bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modeling dissolved Fe and H 2 inter-relationships under low pressure natural systems: Insights on long term hydrogen storage
Authors: Pathak Arkajyoti , Bowman Samuel , Agrawal Vikas , Sharma Shikha 
Published: September 2023

Abstract
Subsurface hydrogen storage is necessary to shift towards sustainable and zero-emission energy technologies, but geochemical data on the suitability of different reservoirs for hydrogen storage are scarce. Studies on complex chemical dynamics of aqueous Fe2+ and H2 have partially quantified the degree of loss for hydrogen gas in the subsurface at different operating pressures of hydrogen. However, a consensus regarding their thermodynamic relationships is lacking. In this study, we have investigated the magnitude of variation of hydrogen partial pressure in the subsurface in the presence of various concentrations of dissolved Fe2+ through simulations. Observations imply that for considerably low partial pressures of hydrogen (~ 10 − 5 bars), a feature of many natural brines, decreasing activity of Fe2+ by an order of magnitude can reduce the initial partial pressure of hydrogen by 3–4 orders of magnitude within a few years, due to enhanced reductive dissolution of the oxides. When pH2 of injected hydrogen exceeds 10 − 2 bars, magnetite becomes dominant as a secondary phase after the reduction of primary Fe3+ oxides, leading to almost three orders of magnitude of H2 (gaseous) loss that is almost independent of variation in Fe2+ activity. Both processes are supplemented with a varying degree of Fe2+ increase in the aqueous phase, supporting the release of Fe2+ to the aqueous phase due to Fe3+ oxide dissolution. These results point towards the degree of formation of magnetite as a potential controller of brine chemistry that depends upon nucleation kinetics and a threshold partial pressure for injected H2 under low reservoir temperatures (50–100℃). These results directly apply to understanding the cycling of redox-controlled elements and injected hydrogen in subsurface aqueous systems.
Navier-Stokes bounds and early turbulent scaling for compact trefoils in (2ℓπ)3 domains.
Authors: Kerr Robert 
Published: September 2023

Abstract

A principle largely unknown outside of the applied analysis fluids community is that ν≠0Navier-Stokes solutions in (2π)3 periodic domains are bounded by their ν ≡ 0 Euler solutions as ν → 0 for ν < νs, with the νs critical viscosities coming from analysis in higher-s Sobolev Hs spaces. This result also bounds lower-s norms. Could modest Reynolds number viscous calculations in larger domains be influenced by this result? Numerically, for (2lπ)3 domains, empirical critical viscosities νc(l) have been identified using compact trefoil vortex knots. √νZ(t), Z(t) enstrophy could be disrupted if ν < νc (l). And then restored if l is increased. That type of convergence has now been extended to higher-order vorticity moments with temporal convergence of ν1/4Ωm, m = 9,∞, at tm < tx, scaling that is consistent with the empirical observation that the domain should increase as l ∼ ν-1/4 as the observed vortex sheets grow with decreasing ν. Once formed, enstrophy growth accelerates as those sheets roll-up, leading to convergent dissipation rates with ε = νZ at t ∼ teps ∼ 2tx. Simultaneously, between tx and teps, a Zv ∼ k1/3 enstrophy spectrum develops, analogous to a k-5/3 energy spectrum. To explain these observations, the Sobolev νs critical viscosity analysis in (2π)3 domains is extended to larger (2lπ)3, l > 1, domains. The method squeezes the ∥u)∥s ̇+1 of Navier- Stokes solutions in a large (2lπ)3 domain into a (2π)3 domain, then in (2π)3 applies the resulting ∥u_λ∥.s+1+1 (λ = l) to approximations of the Hs2pi Sobolev mathematics developed in (2π)3 domains. Finally, the resulting νs2pi are rescaled back into the original (2lπ)3 domain. Resulting in decreasing νs ∼ exp( ∫λs+1∥ul(τ)∥.s+1dτ)λ3 as λ = l increases, with the ∥ul(τ)∥.s+1coming from the original domain and the exponential factor dominating over the algebraic λ3 factor. In the discussion, mathematics that might fill gaps between the high-s Sobolev analysis and the numerical analysis is mentioned.
Synergistic Nickel-Molybdenum Carbide-Graphite Nanofiber Composite Catalyst for Enhanced Green Hydrogen Production Through Ethanol Electrooxidation
Authors: Barakat Nasser A. M. , Gomaa Hassan E. , Khalil Khalil , Al-Mubaddel Fahad S , Abdel-Aty Marwa M. 
Published: September 2023

