bluuebunny/crossref_metadata_2025 huggingface dataset:
The Contribution of Genetic and Epigenetic Factors: An Emerging Concept in the Assessment and Prognosis of Inflammatory Bowel Diseases
Authors: Minea Horia , Singeap Ana-Maria , Minea Manuela , Juncu Simona , Muzica Cristina , Sfarti Catalin Victor , Girleanu Irina , Chiriac Stefan , Miftode Ioana Diandra , Stanciu Carol , Trifan Anca
Published: August 2024

Inflammatory bowel disease (IBD) represents heterogeneous and relapsing intestinal conditions with a severe impact on the quality of life of individuals and a continuously increasing prevalence. In recent years, the development of sequencing technology has provided new means of exploring the complex pathogenesis of IBD. An ideal solution is represented by the approach of precision medicine that investigates multiple cellular and molecular interactions, which are tools that perform a holistic, systematic, and impartial analysis of the genomic, transcriptomic, proteomic, metabolomic, and microbiomics sets. Hence, it has led to the orientation of current research towards the identification of new biomarkers that could be successfully used in the management of IBD patients. Multi-omics explores the dimension of variation in the characteristics of these diseases, offering the advantage of understanding the cellular and molecular mechanisms that affect intestinal homeostasis for a much better prediction of disease development and choice of treatment. This review focuses on the progress made in the field of prognostic and predictive biomarkers, highlighting the limitations, challenges, and also the opportunities associated with the application of genomics and epigenomics technologies in clinical practice.
AI-Driven Deep Learning Techniques in Protein Structure Prediction
Authors: Chen Lingtao , Li Qiaomu , Nasif Kazi Fahim Ahmad , Xie Ying , Deng Bobin , Niu Shuteng , Pouriyeh Seyedamin , Dai Zhiyu , Chen Jiawei , Xie Chloe Yixin
Published: August 2024

Protein structure prediction is important for understanding their function and behavior. This review study presents a comprehensive review of the computational models used in predicting protein structure. It covers the progression from established protein modeling to state-of-the-art artificial intelligence (AI) frameworks. The paper will start with a brief introduction to protein structures, protein modeling, and AI. The section on established protein modeling will discuss homology modeling, ab initio modeling, and threading. The next section is deep learning-based models. It introduces some state-of-the-art AI models, such as AlphaFold (AlphaFold, AlphaFold2, AlphaFold3), RoseTTAFold, ProteinBERT, etc. This section also discusses how AI techniques have been integrated into established frameworks like Swiss-Model, Rosetta, and I-TASSER. The model performance is compared using the rankings of CASP14 (Critical Assessment of Structure Prediction) and CASP15. CASP16 is ongoing, and its results are not included in this review. Continuous Automated Model EvaluatiOn (CAMEO) complements the biennial CASP experiment. Template modeling score (TM-score), global distance test total score (GDT_TS), and Local Distance Difference Test (lDDT) score are discussed too. This paper then acknowledges the ongoing difficulties in predicting protein structure and emphasizes the necessity of additional searches like dynamic protein behavior, conformational changes, and protein–protein interactions. In the application section, this paper introduces some applications in various fields like drug design, industry, education, and novel protein development. In summary, this paper provides a comprehensive overview of the latest advancements in established protein modeling and deep learning-based models for protein structure predictions. It emphasizes the significant advancements achieved by AI and identifies potential areas for further investigation.
A Review of Global Efforts in BIM Adoption for Road Infrastructure
Authors: Nielsen Otto Araujo , Miceli Giuseppe , Ferreira Filho Altair dos Santos , Pellanda Paulo César
Published: August 2024

This review article examines global initiatives in the adoption of building information modeling (BIM) for road infrastructure. It begins with an overview of the distinctions between BIM applications for buildings and infrastructure projects. This study evaluates noteworthy BIM publications (NBPs) from various countries and organizations to understand BIM’s transformative impact on roadway infrastructure projects. It analyzes the evolution of these publications, compares academic output with NBP, identifies the stages of BIM maturity, and evaluates adherence to ISO 19650 standards. Through this analysis, the article presents current global and regional scenarios, providing a comprehensive overview of the current state and future prospects of BIM implementation in the road infrastructure sector.
Lack of Neuromuscular Fatigue Due to Recreational Doubles Pickleball
Authors: Martin Eric , Ritchey Matthew , Kim Steven , Falknor Margaret , Beckham George
Published: August 2024

Background: The lack of knowledge about physical responses to pickleball creates a clear gap about performance in this sport. The purpose of this study was to investigate neuromuscular fatigue caused by playing doubles pickleball. Methods: Recreational pickleball players (n = 32, mean age = 60.0 years) were recruited to perform sets of four countermovement jumps (CMJs) on a force plate before and after doubles pickleball matches. Results: For players who had not played a match prior to testing, there was a significant learning effect across trials within the baseline set of jumps for five outcomes from the CMJ test, including propulsive peak force (p = 0.005); however, there was no significant learning effect for jump height. There were significant improvements in the large effect size for all except one dependent variable (propulsive phase time) between the first and second set of jumps (i.e., after one match). Neither further increases nor decreases were seen after the second set of jumps. Conclusions: Participants saw significant increases in CMJ performance across trials after one pickleball match, indicating learning and potentiation effects. After three matches of doubles pickleball, no fatigue effect was detected.
Effect of Photo-Crosslinking Conditions on Thermal Conductivity of Photo-Curable Ladder-like Polysilsesquioxane–Al2O3 Nanocomposites
Authors: Romeo Chiara , Fredi Giulia , Callone Emanuela , Parrino Francesco , Dirè Sandra
Published: August 2024

