bluuebunny/crossref_metadata_2025_split huggingface dataset:
Technical and economic assessment of bio-syngas production from biomass and its application in natural gas pipelines
Authors: Zhang Zhihai , Rezazgui Olivier , Delcroix Benoit , Mangin Patrice 
Published: July 2023

Abstract
Biomass frequently constrains its widespread application due to its low economic efficiency. In this project, a new approach of biomass application was explored to reduce bio-syngas production cost. A model for the bio-syngas production from biomass gasification and bio-syngas purification (Selexol and water scrubbing) were studied. Based on the simulation results, we assessed the feasibility and viability of the project. Preliminary results showed that the bio-syngas production cost with Selexol (2.15 $/Nm3) is even higher than biomass used in power generation systems (equal to 1.58–2.21 $/Nm3). However, water scrubber was used as bio-syngas purification, the capital investment cost and bio-syngas production cost (1.34 $/Nm3) was significantly reduced. A sensitivity analysis was conducted on the bio-syngas price, which could be further reduced by various factors: biomass price, carbon taxes, and carbon credits. We assumed that bio-syngas was applied to natural gas pipeline, our analysis showed that the application of bio-syngas (2–10% content) to natural gas had little impact on natural gas properties: combustion value and price. The technology of water scrubber makes the applications of biomass-based fuels competitive.
Identification of potential blood biomarkers of coronary artery disease using a cuproptosis gene set
Authors: Li Jia , Xiang Bitao , Chen Yubin , Yin Yue , Fang Cheng , Lei Kaibo , Zhu Zhanwei , Tang Can-E , Luo Fanyan 
Published: July 2023

Abstract

Background
Coronary artery disease (CAD) is a multifactorial cardiovascular disease that causes high mortality worldwide. Cuproptosis is a newly discovered method of programmed cell death, but it is unclear whether it is involved in the development of CAD.
Methods
GSE180081 was downloaded from the GEO database and genes that were differentially expressed in controls and patients with CAD were identified. These were clustered according to the cuproptosis gene set, to identify differentially expressed cuproptosis related genes. The intersection of the two sets of differentially expressed genes was used to identify genes relevant to the diagnosis of CAD using LASSO regression. A diagnostic model was created using the selected genes and logistic regression. Enriched immune genes were identified, the associated ceRNA network was characterized, and drugs that may target the identified genes were searched for.
Results
We identified 818 differentially expressed genes that were common to the CAD and cuproptosis gene sets, which principally represented the cell-substrate junction and the positive regulation of leukemia. Furthermore, HIST1H4E, IL6ST, RN7SKP45, LST1, and SNORD50B were found be potentially useful for the diagnosis of CAD using the diagnostic model. These genes were found to be closely associated with immune modification.
Conclusion
We have constructed a diagnostic prediction model based on a cuproptosis gene set using whole-blood transcriptome data. Using this, we have identified HIST1H4E, IL6ST, and LST1 as potential biomarkers of the risk of CAD. These findings provide a novel approach to the prediction, prevention, and individualized treatment of CAD.
Upgrading the performance of InP/Si based multi junction thin solar cell through Opto-electronics modeling and simulation
Authors: ROY ARIJIT BARDHAN , AKBAR SHAIK 
Published: July 2023

Abstract
Indium Phosphide (InP) and Silicon(Si) based multi junction thin solar cell is one of the most competent devices in PV community which have the potential to fulfill the energy demand of present era with minimum material consumption. Through this study we try to develop different types of designs and evaluate the efficiency of InP/Si based multi-junction solar cells through various opto-electronics simulation studies. During this investigation we achieved more than 18% efficiency of solar cell using optimized doping profile of both materials with 12 µm substrate thickness. Further the electrical model was validated by different optical studies and found its competency in that domain also.
The mediating role of coping style between nurses’ workplace bullying and professional quality of life
Authors: Jiao Rui , Li Jinping , Cheng Nan , Liu Xiangying , Tan Yizhou 
Published: July 2023

