveraged as training data, including PERSIANN, PERSIANN-CCS, PERSIANN-CDR, and PDIR-Now. The selected AutoML models proved their effectiveness in forecasting the streamflow in the considered basin. In particular, the reliability of streamflow predictions was high both in the case when training data came from rain and streamflow gauge stations and when training data were collected by the four previously mentioned estimated remote-sensing products. Moreover, the selected AutoML models showed promising results in forecasting the streamflow up to a three-day horizon, relying on the two available kinds of input features. As a final result, the present research underscores the potential of employing AutoML models for reliable streamflow forecasting, which can significantly advance water-resource planning and management within the studied geographical area.
Assessing the Influence of the Knowledge Management Cycle on Job Satisfaction and Organizational Culture Considering the Interplay of Employee Engagement
Authors: Obeng Hayford Asare , Arhinful Richard , Mensah Leviticus , Owusu-Sarfo Jerry Seth
Published: October 2024

This study leveraged the social exchange theory to explore the influence of the knowledge management cycle on employee engagement, job satisfaction, and organizational culture within the Ghana Highway Authority (GHA). The structural equation modeling (SEM) software (AMOS version 23) was employed to analyze data from 300 GHA employees. The study used snowball sampling and a descriptive cross-sectional methodology to collect data through printed and electronic questionnaires. The findings demonstrated a substantial and positive impact of the knowledge management cycle on employee engagement, job satisfaction, and organizational commitment. Employee engagement also exhibited a significant and positive influence on both job satisfaction and organizational commitment. Furthermore, employee engagement partially mediated the relationships between the knowledge management cycle, job satisfaction, and organizational commitment. This study’s findings underscore the practical implications of allocating resources to knowledge management activities. Such allocation can promote organizational culture and employee satisfaction, enabling firms to achieve real gains.
Developing a Sustainable Digital Transformation Roadmap for SMEs: Integrating Digital Maturity and Strategic Alignment
Authors: Mick Marcela Marçal Alves Pinto , Kovaleski João Luiz , Mick Rafael Luis , Chiroli Daiane Maria de Genaro
Published: October 2024

Digital transformation (DT) is crucial for SMEs to streamline operational efficiency, foster innovation, and meet upcoming challenges. Integrating sustainability into this process not only enhances a company’s reputation but also attracts customers and investors who value environmental responsibility. Despite this opportunity, many SMEs operate without clear plans and strategies. The literature review identified a lack of roadmaps that integrate sustainability into the digital transformation process for SMEs. Thus, this paper aims to propose a sustainable digital transformation roadmap for SMEs that evaluates their digital maturity and facilitates gradual implementation in alignment with their strategic objectives. A systematic literature review using the Methodi Ordinatio defined six key dimensions of digital transformation. Consequently, the SDT-SMEs Roadmap was developed, drawing on ISO/IEC 33000 standards to offer well-defined processes for enhancing digital competencies. The roadmap features three organizational planning levels—strategic, tactical, and operational—and includes a maturity model that evaluates 75 processes across six dimensions: Digital Technologies, Customer Focus, Organizational Culture, Organizational Governance, People, and Sustainability. Validation through a case study confirmed the roadmap’s effectiveness in addressing real-world challenges and guiding SMEs through the digitization process. The SDT-SMEs Roadmap provides a comprehensive and integrated approach, ensuring continuous adaptation and improvement in sustainable digital transformation efforts. This roadmap addresses a significant gap in the literature and presents a practical, strategic, and adaptable pathway for SMEs embarking on their digital transformation journeys.
Verification of On-Site Applicability of Rainwater Road Surface Spraying for Promoting Rainwater Utilization and Analyzing the Fine Dust Reduction Effect
Authors: Lee JungMin , Choi JongSoo , Kim MyeongIn , Cho YoungTae , Kim JaeKyoung , Cho PilKyu
Published: October 2024