The miniaturization and high-power density of modern electronic devices pose significant thermal management issues, particularly affecting their performance and lifetime. Ladder-like polysilsesquioxanes (LPSQs) offer a promising solution due to their remarkable thermal, mechanical, and chemical properties. By incorporating thermally conductive fillers, LPSQ composites can achieve high thermal conductivity (TC), making them ideal for thermal management in advanced electronic applications. In this study, LPSQ-based nanocomposites containing functionalized alumina nanoparticles were prepared by solution casting and UV curing, and the effects of varying amounts of Irgacure-184 photoinitiator on their structural and thermal properties were investigated. Three sets of samples were prepared with a fixed amount of LPSQs, 80 wt.% of nanoparticles, and 1, 5, or 10 wt.% of photoinitiator with respect to the matrix. TC was evaluated from the measured values of heat capacity, density, and thermal diffusivity. TC values increased by 60%, 71.2%, and 93.1% for the three samples, respectively, compared to the neat matrix. Results indicate that an intermediate amount of photoinitiator (5%) preserved LPSQs’ structural integrity, namely the presence of long linear silsesquioxane chains, and provided good filler dispersion and distribution, high polymerization degree, thermal stability, and high TC.
Investigation on the Mechanical and Thermal Properties of Jute/Carbon Fiber Hybrid Composites with the Inclusion of Crab Shell Powder
Authors: Kocharla Ravi Prakash Babu , Bandlamudi Raghu Kumar , Mirza Abdul Ahad , Kolli Murahari , Shanmugam Ragavanantham , Cheepu Muralimohan
Published: August 2024

In recent years, natural fiber-reinforced hybrid composites have been utilized in many applications because of their lower cost, biodegradability, and low density. The aim of this research is to convert crab shell waste into an effective reinforcement in jute/carbon fiber hybrid composites. Various weight percentages of crab shell powder (0%, 1%, 3%, 5%, and 7%) were used to prepare crab shell powder hybrid composites. The performance of the crab shell powder hybrid composites was evaluated by preparing the specimens to conduct tensile, flexural, impact, and hardness tests as per ASTM standards. The results show that the inclusion of 5% crab shell powder displayed a better enhancement in the properties of the hybrid composite compared to other weight percentages. The tensile, flexural, and impact strengths of the 5% crab shell powder hybrid composite increased by 21%, 52%, and 50%, respectively. Also, the hardness of the hybrid composite was enhanced by 33%. Scanning electron microscopy (SEM) tests were conducted on the tensile-fractured specimen surfaces, and their morphology and structure confirmed the presence of a well-bonded interface between the fiber and matrix. Differential Scanning Calorimetry (DSC) and Thermogravimetry (TG) analysis have shown that the crystallization behavior and thermal stability of the composite were enhanced with the inclusion of crab shell powder. The presence of crab shell powder in the hybrid composite was identified using SEM with Energy-Dispersive X-ray Spectroscopy (EDS).
The Ocular Surface–Gut Axis in Spaceflight: Implications of Intestinal Changes in Microgravity on Tear Film Physiology
Authors: Sampige Ritu , Ong Joshua , Waisberg Ethan , Berdahl John , Lee Andrew G.
Published: August 2024

With increasing space exploration, there is a rising need to evaluate the impact of spaceflight on astronauts’ health, including the effects of space-associated hazards such as microgravity. Astronauts’ reports of experienced symptoms upon spaceflight include a notable prevalence of dry eye disease (DED). Hence, there is a pressing need to understand the pathogenesis and mechanism behind space-associated DED onset, which will subsequently guide the development of necessary therapies to reduce dry eye symptoms among astronauts. One critical effect of spaceflight includes alterations to the gut microbiome. On Earth, the prior literature has established the presence of an ocular surface–gut axis and the potential role of gut dysbiosis in DED onset. Meanwhile, the literature about astronauts’ health underscores the presence of space-associated gut microbiome composition alterations and the presence of DED separately. Therefore, in this opinion article, we review and present the current literature regarding the ocular surface–gut axis on Earth and regarding potential translations to spaceflight. We present the view that, based on the existing literature, the ocular surface–gut axis may be a critical mechanism for the pathogenesis of DED in space, and this axis needs to be further explored in the context of identifying ways to reduce astronauts’ experiences of DED during spaceflight.
Aging, Age-Related Diseases, and the Zebrafish Model
Authors: Abou-Dahech Mariam Sami , Williams Frederick E.
Published: August 2024