Abstract
Aims
This study aimed to explore the relationship between workplace bullying among nurses and their professional quality of life, as well as the mediating role of coping styles between the two factors.
Background
In China, the overall status of nurses' professional quality of life is not optimistic, and the problems of low compassion satisfaction and high empathy fatigue persist. Workplace bullying, which is a serious worldwide problem, can hurt the mental health and professional quality of nurses. However, it has still not attracted enough attention from managers.
Methods
The study used a cross-sectional research design and surveyed 297 clinical nurses from two tertiary grade A hospitals in Wuhan, China. Data were collected through an online questionnaire survey from March to May 2022. The data were analyzed using descriptive statistical methods, including Pearson correlation analysis and structural equation modeling.
Results
The score for nurses' workplace bullying was 38.72 ± 12.30. The scores for the three dimensions of professional quality of life were 27.56 ± 4.79 for compassion satisfaction, 30.51 ± 4.33 for burnout, and 28.47 ± 4.65 for secondary trauma stress. The scores for positive coping style and negative coping style were 34.59 ± 5.72 and 20.34 ± 5.08 points, respectively. Workplace bullying has negative and direct effects on compassion satisfaction, and positive and direct effects on burnout and secondary traumatic stress. Coping styles mediate the relationship between workplace bullying and compassion satisfaction, burnout, and secondary traumatic stress.
Conclusion
Workplace bullying hurts nurses' professional quality of life, while coping style plays an intermediary role between workplace bullying and professional quality of life. Nursing managers can improve nurses' professional quality of life by reducing workplace bullying and enhancing positive responses.
Implications for nursing management:
Nursing managers need to apply management wisdom and methods to promote nurses maintaining a positive work state, and to reduce the existence and harm of workplace bullying, in order to improve the professional quality of life for nurses.
Phenotypic Correlates of Structural and Functional Protein Impairments Resultant from ALDH5A1 Variants
Authors: Latzer Itay Tokatly , Roullet Jean-Baptiste , Cesaro Samuele , DiBacco Melissa L. , Arning Erland , Rotenberg Alexander , Lee Henry H C , Opladen Thomas , Jeltsch Kathrin , García-Cazorla Àngels , Juliá-Palacios Natalia , Gibson K. Michael , Bertoldi Mariarita , Pearl Phillip L. 
Published: July 2023

Abstract
Objective
To investigate the genotype-to-protein-to-phenotype correlations of succinic semialdehyde dehydrogenase deficiency (SSADHD), an inherited metabolic disorder of γ-aminobutyric acid catabolism.
Methods
Bioinformatics and in silico mutagenesis analyses of ALDH5A1 variants were performed to evaluate their impact on protein stability, active site and co-factor binding domains, splicing, and homotetramer formation. Protein abnormalities were then correlated with a validated disease-specific clinical severity score and neurological, neuropsychological, biochemical, neuroimaging, and neurophysiological metrics.
Results
A total of 58 individuals (1:1 male/female ratio) were affected by 32 ALDH5A1 pathogenic variants, eight of which were novel. Compared to individuals with single homotetrameric or multiple homo and heterotetrameric proteins, those predicted not to synthesize any functional enzyme protein had significantly lower expression of ALDH5A1 (p = 0.001), worse overall clinical outcomes (p = 0.008) and specifically more severe cognitive deficits (p = 0.01), epilepsy (p = 0.04) and psychiatric morbidity (p = 0.04). Compared to individuals with predictions of having no protein or a protein impaired in catalytic functions, subjects whose proteins were predicted to be impaired in stability, folding, or oligomerization had a better overall clinical outcome (p = 0.02) and adaptive skills (p = 0.04).
Conclusions
The quantity and type of enzyme proteins (no protein, single homotetramers, or multiple homo and heterotetramers), as well as their structural and functional impairments (catalytic or stability, folding, or oligomerization), contribute to phenotype severity in SSADHD. These findings are valuable for assessment of disease prognosis and management, including patient selection for gene replacement therapy. Furthermore, they provide a roadmap to determine genotype-to-protein-to-phenotype relationships in other autosomal recessive disorders.
Analysis of characteristic prediction of aluminized boron steel after the hot stamping process using an image color-based neural network
Authors: Yoon Seung Chae , Kong Je Youl , Park Jea Myoung , Park Kye Jeong , Hyun Joo Sik 
Published: July 2023