Abstract
Novel nickel-molybdenum carbide-graphite nanofiber composite is introduced as an electrocatalyst to produce green hydrogen from ethanol electrooxidation. The proposed nanofibers have been prepared by calcinating electrospun nanofibers composed of nickel acetate tetrahydrate, molybdenum chloride, and poly (vinyl alcohol). Physicochemical characterizations have indicated that during the sintering process, nickel acetate is entirely reduced to nickel metal, and molybdenum has bonded with carbon to produce molybdenum carbide. At the same time, the used polymer has been pyrolyzed to produce a carbon nanofiber matrix embedding formed inorganic nanoparticles. Electrochemical measurements concluded that both molybdenum content and calcination temperature should be controlled to maximize the electrocatalytic activity of the proposed catalyst. Typically, the oxidation peak current density was 28.5, 28.8, 51.5, 128.3, 25.6, and 3 mA/cm2 for nanofibers prepared from an electrospun solution containing 0, 5, 10, 15, 25, and 35 wt% molybdenum carbide, respectively. Moreover, the optimum calcination temperature was found to be 1000 oC. Kinetic studies have indicated that the order of reaction is close to zero with a reaction temperature-dependent value. Moreover, it was detected that electrooxidation reaction of ethanol over the proposed nanofiber composite follows Arrhenius equation, the determined activation energy is 33 kJ/mol which indicates good catalytic activity of the introduced nanofibers. Through the application of a set of visualization-based tools and the general linear model (GLM), the optimal conditions that generate the highest current density were identified. The computations unveiled that the optimal parameter settings are as follows: Mo content at 15 wt.%, methanol concentration of 1.55 M, and reaction temperature of 59°C.
The Role of Methyl Jasmonate During the Biotic Stress in Matricaria Chamomilla L.
Authors: Dučaiová Zuzana , Petrulova Veronika 
Published: September 2023

Abstract
The objective of the present study was to evaluate the effect of methyl jasmonate (MeJA) in plant resistance to polyphagous thrips. Eight-weeks old diploid and tetraploid chamomile plants (Matricaria chamomilla) in stage of leaf-rosettes were pre-treated with 0.22 mM MeJA for 72 h and then co-cultivated with thrips for next 96 h. In both cultivars, there was an increase in the content of hydrogen peroxide and superoxide radical, with a maximum in plants after thrips infestation. The pre-treatment with MJ led to a reduction, but the measured values were still higher than those in the control plants. The accumulation of total phenols and flavonoids corresponded with the activity of phenylalanine ammonia-lyase (PAL). The highest PAL activity and the highest levels of total phenols were observed in plants infected with thrips. MeJA pre-treatment slightly decreased their values. Within the cultivars we noticed differences in the accumulation of monitored coumarins: (Z)- and (E)-GMCA, herniarin and umbelliferone. In diploids MeJA significantly ameliorated their accumulation caused by thrips. On the other hand, in tetraploids, changes were minimal. The amount of umbelliferone sharply increased in both cultivars which points to its role as a stress metabolite.
AEGAN-Pathifier: A data augmentation method to improve cancer classification for imbalanced gene expression data
Authors: Zhang Qiaosheng , Wei Yalong , Hou Jie , Li Hongpeng , Zhong Zhaoman 
Published: September 2023

Abstract

Background: Cancer classification has consistently been a challenging problem, with the main difficulties being high-dimensional data and the collection of patient samples. Concretely, obtaining patient samples is a costly and resource-intensive process, and imbalances often exist between samples. Moreover, expression data is characterized by high dimensionality, small samples and high noise, which could easily lead to struggles such as dimensionality catastrophe and overfitting. Thus, we incorporate prior knowledge from the pathway and combine AutoEncoder and Generative Adversarial Networks (GANs) to solve these difficulties.
Results: In this study, we propose an effective and efficient deep learning method, called AEGAN, for generating synthetic samples of the minority class in imbalanced gene expression data. The proposed data balancing technique has been demonstrated to be highly useful for cancer classification and improving the performance of classifier models. Additionally, we integrate prior knowledge from the pathway and employ the pathifier algorithm to calculate pathway scores for each sample. This data augmentation approach, referred to as AEGAN-Pathifier, not only preserves the biological features of the data but also possesses dimensionality reduction capabilities. Through extensive validation with various classifiers, the experimental results consistently show an improvement in classifier performance.
Conclusion: AEGAN-Pathifier demonstrates superior performance on all three imbalanced datasets: GSE25066, GSE20194, and Liver24. The results obtain with various classifiers strongly indicate the remarkable generalizability of AEGAN-Pathifier, making it easily applicable to other tasks.
Escherichia coli Isolation, Prevalence, and Multi Drug Resistance from a Poultry Farm in Sendafa Town, Central Ethiopia
Authors: Umer Abdi Ahmed , Hambisa Ebisa Mezgebu 
Published: September 2023