The entrance of cells into a permanent state of cell cycle arrest with the ability to resist apoptosis is termed “cellular senescence”. The accumulation of senescent cells within the body can lead to tissue aging and the dysfunction of organs. Whether due to external stressors or the passage of time, aging is an inevitable process that afflicts every living being. Current studies that investigate aging rely on the use of cells or rodent models. Although cells present a cost-effective and quick way to analyze aging, they lack the complexity of whole-body systems and therefore require the use of an in vivo model post-in vitro assays. The zebrafish, Danio rerio, presents a cost-effective model with quick development and large numbers of offspring. These fish share 70% similarity of their genes with humans, including genes known to be associated with human diseases, such as those diseases of aging and/or senescence, like Alzheimer’s disease. Major tissues and organs of humans are also found in these fish, and therefore, zebrafish can serve as a useful model when studying diseases, aging, Alzheimer’s disease, and other disorders. In this review, we will discuss some of the major senescence biomarkers and detection methods, as well as discuss how zebrafish models can be used for the study of aging and age-related disorders.
Semantic Segmentation in Large-Size Orthomosaics to Detect the Vegetation Area in Opuntia spp. Crop
Authors: Duarte-Rangel Arturo , Camacho-Bello César , Cornejo-Velazquez Eduardo , Clavel-Maqueda Mireya
Published: August 2024

This study focuses on semantic segmentation in crop Opuntia spp. orthomosaics; this is a significant challenge due to the inherent variability in the captured images. Manual measurement of Opuntia spp. vegetation areas can be slow and inefficient, highlighting the need for more advanced and accurate methods. For this reason, we propose to use deep learning techniques to provide a more precise and efficient measurement of the vegetation area. Our research focuses on the unique difficulties posed by segmenting high-resolution images exceeding 2000 pixels, a common problem in generating orthomosaics for agricultural monitoring. The research was carried out on a Opuntia spp. cultivation located in the agricultural region of Tulancingo, Hidalgo, Mexico. The images used in this study were obtained by drones and processed using advanced semantic segmentation architectures, including DeepLabV3+, UNet, and UNet Style Xception. The results offer a comparative analysis of the performance of these architectures in the semantic segmentation of Opuntia spp., thus contributing to the development and improvement of crop analysis techniques based on deep learning. This work sets a precedent for future research applying deep learning techniques in agriculture.
mRNA Expression Level of ALK in Neuroblastoma Is Associated with Histological Subtype, ALK Mutations and ALK Immunohistochemical Protein Expression
Authors: Bruinsma Rixt S. , Fiocco Marta F. , de Leng Wendy W. J. , Kester Lennart A. , Langenberg Karin P. S. , Tytgat Godelieve A. M. , van Noesel Max M. , Wijnen Marc H. W. A. , van der Steeg Alida F. W. , de Krijger Ronald R.
Published: August 2024

ALK is related to poor survival in neuroblastoma patients. We investigated the prognostic relevance of ALK mRNA expression and the relationship with ALK immunohistochemical expression, histological subtype and ALK aberrations. Whole transcriptome sequencing data were available from 54 patients. Overall survival (OS) and event-free survival (EFS) were estimated with Kaplan–Meier’s methodology. ALK protein expression was analyzed by immunohistochemistry. ALK aberrations were detected using whole exome sequencing, single nucleotide polymorphism array, next generation sequencing and/or fluorescence in situ hybridization. OS was 74.8% and EFS was 60%. ALK mRNA expression was not associated with OS (HR 1.127, 95% CI (0.812–1.854), p = 0.331) and adjusted EFS (HR 1.134, 95% CI (0.783–1.644), p = 0.505), but was associated with histological subtype (OR 1.914, 95% CI (1.083–3.382), p = 0.025) and ALK protein expression (negative versus weak: OR 2.829, 95% CI (1.290–6.204), p = 0.009) (negative versus moderate/strong: OR 2.934, 95% CI (0.889–9.679), p = 0.077). ALK mutated tumors had significantly higher ALK mRNA expression than non-mutated tumors (p < 0.001). MYCN-amplified neuroblastomas have higher MYCN mRNA expression (p ≤ 0.001), but not ALK mRNA expression (p = 0.553). ALK mRNA expression is higher in ALK mutated neuroblastomas and is associated with poorer differentiation degree and higher protein expression. ALK mRNA expression is not significantly associated with OS and EFS.
Time-Series Explanatory Fault Prediction Framework for Marine Main Engine Using Explainable Artificial Intelligence
Authors: Je-Gal Hong , Park Young-Seo , Park Seong-Ho , Kim Ji-Uk , Yang Jung-Hee , Kim Sewon , Lee Hyun-Suk
Published: August 2024

As engine monitoring data has become more complex with an increasing number of sensors, fault prediction based on artificial intelligence (AI) has emerged. Existing fault prediction models using AI significantly improve the accuracy of predictions by effectively handling such complex data, but at the same time, the problem arises that the AI-based models cannot explain the rationale of their predictions to users. To address this issue, we propose a time-series explanatory fault prediction framework to provide an explainability even when using AI-based fault prediction models. It consists of a data feature reduction process, a fault prediction model training process using long short-term memory, and an interpretation process of the fault prediction model via an explainable AI method. In particular, the proposed framework can explain a fault prediction based on time-series data. Therefore, it indicates which part of the data was significant for the fault prediction not only in terms of sensor type but also in terms of time. Through extensive experiments, we evaluate the proposed framework using various fault data by comparing the prediction performance of fault prediction and by assessing how well the main pre-symptoms of the fault are extracted when predicting a fault.
Observation and Modeling of Nonlinear Internal Waves on the Sea of Japan Shelf
Authors: Yaroshchuk Igor , Liapidevskii Valery , Kosheleva Alexandra , Dolgikh Grigory , Pivovarov Alexander , Samchenko Aleksandr , Shvyrev Alex , Gulin Oleg , Korotchenko Roman , Khrapchenkov Fedor
Published: August 2024