Abstract
Hot stamping is an innovative technology that enables the production of high-strength automotive body parts by heating the material to a high temperature and simultaneously forming and quenching it in-die. The process results in parts with excellent strength-to-weight ratios, which are essential for the automotive industry. The widely used 22MnB5 material is heated to temperatures above 900°C, and an Al-Si coating is applied to prevent the formation of oxide scale on the sheet surface. The distinctive color on the sheet surface after hot stamping is produced by the Al-Si coating. This phenomenon is attributed to the formation of Al2O3 on the surface of the Al-Si coating layer and the diffusion of Fe from the substrate into the Al-Si coating layer, both of which are significantly influenced by the heating time and temperature. In this study, the neural network was investigated to predict the hot stamping heating temperature and time conditions based on the color exhibited on the sheet surface after the process. Additionally, the neural network was combined with numerical models to predict the inter-diffusion layer thickness in the Al-Si coating layer, which affects the weldability of the vehicle part, and the amount of hydrogen uptake that directly influences hydrogen embrittlement.
Optimising the Mechanical Properties of Additive-Manufactured Recycled Polylactic Acid (rPLA) using Single and Multi-Response Analyses Methods.
Authors: Gebrehiwot Silas , Gebrehiwot Author Silas Z. , Espinosa-Leal Leonardo , Linderbäck Paula , Remes Heikki 
Published: July 2023

Abstract

Taguchi’s design of experiment (DoE) and the grey relational analysis are used to optimise fused deposition modelling (FDM) parameters for the tensile strength and Modulus of toughness (MoT) responses of a recycled Polylactic acid (Reform-rPLA) polymer. The influences of the infill geometry, infill density, infill orientation, nozzle temperature and infill speed on the mechanical properties of the material are studied using the \({L}_{18}\) orthogonal array which is based the \({2}^{1}\times {4}^{3}\) factor levels with 3 experimental repetitions. The output responses are first studied individually and combined as a multi-response optimisation using the grey relational analysis method. The analysis of variance (ANOVA) showed that the infill orientation parameter highly influences both the single and multi-response optimisations. In the strength optimisation, the infill orientation and infill density are statistically significant with P-values \(\alpha\) less than the 0.05 criterion. Similarly, the ANOVA for the (MoT) showed that infill orientation and infill geometry parameters are statistically significant. The infill orientation is statistically significant for the multi-response optimisation, followed by the infill density with \({\alpha }=0.08\). On the other hand, the response predictions indicated that the zigzag infill geometry, \(45\%\) infill density, \(90^\circ\) infill geometry and \(205℃\) nozzle temperature led to optimum tensile strength and MoT properties. Our confirmation tests are in good agreement with optimum response predictions. Based on rankings of the mean responses, the first three factors were used to develop linear regression models for the tensile strength and MoT of the material. The predictive models showed average errors of \(7.91\%\) for the tensile strength and \(8.6\%\) for the MoT.
2D phase contrast MRI reveals changes in uterine arterial blood flow in pregnant women administrated tadalafil for fetal growth restriction
Authors: Nii Masafumi , Enomoto Naosuke , Ishida Masaki , Magawa Shoichi , Takakura Sho , Maki Shintaro , Tanaka Kayo , Toriyabe Kuniaki , Tanaka Hiroaki , Kondo Eiji , Sakuma Hajime , Ikeda Tomoaki 
Published: July 2023