Abstract
Background: Escherichia coliis bacteria that exist as commensal in the intestine of animals and humans, but pathogenic strains cause disease in chickens. The growth of antimicrobial resistance in E. coli is one of major concern worldwide.
Objective: This study aimed to assess the prevalence, and Multi drug resistance profile and determine the potential risk factor of E. coli isolates from chickens and chickens environment in Sendafa town, central Ethiopia
Methods: A cross-sectional study was carried out from January to August 2023 in Sendafa town. Purposive sampling techniques were used based on the presence of clinical symptoms suggestive of E. coli in chicken farms. Different types of samples were collected including 207 cloacae swabs, 8 feed, and 8 water from different farms. E. coli isolation and identification were done using bacterial culture, and biochemical, and confirmed using the Matrix Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry (MALDI TOF MS). Antimicrobial susceptibility testing (AST) was done using the Kirby Bauer disc diffusion method. Data were entered in Microsoft Excel and analyzed with descriptive statistics using SPSS version 20.
Result: Out of a total of 223 samples of cloacae swab, feed, and water 71 (31.83 %) were found to be E. coli suspected by biochemical and finally confirmed with Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry (MALDI TOF MS). All confirmed isolates were subjected to 12 antimicrobial agents to check their susceptibility. From 71 tested E. coliisolates we found resistant patterns of E. coli to 62(87.3%) Amoxicillin, 44(62%) Tetracycline, and 39(54.9%) Streptomycin respectively. Multi-drug resistance was observed in this study for two or more than resistant detected. Some isolate was sensitive to 60(84.5%) Trimethoprim Sulphamethoxazole, 57(80.3%) Norfloxacin, 56(78.9 %) Ceftriaxone, and 53(74.6%) Meropenem respectively. Intermediate antibiotics were observed on 32(45.1 %) Sulfonamides, and 23(32.4%) Gentamicin for E. coli isolate.
Risk factors were analyzed with descriptive statistics. In the study, the difference in E. coli prevalence by age and among sample types was not statistically significant (P>0.05). Between kebeles and farms, there was a statistically significant difference in E. coli prevalence (P <0.05).
Conclusion: In this study, a high incidence of E. coli and antibiotic resistance to commonly used antibiotics including Amoxicillin, Tetracycline, and Streptomycin in poultry were found. This implies that there is the existence of practices that accelerate antimicrobial resistance in the sampled chickens. Therefore, appropriate use of antimicrobial agents, good biosecurity measures, and hygiene practices in chicken farms are important.
Cardiac Biomarkers Aid in Differentiation of Kawasaki Disease from Multisystem Inflammatory Syndrome in Children Associated with COVID-19
Authors: Walton Mollie , Raghuveer Geetha , Harahsheh Ashraf , Portman Michael A. , Lee Simon , Khoury Michael , Dahdah Nagib , Fabi Marianna , Dionne Audrey , Harris Tyler H. , Choueiter Nadine , Garrido-Garcia Luis Martin , Jain Supriya , Dallaire Frédéric , Misra Nilanjana , Hicar Mark D. , Giglia Therese M. , Truong Dongngan T. , Tierney Elif Seda Selamet , Thacker Deepika , Nowlen Todd T. , Szmuszkovicz Jacqueline R. , Norozi Kambiz , Orr William B. , Farid Pedrom , Manlhiot Cedric , McCrindle Brian W. , Alsalehi Mahmoud , Ballweg Jean A. , Barnes Benjamin T. , Braunlin Elizabeth , Buffone Ashley , Bustamante-Ogando Juan Carlos , Chang Arthur J. , Corral Nicolas , Cowles Heather , Dancey Paul , de Ferranti Sarah D , Ganzoury Mona El , Elias Matthew , Elsamman Nora , Cooke Elisa Fernández , Goldenberg Guillermo Larios , Grcic Michelle M. , Harris Kevin C. , Jone Pei-Ni , Kajimoto Hidemi , Khare Manaswitha , Kutty Shelby , Lanari Marcello , Mauriello Daniel , McHugh Kimberly E. , Merves Shae A. , Mohandas Sindhu , Mondal Tapas , Pagano Joseph J. , Prasad Deepa , Ravi Prasad 
Published: September 2023