This paper presents a discussion on observations of nonlinear internal waves (NLIWs) in the coastal zone of the Sea of Japan, based on the mooring of thermostring clusters in different seasons of 2022. For statistical evaluation of the frequency of event occurrence and determination of NLIW movement direction, we use our observations of the past 12 years. We present the NLIW structures, observed in spring, summer, and autumn of 2022, which are typical for this shelf area. Two types of nonlinear waves are described—solitary and undular bores, with or without strong vertical mixing behind the front. We demonstrate spatial transformation of an undular bore as it moves over the shelf. A mathematical model based on the second-order shallow water approximation is proposed for numerical simulation. To simplify calculations, the authors limit themselves to two- and three-layer shallow water models. We investigate the possibility of spatiotemporal reconstruction of internal nonlinear structures between thermostrings using experimental data and proposed models. The authors show that at distances of up to several kilometers between thermostrings, the wave fields of strongly nonlinear and nonstationary structures can be successfully reconstructed. Water flow induced by NLIWs can be reconstructed from the data of even one thermostring.
Serine Rejuvenated Degenerated Volvariella volvacea by Enhancing ROS Scavenging Ability and Mitochondrial Function
Authors: Wang Qiaoli , Zhu Jianing , Wang Yonghui , Yun Jianmin , Zhang Yubin , Zhao Fengyun
Published: August 2024

Serine is a functional amino acid that effectively regulates the physiological functions of an organism. This study investigates the effects of adding exogenous serine to a culture medium to explore a feasible method for the rejuvenation of V. volvacea degenerated strains. The tissue isolation subcultured strains T6, T12, and T19 of V. volvacea were used as test strains, and the commercially cultivated strain V844 (T0) was used as a control. The results revealed that the addition of serine had no significant effect on non-degenerated strains T0 and T6, but could effectively restore the production characteristics of degenerated strains T12 and T19. Serine increased the biological efficiency of T12 and even helped the severely degenerated T19 to regrow its fruiting body. Moreover, exogenous serine up-regulated the expression of some antioxidant enzyme genes, improved antioxidase activity, reduced the accumulation of reactive oxygen species (ROS), lowered malondialdehyde (MDA) content, and restored mitochondrial membrane potential (MMP) and mitochondrial morphology. Meanwhile, serine treatment increased lignocellulase and mycelial energy levels. These findings form a theoretical basis and technical support for the rejuvenation of V. volvacea degenerated strains and other edible fungi.
Math Calculation and Financial Literacy: The Incidence of Geometric Progressions in the Calculation of Financial Interest
Authors: Moreno-García Elena
Published: August 2024

Calculations about compound interest serve as the basis of most financial decisions; therefore, it is imperative to explore what mathematical knowledge people need to correctly calculate simple and compound interest. The aim of this study is to analyze the relationship between college students’ competence in calculating simple and compound interest and their understanding of the arithmetic and geometric progressions. It is also pointed out whether the results vary according to gender. Population proportion tests are carried out, and gender proportion differences are considered for inferential analysis. The dichotomous Probit model was used for correlation analysis. Results demonstrate that 59.8% of students know how to formulate a whole-number succession, and only 30.9% in the case of fractional numbers. Less than 50% of students can calculate compound interest, but 76.7% can calculate simple interest. There is no significant difference between men and women. The results show a positive relationship between male students’ competence in calculating compound interest with the possibility to correctly formulate a geometric succession. Findings can be useful for mathematics teaching strategy design and its applications in finance contexts with the purpose of training students to be better at finance decision making.
Loan Pricing in Peer-to-Peer Lending
Authors: Maloney David D. , Hong Sung-Chul , Nag Barin
Published: August 2024

Lenders writing loans in the peer-to-peer market carry risk with the anticipation of an expected return. In the current implementation, many lenders do not have an exit strategy beyond holding the loan for the full repayment term. Many would-be lenders are deterred by the risk of being stuck with an illiquid investment without a method for adjusting to overall economic conditions. This risk is a limiting factor for the overall number of loan transactions. This risk prevents funding for many applicants in need, while simultaneously steering capital towards other more liquid and mature markets. The underdeveloped valuation methods used presently in the peer-to-peer lending space present an opportunity for establishing a model for assigning value to loans. We provide a novel application of an established model for pricing peer-to-peer loans based on multiple factors common in all loans. The method can be used to give a value to a peer-to-peer loan which enables transactions. These transactions can potentially encourage participation and overall maturity in the secondary peer-to-peer loan trading market. We apply established valuation algorithms to peer-to-peer loans to provide a method for lenders to employ, enabling note trading in the secondary market.
The Guidance of Public Value in China’s Historic Environment: Research on Regeneration Strategies Using Taiyuan’s Bell Tower Street as an Example
Authors: Zhang Ruijie , Martí Casanovas Miquel , González Montserrat Bosch , Zhang Zhihui , Li Haoran
Published: August 2024