Abstract
We aimed to examine the effect of uterine arterial (UtA) blood flow changes after tadalafil treatment for fetal growth restriction (FGR) using two-dimensional (2D) phase-contrast magnetic resonance imaging (PC-MRI). We recruited 14 pregnant women with FGR who were aged 20–44 years, at ≥ 20 weeks’ gestation, between May 2019 and July 2020. They underwent 2D PC-MRI for UtA blood flow measurement 3 days (interquartile range: 2–4) after diagnosis. This group (FGR group) was compared with 14 gestational age (GA)-matched healthy pregnant women (control group). Six patients in the FGR group received treatment with tadalafil administered at 20 mg twice daily after the first MRI until delivery. They underwent a second MRI 1 week later. The median total UtA blood/body surface area was 420 mL/min/m2 (290–494) in the FGR group and 547 mL/min/m2 (433–681) in the control group (p = 0.01). Percent increase of blood flow in the FGR and control groups were significantly different at 68.8% (51–75) and 18.8% (16.0–57), respectively (p < 0.01). UtA blood flow in pregnant women with FGR was significantly lower than that in healthy pregnant women. Tadalafil is expected to improve UtA blood flow, thereby improving placental function in pregnant patients with FGR.
Usefulness of a questionnaire for assessing the relationship between eating behavior and fatty liver disease among Japanese male young adults
Authors: Miwa Takao , Tajirika Satoko , Hanai Tatsunori , Imamura Nanako , Adachi Miho , Horita Ryo , Fukao Taku , Shimizu Masahito , Yamamoto Mayumi 
Published: July 2023

Abstract
This study aimed to reveal the relationship between eating behavior and nonalcoholic fatty liver disease (NAFLD)/metabolic dysfunction-associated fatty liver disease (MAFLD) in young adults and suggest a questionnaire for eating behavior assessment. We included 330 male graduate students at Gifu University in April 2022. Diagnoses of NAFLD and MAFLD were based on the presence of hepatic steatosis on ultrasonography. Eating behavior was assessed using the eating behavior questionnaire (EBQ) recommended by the Japan Society for the Study of Obesity. We assessed the eating behaviors associated with NAFLD and MAFLD using logistic regression, decision tree, and random forest analyses. The median age of the participants was 22 years, and 10% and 16% had NAFLD and MAFLD, respectively. The total EBQ score was significantly higher in participants with MAFLD than in those without MAFLD (102 vs. 91 points, P = 0.003) and in those with NAFLD than in those without NAFLD (97 vs. 91 points, P = 0.010). Among eating behavior categories, the decision tree and random forest analyses revealed that “perception of constitution and weight” was the strongest contributor for NAFLD/MAFLD. Our study revealed that eating behavior assessed with EBQ is robustly associated with NAFLD and MAFLD in young male adults.
Causal Associations Between Ankylosing Spondylitis and 36 Common Mental Disorders: A Two-Sample Mendelian Randomization Study
Authors: Wang Jiachen , Yang Mingyi , Xu Ke , Luo Pan , Feng Ruoyang , Wan Xianjie , Xie Jiale , Yu Hui , Xu Peng 
Published: July 2023

Abstract
Ankylosing spondylitis (AS) onset is often accompanied by psychiatric symptoms. In this study, two-sample Mendelian randomization (MR) was used to explore the genetic associations between AS and mental disorders. In this study, AS was regarded as exposure, and 36 mental disorders were regarded as outcomes. All the data were from the 7th version of the FinnGen GWAS summary data. Inverse-variance weighted (IVW), MR‒Egger regression, weight median, simple mode, and weight mode methods were used to determine the genetic associations. The Cochrane Q test, Egger-intercept test, MR pleiotropy residual sum and outlier, and leave-one-out tests were performed for sensitivity tests. The IVW results showed that AS was positively associated with autism, insomnia, depression, bipolar disorder, delirium, anankastic personality disorder, generalized anxiety disorder, anxious personality disorder, and mental and behavioral disorders due to opioids, hallucinogens, sedatives or hypnotics; AS was inversely associated with schizophrenia, persistent delusional disorder, and sexual dysfunction. The sensitivity tests showed these results were stable and robust. This study provides a theoretical basis for the early diagnosis of common mental disorders in patients with AS. It also provides evidence for the impact of inflammation on the central nervous system.
Sex, health and habitat alter the community composition and assembly processes of symbiotic bacteria in captive frogs
Authors: Liu Senlin , Imad Sewar , Hussain Sarfraz , Xiao Shuiqing , Cao Hui 
Published: July 2023