This study conducted a pilot test and field demonstration to analyze the feasibility of using rainwater for road surface sprinkling and its effectiveness in reducing fine dust to create sustainable cities. The pilot test results verified the effectiveness of rainwater sprinkling on road surfaces in reducing fine dust. Subsequently, to ensure field applicability, a test bed with different pavement sections was established along Ojeong-ro in Bucheon, Gyeonggi-do, and a circulatory system for reusing the runoff rainwater was installed and tested for its acceptable dust reduction effectiveness. The results showed that the section with porous pavement exhibited a significant reduction in acceptable dust levels, and a trend of decreasing pollutant levels due to the initial washing effect of rainwater was observed. However, the water quality and quantity analysis revealed that additional purification processes are necessary to reuse the water for road surface sprinkling. Based on these findings, this study suggests that expanding porous pavement and introducing purification systems are essential for installing rainwater utilization facilities to reduce fine dust in urban areas. This research provides critical foundational data that can contribute to urban environmental improvement and establish a sustainable water circulation system.
Eco-Friendly Photocatalytic Treatment of Dyes with Ag Nanoparticles Obtained through Sustainable Process Involving Spirulina platensis
Authors: Sidorowicz Agnieszka , Fais Giacomo , Desogus Francesco , Loy Francesco , Licheri Roberta , Lai Nicola , Cao Giacomo , Concas Alessandro
Published: October 2024

The development of efficient photocatalysts is crucial in addressing water pollution concerns, specifically in the removal of organic dyes from wastewater. In this context, the use of silver nanoparticles (Ag NPs) might represent a method to achieve high dye degradation efficiencies. On the other hand, the classical Ag NP production process involves several reactants and operating conditions, which make it poorly sustainable. In the present work, Ag NPs were synthesized according to a new sustainable process involving the use of natural extracts of Spirulina platensis and milder operating conditions. The material was also calcined to determine the influence of organic content on the properties of Ag NPs. The X-ray diffraction (XRD) analysis displayed the AgCl and Ag phases with a crystalline size of 11.79 nm before calcination. After calcination, only the Ag phase was present with an increased crystalline size of 24.60 nm. Fourier Transform Infrared Spectroscopy (FTIR) confirmed the capping role of the metabolites from the extract. Scanning Electron Microscopy (SEM) and Transmission Electron Microscopy (TEM) revealed the spherical or quasi-spherical morphologies with agglomeration due to the calcination. Energy-dispersive X-ray spectroscopy (EDX) and Thermogravimetric (TGA) analyses further confirmed the involvement of metabolites in the synthesis of Ag NPs. The optical changes in the products were observed in a UV-Vis analysis. The Ag NPs were tested for their photocatalytic activity against the laboratory dye brilliant blue r in visible light in various conditions. The highest degradation efficiency of 81.9%, with a kapp value of 0.00595 min−1, was observed in alkaline medium after 90 min of light irradiation.
Promising Phytogenic Feed Additives Used as Anti-Mycotoxin Solutions in Animal Nutrition
Authors: Quesada-Vázquez Sergio , Codina Moreno Raquel , Della Badia Antonella , Castro Oscar , Riahi Insaf
Published: October 2024

Mycotoxins are a major threat to animal and human health, as well as to the global feed supply chain. Among them, aflatoxins, fumonisins, zearalenone, T-2 toxins, deoxynivalenol, and Alternaria toxins are the most common mycotoxins found in animal feed, with genotoxic, cytotoxic, carcinogenic, and mutagenic effects that concern the animal industry. The chronic negative effects of mycotoxins on animal health and production and the negative economic impact on the livestock industry make it crucial to develop and implement solutions to mitigate mycotoxins. In this review, we summarize the current knowledge of the mycotoxicosis effect in livestock animals as a result of their contaminated diet. In addition, we discuss the potential of five promising phytogenics (curcumin, silymarin, grape pomace, olive pomace, and orange peel extracts) with demonstrated positive effects on animal performance and health, to present them as potential anti-mycotoxin solutions. We describe the composition and the main promising characteristics of these bioactive compounds that can exert beneficial effects on animal health and performance, and how these phytogenic feed additives can help to alleviate mycotoxins’ deleterious effects.