When profit-driven renewal is difficult to implement, many historic districts in China become “frozen” under protection. In the recent social context of “building cities for the people”, public value-oriented renewal of urban historic areas has become crucial in city transformation. This study investigates strategies for historic district regeneration in China by integrating spatial form, urban governance, and public value. We propose a novel framework to analyze the regeneration of historic districts, using Taiyuan’s Bell Tower Street as a case study. The framework distinguishes between two dimensions: spatial and economic–social. In the spatial dimension, we focus on the transformation of spatial form to regenerate public value, emphasizing the attribute of “publicness” as central to urban regeneration efforts. This involves a tiered approach to excavating and upgrading historic districts at macro, meso, and micro levels. The economic–social dimension explores urban governance to enhance public value through collaboration between government, market, and societal actors. This study employs a mixed-methods approach, including document reviews, interviews, field observations, and statistical data analysis. The analysis highlights that a public value-oriented approach to heritage regeneration can balance historical preservation with contemporary urban needs, offering a sustainable model for other cities.
Exploration of High-Nutritional-Quality Vegetable Oil Blend with Enhanced Oxidative Stability as a Frying Medium Substitute for Palm Oil
Authors: Athanasiadis Vassilis , Chatzimitakos Theodoros , Kalompatsios Dimitrios , Bozinou Eleni , Lalas Stavros I.
Published: August 2024

Blending is a commonly utilized technique for enhancing the oxidative stability, nutritional quality, and physicochemical properties of vegetable oils. This study explored the potential of a vegetable oil blend consisting of common seed oils (sunflower, soybean, rapeseed, cottonseed, and corn oils), through partial least squares analysis, as a substitute for palm oil in the food preparation sector. Oxidative stability assays were conducted initially and after 14 and 28 days of incubation at 60 °C. These assays included radical inhibition activities between the optimal blended oil and palm oil through DPPH• inhibition activity and thermal stability via accelerated oxidation conditions with Rancimat (110 °C, 15 L/h) and conjugated diene and triene formation. The impact of each oil was assessed through correlation analyses and Pareto plots. The optimal blended oil consisted of soybean/sunflower/cottonseed/corn oils at a ratio of 2:1:4:4. It had an induction period (i.e., full rancidity) vastly enhanced to 5.38 h but was statistically significantly lower than the stable palm oil by ~50%. Prior to thermal incubation, the blended oil was more potent in inhibiting DPPH•, as it recorded 139.83 μmol of Trolox equivalents per kg of oil, ~53% more than palm oil. The conjugated diene and triene concentrations were similar for both oils at ~15 and ~7 mmol/kg oil, respectively. The Fourier-Transform Infrared spectra revealed the prevalence of cis fatty acids in the optimal oil blend and trans fatty acids in palm oil, indicating an enhancement in the nutritional quality of the vegetable oil blend. The results of the study could provide a nutritional oil blend that could be used as a substitute for palm oil in the food industry.
Useful Predictor for Exacerbation of Esophagogastric Varices after Hepatitis C Virus Eradication by Direct-Acting Antivirals
Authors: Nagaoki Yuko , Yamaoka Kenji , Fujii Yasutoshi , Uchikawa Shinsuke , Fujino Hatsue , Ono Atsushi , Murakami Eisuke , Kawaoka Tomokazu , Miki Daiki , Aikata Hiroshi , Hayes C. Nelson , Tsuge Masataka , Oka Shiro
Published: August 2024

To clarify the risk factors for the aggravation of esophagogastric varices (EGVs) after hepatitis C virus (HCV) eradication with direct-acting antiviral (DAA) therapy, we enrolled 167 consecutive patients with HCV-related compensated cirrhosis who achieved a sustained virological response (SVR) after DAA therapy. During a median of 69 months, EGVs were aggravated in 42 (25%) patients despite SVR. The cumulative 1-, 3-, 5-, and 10-year aggravated EGV rates were 7%, 23%, 25%, and 27%, respectively. Multivariate analysis identified a platelet count < 11.0 × 104/μL, LSM ≥ 18.0 kPa, total bile acid ≥ 33.0 μmol/L, and a diameter of left gastric vein (LGV) ≥ 5.0 mm at HCV eradication as independent risk factors for EGV aggravation post-SVR. In groups that met all of these risks, the cumulative EGV aggravation rates at 1, 3, and 5 years were 27%, 87%, and 91%, respectively. However, none of the patients who had only one or none of the risk factors experienced EGV aggravation. Platelet count, LSM, total bile acid, and diameter of LGV at HCV eradication were associated with aggravated EGV post-SVR. EGVs tend to worsen as two or more of these risk factors increase.
A Study on the Pre-Hardened Shrinkage Reduction of Grout Using Carbon Materials
Authors: Lee Jeong-Bae , Kim Seong-Soo , Lee Young-Jun , Jang In-Soo , Kim Ju-Youn
Published: August 2024