Abstract
Background
Frogs are critical economic animals essential to agricultural ecosystem equilibrium. Frog symbiotic microbes possess functions like elemental cycling and immune regulation, but little is known about how frog sex and health impact gut microbes. The relationship between frog habitat and soil microbes is unclear. We aimed to determine how frog sex, health and habitat influence symbiotic microbes and community assembly. To provide guidance for sustainable frog farming and conservation. We studied gut contents and symbiotic soils of frogs from a farm with Meningitis-like infectious diseases (MID).
Results
We used 16S rRNA sequencing to analyze gut microbes among frog sex and health. We also compared symbiotic microbes in frog aggregation soils, native soils, and soybean soils on the farm. Frog sex and health strongly impacted gut microbe β-diversity and taxonomy. Healthy frogs had better gut microbial metabolism. Symbiotic network analysis showed healthy female frogs were more complex than males, but diseased males were more complex than females. Male frog gut microbe assembly was primarily deterministic, but female assembly was stochastic. Stochastic dispersal limitation predominated gut microbe assembly in frogs of different health. Deterministic processes most strongly influenced soybean soil symbionts. Pathogens, nitrogen respiration/fixation were enriched in soybean soil. Sulfur respiration and hydrocarbon degradation were highest in aggregation soil.
Conclusion
Frog gut symbionts showed major differences in network structure and assembly based on sex and health. Disease reduced gut symbiont metabolic function. Diverse symbiotic soils, especially soybean soils, could benefit frog farming. Our findings provide insight into the negative impacts of disease and other factors on frog symbiotic microbes. This could aid development of sustainable frog farming practices.
Quantitative study of LUV-GUV interaction using fluorescence lifetime imaging microscopy and fluorescence correlation spectroscopy
Authors: Bruun Kristina , Löhmannsröben Hans-Gerd , Hille Carsten 
Published: July 2023

Abstract
Drug delivery systems are frequently used for targeted transport of pharmaceuticals and their controlled release at a destined target site. One of the most commonly used drug carriers are liposomes. Additionally, such drug-liposome system is used as model system for studying interaction processes at cellular or even molecular level. The aim of our work was to improve the understanding of drug carrier uptake mechanisms by applying fluorescence lifetime imaging microscopy (FLIM) and fluorescence correlation spectroscopy (FCS), both combined with two-photon (2P) excitation. We prepared giant unilamellar vesicles (GUVs) representing a simplified model system for cell membrane, labelled with the amphiphilic fluorescent dye 3,3'-dioctadecyloxacarbocyanine (DiOC18(3)). Furthermore, large unilamellar vesicles (LUVs) were used as a drug carrier system, containing the spectrally different fluorescent sulforhodamine 101 (SRh101) as drug imitate. Herein, we present results of the varying interaction between GUVs and LUVs depending on the used charged lipids. The exchange kinetics and structural changes of the liposome carriers during the fusion process were investigated. We also observed that the internalisation efficiency was mainly influenced by the vesicle´s lipid composition. We ultimately demonstrated that 2P-FLIM and FCS provide a unique methodological approach to study liposome interactions and use them as a versatile model system.
Prediction of glass chemical composition and type identification based on machine learning algorithms
Authors: Chen Ziwei , Xu Yang , Zhang Chao , Tang Min 
Published: July 2023

Abstract
Glass was a significant symbol of early trade exchanges on the Silk Road. However, the glass artifacts were susceptible to environmental influences when buried underground, leading to weathering and changes in their chemical composition. Analyzing the chemical composition of ancient glass was conducive to evaluate weathering status and propose the measures to reduce glass weathering. The objective of this study was to explore the optimal machine learning algorithm for glass type classification based on chemical composition. A set of glass artifact data including color, emblazonry, weathering, and chemical composition was employed and various methods including logistic regression and machine learnings were used. Results indicated a significant correlation (p < 0.05) was only observed between surface weathering and the glass types (high-potassium and lead-barium). Based on the random forest and logistic regression, the primary chemical components that signifying glass types and weathering status were determined by PbO, K2O, BaO, SiO2, Al2O3, and P2O5. The random forest model presented superior capability for identifying glass types and weathering status, with a global accuracy of 96.3%. This study demonstrates great potential of machine learning for glass chemical component estimation and glass type and weathering status identification providing technical guidance for the appraisal of ancient glass artifacts.