In this study, the characteristics of grout mixed with charcoal as an expansive agent were examined to reduce the pre-hardening shrinkage of cementitious materials. This study compared and reviewed the application of CSA, a conventional expansive agent, to grout. The setting time, fluidity, compressive strength, and pre-hardening shrinkage/expansion were evaluated to explore the usability of charcoal as an expansive agent. The test results confirmed that, as the incorporation rate of charcoal increased, the pre-hardening expansion rate of the grout also increased, making it more effective for pre-hardening expansion than the conventional expansive agent CSA. However, when charcoal was used as an expansive agent, the compressive strength decreased after hardening, indicating the need for caution regarding the amount of charcoal used. Furthermore, the pre-hardening shrinkage and expansion rates of the various types of charcoal used in this study showed some differences, suggesting the need for further research on the internal pore volume and pore size of the charcoal.
Direct Ink Writing of SiCN/RuO2/TiB2 Composite Ceramic Ink for High-Temperature Thin-Film Sensors
Authors: Wang Yusen , Xu Lida , Zhou Xiong , Zhao Fuxin , Liu Jun , Wang Siqi , Sun Daoheng , Chen Qinnan
Published: August 2024

Direct ink writing (DIW) of high-temperature thin-film sensors holds significant potential for monitoring extreme environments. However, existing high-temperature inks face a trade-off between cost and performance. This study proposes a SiCN/RuO2/TiB2 composite ceramic ink. The added TiB2, after annealing in a high-temperature atmospheric environment, forms B2O3 glass, which synergizes with the SiO2 glass phase formed from the SiCN precursor to effectively encapsulate RuO2 particles. This enhances the film’s density and adhesion to the substrate, preventing RuO2 volatilization at high temperatures. Additionally, the high conductivity of TiB2 improves the film’s overall conductivity. Test results indicate that the SiCN/RuO2/TiB2 film exhibits high linearity from room temperature to 900 °C, high stability (resistance drift rate of 0.1%/h at 800 °C), and high conductivity (4410 S/m). As a proof of concept, temperature sensors and a heat flux sensor were successfully fabricated on a metallic hemispherical surface. Performance tests in extreme environments using high-power lasers and flame guns verified that the conformal thin-film sensor can accurately measure spherical temperature and heat flux, with a heat flux sensor response time of 53 ms. In conclusion, the SiCN/RuO2/TiB2 composite ceramic ink developed in this study offers a high-performance and cost-effective solution for high-temperature conformal thin-film sensors in extreme environments.
Learning Optimal Dynamic Treatment Regime from Observational Clinical Data through Reinforcement Learning
Authors: Abebe Seyum , Poli Irene , Jones Roger D. , Slanzi Debora
Published: August 2024

In medicine, dynamic treatment regimes (DTRs) have emerged to guide personalized treatment decisions for patients, accounting for their unique characteristics. However, existing methods for determining optimal DTRs face limitations, often due to reliance on linear models unsuitable for complex disease analysis and a focus on outcome prediction over treatment effect estimation. To overcome these challenges, decision tree-based reinforcement learning approaches have been proposed. Our study aims to evaluate the performance and feasibility of such algorithms: tree-based reinforcement learning (T-RL), DTR-Causal Tree (DTR-CT), DTR-Causal Forest (DTR-CF), stochastic tree-based reinforcement learning (SL-RL), and Q-learning with Random Forest. Using real-world clinical data, we conducted experiments to compare algorithm performances. Evaluation metrics included the proportion of correctly assigned patients to recommended treatments and the empirical mean with standard deviation of expected counterfactual outcomes based on estimated optimal treatment strategies. This research not only highlights the potential of decision tree-based reinforcement learning for dynamic treatment regimes but also contributes to advancing personalized medicine by offering nuanced and effective treatment recommendations.
A Discrete Resistance Network Based on a Multiresolution Grid for 3D Ground-Return Current Forward Modeling
Authors: Duan Lijun , Feng Xiao , Li Ruiheng , Li Tianyang , Di Yi , Hao Tian
Published: August 2024

While the high-voltage direct current (HVDC) transmission system is in monopolar operation, it produces thousands of amperes of ground-return currents (GRCs). Accurate computation of the GRCs is essential for assessing safety implications for nearby industrial infrastructure. Current three-dimensional forward models of GRCs are typically constructed based on discrete differential equations, and their solving efficiency is constrained by the increased degrees of freedom resulting from the fine discretization grids in high-conductivity conductors and ground points. To address this issue, we present a new resistor network (RN) forward solver based on a multi-resolution grid approach. This solver utilizes an RN to avoid the massive degrees of freedom resulting from fine discretization of high-voltage conductors and enhances grid discretization efficiency near the surface grounding system through multi-resolution grids. We demonstrate, through multiple three-dimensional geoelectrical model cases, that the proposed method reduces the forward modeling misfit to 1% and possesses only 3‰ of the required discrete elements compared to traditional approaches. Furthermore, practical HVDC grid model analyses indicate the successful application of the proposed method for GRC analysis in complex geoelectric conditions.
A New State Assessment Method for Hydrodynamic Journal Bearings under Different Assembly Characteristics
Authors: Lu Hong , Dai Jiashun , Liu Qi , Mei Jiangnuo , He Jiji
Published: August 2024

As the transmission component in mechanical systems, hydrodynamic journal bearing is widely used in large electromechanical equipment. The instability of the hydrodynamic journal bearing often results in mechanical wear and damage, which may cause maintenance shutdowns and significant financial losses. Accordingly, assessing the hydrodynamic journal bearing online is a highly effective approach to guaranteeing reliability. To analyze oil film thickness distribution under various assembly characteristics, this paper proposes a Fluid–Solid coupling analysis method based on hydrodynamic lubrication theory and Hertzian elastic deformation theory. The novelty is that the difference between the oil film thicknesses at the same measuring angle within the two opposing faces of the bearing shell is taken as the assessment parameter, which can directly indicate the deviation degree of the stator axis. Comparison of simulation and experimental results validated that the proposed method exhibits exceptional accuracy in practical applications.
Inverse Problem for the Nonlinear Convection–Diffusion Equation by Using the Multigrid Method and Constraint Data
Authors: Wang Shuai , Ling Shiyi , Chao Heyang , Qi Yunfei , Zhang Wenwen , Ma Qiang , Liu Tao
Published: August 2024

In the article, we propose a combination method based on the multigrid method and constraint data to solve the inverse problem in the context of the nonlinear convection–diffusion equation in the multiphase porous media flow. The inverse problem consists of a data-fitting term involving the discretization of a direct problem, a constraint term concerning the incorporation of constraint data, and a regularization term dealing with the improvement of stability. A multigrid method, which is specialized for large-scale problems and works by keeping the consistence of objective functionals between different grids, is applied in the process of inversion. Based on the numerical results, the proposed combination method has the advantages of fast calculation, high precision, good stability, and strong anti-noise ability in computation. It obtains good performance under various noise levels, as well as outperforming any one method used alone.
Biochemical Markers in the Prediction of Pregnancy Outcome in Gestational Diabetes Mellitus
Authors: Mandić-Marković Vesna , Dobrijević Zorana , Robajac Dragana , Miljuš Goran , Šunderić Miloš , Penezić Ana , Nedić Olgica , Ardalić Danijela , Miković Željko , Radojičić Ognjen , Mandić Milica , Mitrović Jelena
Published: August 2024

Background and Objectives: Gestational diabetes mellitus (GDM) may impact both maternal and fetal/neonatal health. The identification of prognostic indicators for GDM may improve risk assessment and selection of patient for intensive monitoring. The aim of this study was to find potential predictors of adverse pregnancy outcome in GDM and normoglycemic patients by comparing the levels of different biochemical parameters and the values of blood cell count (BCC) between GDM and normoglycemic patients and between patients with adverse and good outcome. Materials and Methods: Prospective clinical study included 49 patients with GDM (study group) and 44 healthy pregnant women (control group) who underwent oral glucose tolerance test (OGTT) at gestational age of 24–28 weeks. At the time of OGTT peripheral blood was taken for the determination of glucose levels, insulin, glycated hemoglobin, lipid status, homeostatic model assessment, BCC, iron and zinc metabolism, liver function, kidney function and inflammatory status. Each group was divided into two subgroups—normal and poor pregnancy outcome. Results: Higher RBC, hemoglobin concentration, hematocrit value, fasting glucose, uric acid and fibrinogen were found in GDM patients compared to control group. In GDM patients with poor pregnancy outcome values of fibrinogen, ALT, sedimentation rate, granulocyte and total leukocyte counts were elevated, while the serum level of zinc was significantly lower. Higher level of fibrinogen was found in normoglycemic patients with adverse pregnancy outcomes. ROC curve was constructed in order to assess fibrinogen’s biomarker potential. The established AUC value for diagnostic ROC was 0.816 (p < 0.001, 95% CI 0.691–0.941), while the AUC value for assessing fibrinogen’s potential to predict poor pregnancy outcome in GDM was 0.751 (p = 0.0096, 95% CI 0.561–0.941). Conclusions: The results of our study demonstrated that the best prognostic potential in GDM showed inflammation related parameters, identifying fibrinogen as a parameter with both diagnostic and prognostic ability.
Coronary Artery Disease in Patients on Dialysis: Impact of Traditional Risk Factors
Authors: Nakić Dario , Grbić Pavlović Petra , Vojković Marina , Stipćević Mira , Patrk Jogen , Bištirlić Marin , Bakotić Zoran , Vučak Lončar Jelena , Gusar Ivana
Published: August 2024

Background and Objectives: End-stage kidney disease (ESKD) is a major risk factor for cardiovascular morbidity and mortality. This study aims to evaluate the contribution of traditional risk factors to the development of coronary artery disease (CAD) in patients on dialysis. Materials and Methods: In this study, 54 patients on dialysis with angina symptoms or a positive exercise stress test underwent coronary angiography. Lesions with obstruction >70% lumen diameter of the coronary artery were considered significant. Traditional risk factors included hypertension, diabetes, smoking, dyslipidemia, age, gender, and time spent on dialysis. Results: Out of 54 participants, 41 (75.92%) were men and 13 (24.07%) women. CAD was present in 34 (62.96%) patients, and 20 (37.03%) patients were without CAD. The average age of the participants was 66.51 years. In the group with CAD, the average age was 69.52 years with an average time spent on dialysis of 2.73 years. In the group without CAD, the average age was 61.40 years with a time spent on dialysis of 2.35 years. Hypertension was present in 92.59% of all participants and 97.05% of those with CAD. Diabetes was present in 41.17 patients with CAD and 40% of those without CAD. Dyslipidemia was present in 76.47 participants with CAD and in 40% of those without CAD. Smoking was noticed in 35.29% of the participants with CAD and 57.14% of those without CAD. Besides hypertension, significant predictors for the development of CAD in patients on dialysis were dyslipidemia (OR 3.698, Cl 1.005–13.608, p = 0.049) and age (OR 1.056, Cl 1.004–1.110, p = 0.033). Conclusions: Among the traditional risk factors, hypertension, dyslipidemia, and age are the predictors for the development of CAD in patients on dialysis. Further large randomized clinical studies are needed to clarify the role of traditional risk factors for CAD in patients with ESKD.
The Relationship between Psychological Stress and Anthropometric, Biological Outcomes: A Systematic Review
Authors: Rog Joanna , Nowak Katarzyna , Wingralek Zuzanna
Published: August 2024

Background and Objectives: Challenges and threats to global security and the growing demands of today’s society lead to significantly increased exposure to stress. Stress can negatively affect numerous physiological processes, including metabolic changes. An unhealthy lifestyle might intensify this disruption. The aim of the systematic review was to establish the effect of psychological stress on metabolic and anthropometric factors in healthy individuals. Materials and Methods: The study was conducted according to the PRISMA guidelines; and the risk of bias (ROB) assessment was based on the Newcastle–Ottawa Scale (NOS). A literature search of the MEDLINE/PubMed database was conducted using specific search terms. Results: We identified 32 articles meeting the inclusion criteria for the review with the different experimental designs and aims. Most of the papers were at high ROB. The included studies were conducted in groups of adults and children/teenagers. The most-often-applied tool to measure stress severity was the Perceived Stress Scale (PSS). Twenty-two studies analyzed the connection between stress and body composition, and bioimpedance analysis (BIA) was the most often used method. For biological parameters, the most frequently analyzed was cortisol (n = 9). The other examined factors included glucose, insulin, parameters related to food intake regulation, carbohydrates, lipid metabolism, inflammation, and oxidative stress. The included studies were incompliance in relation to the assessment method and type of assessed biological fluids. Conclusions: The vast majority of studies do not support the effect of chronic distress on anthropometric measurements and biological markers levels. However, many of them suggest adverse, synergistic effects of unhealthy lifestyle patterns and the stress on the examined variables. Further experiments should implement a similar and repeatable methodology.
Predicting Delayed Postoperative Length of Stay Following Robotic Kidney Transplantation: Development and Simulation of Perioperative Risk Factors
Authors: Lee Sang-Wook , Kim Kyoung-Sun , Kim Sung-Hoon , Sim Ji-Yeon
Published: August 2024

Background and Objective: Early discharge following robot-assisted kidney transplantation (RAKT) is a cost-effective strategy for reducing healthcare expenses while maintaining favorable short- and long-term prognoses. This study aims to identify predictors of postoperative delayed discharge in RAKT patients and develop a predictive model to enhance clinical outcomes. Materials and Methods: This retrospective study included 146 patients aged 18 years and older who underwent RAKT at a single tertiary medical center from August 2020 to January 2024. Data were collected on demographics, comorbidities, social and medical histories, preoperative labs, surgical information, intraoperative data, and postoperative outcomes. The primary outcome was delayed postoperative discharge (length of hospital stay > 7 days). Risk factors for delayed discharge were identified through univariate and multivariate regression analyses, leading to the development of a risk scoring system, the effectiveness of which was evaluated through receiver operating characteristic curve analysis. Results: 110 patients (74.8%) were discharged within 7 days post-transplant, while 36 (24.7%) remained hospitalized for 8 days or longer. Univariate and multivariate logistic regression analyses identified ABO incompatibility, BUN levels, anesthesia time, and vasodilator use as risk factors for delayed discharge. The RAKT score, incorporating these factors, demonstrated a predictive performance with a C-statistic of 0.789. Conclusions: This study identified risk factors for delayed discharge after RAKT and developed a promising risk scoring system for real-world clinical application, potentially improving postoperative outcome stratification in RAKT recipients.
Occupational Safety from an Individual Perspective: The Influence of Extraversion on Compliance with Safety Standards for Emergency Employees and Nurses
Authors: Albalá-Genol Jazael , Díaz-Fúnez Pedro A. , Martín-Martín Francisco G. , Mañas-Rodríguez Miguel A.
Published: August 2024

When analyzing occupational safety factors, a human factor is associated with 80–90% of incidents and accidents that occur. Controlling this factor is essential when it comes to creating healthy and safe organizations. Personality traits have shown great relevance when understanding the behavior of safety or self-protection in the workplace, affecting the motivation of subjects and, therefore, their behavior. The objective of this study is to analyze the influence of the extraversion trait on compliance with safety rules and behaviors, while evaluating the mediating effect of motivation for safety in health professionals. The sample is composed of 183 nurses and wardens of a hospital in Spain. The obtained results confirm the hypotheses raised, validating the negative influences of extraversion on motivation for security and compliance with norms, behaviors, and security, while verifying the effect of the total mediation of motivation for security in the influence of extraversion on security compliance. This confirms the effect of this personality trait on employees’ safety behaviors, and the possibility of reducing this influence by controlling personal motivations with interventions from the organization.