Abstract
Background: Kawasaki disease (KD) and Multisystem Inflammatory Syndrome in Children (MIS-C) associated with COVID-19 show clinical overlap and both lack definitive diagnostic testing, making differentiation challenging. We sought to determine how cardiac biomarkers might differentiate KD from MIS-C.
Methods: The International Kawasaki Disease Registry enrolled contemporaneous KD and MIS-C pediatric patients from 42 sites from January 2020 through June 2022. The study population included 118 KD patients who met American Heart Association KD criteria and compared them to 946 MIS-C patients who met 2020 Centers for Disease Control and Prevention case definition. All included patients had at least one measurement of amino-terminal prohormone brain natriuretic peptide(NTproBNP) or cardiac troponin I (TnI), and echocardiography. Regression analyses were used to determine associations between cardiac biomarker levels, diagnosis, and cardiac involvement.
Results: Higher NTproBNP (>1500 ng/L) and TnI (>20 ng/L) at presentation were associated with MIS-C versus KD with specificity of 77 and 89% respectively. Higher biomarker levels were associated with shock and intensive care unit admission; higher NTproBNP was associated with longer hospital length of stay. Lower left ventricular ejection fraction, more pronounced for MIS-C, was also associated with higher biomarker levels. Coronary artery involvement was not associated with either biomarker.
Conclusions: Higher NTproBNP and TnI levels are suggestive of MIS-C versus KD and may be clinically useful in their differentiation. Consideration might be given to their inclusion in the routine evaluation of both conditions.
Short Text Analytics based on BERT by using Multivariate Filter Methods for Feature Selection
Authors: Qais Emad , MN Veena 
Published: September 2023

Abstract
This article present a short text analytics method that uses BERT (Bidirectional Encoder Representations from Transformers) and multivariate filter methods for selecting features. In a world where there is a lot of short written data from many different fields, it is hard to find meaningful insights. This makes it important to come up with new methods that can take into account the context and pick out the most important parts for analysis. This study goes into this area and looks at how BERT's understanding of context and the ability of multiple filters to make distinctions can work together. Through a series of carefully planned experiments, the proposed model shows that a hybrid method improves the accuracy, readability, and speed of short text analysis. The results show that predictive metrics have gotten a lot better, which proves that proposed model way will make a big difference. This work not only helps move the field of natural language processing forward, but it also has real-world uses in areas like sentiment analysis, social media tracking, and understanding customer feedback. As digital communication continues to change, the method is set up to find nuanced insights in the short textual data that is dense with information.
Experimental Investigation of Mechanical Properties of Problematic Expansive Soil using Copper Slag and Its Statistical Validation
Authors: Jangid Amit Kumar , Grover Kamaldeep Singh 
Published: September 2023

Abstract
This experimental research has been conducted to improve the mechanical properties of the problematic expansive soil using copper slag. The copper slag has been utilized to improve the Talab soil in Nainwa for the first time. These mechanical properties are consistency limits, compaction, and strength properties. The swelling properties show that the collected soil has a high degree of expansive nature and low specific gravity. Therefore, the copper slag has been added to the soil from 5–30% at a 5% variation by its oven-dry weight. The experimental results reveal that the free swell index of soil has decreased by 69.88% with the addition of 30% copper slag. It has also been observed that the liquid and plastic limits have been decreased. The plastic limit of soil decreases because copper slag takes place in voids. Due to this phenomenon, the maximum dry density of soil has been increased by 14.75% with the addition of 25% copper slag. The California bearing ratio (CBR) value of soil has been increased to 1.13% (soaked condition) and 3.8% (unsoaked condition) by adding 25% copper slag. This research introduces an empirical relationship between unsoaked and soaked CBR with a determination coefficient (R2) of 0.8254. Moreover, it has been observed that the unconfined compressive strength of soil has increased by 51.68% with the addition of 25% copper slag. Moreover, the value of R2 for the experimental results obtained in this research is higher than the published experimental results, presenting the experimental study's accuracy and reliability. In addition, the analysis of variance (ANOVA) test accepts the research hypothesis for the present investigation.
Prediction of BMI traits in the Chinese population based on the gut metagenome
Authors: Liang Yu , Dou Shujie , Zhao Guangzhong , Shen Jie , Dong Chunnan , Fu Guangping , Fu Lihong , Li Shujin , Cong Bin 
Published: September 2023

Abstract
Background: Identifying the individual characteristics of trace evidence left at a crime scene is crucial in forensic identification. Microbial communities found in fecal traces have high individual specificity and could serve as potential markers for forensic characterization. Previous research has established that predicting body type based on the relative abundance of gut microbiome is relatively accurate. However, the long-term stability and high individual specificity of gut microbiome are closely linked to changes in the microbiome genome levels. No studies have been conducted to deduce body size from genetic traits. Therefore, this study investigates the vital role of gut bacterial community characteristics and genetic traits in predicting body mass index (BMI) using gut metagenomic data from a healthy Chinese population.
Results: Regarding the gut microbial community, the underweight group displayed increased α-diversity in comparison to the other BMI groups. There were significant variations in the relative abundance of 19 species between these three BMI groups. There were significant differences in the relative abundance of 19 species among these three BMI groups. The BMI prediction model, based on the 31 most significant species, showed a goodness of fit (R2) of 0.56 and a mean absolute error (MAE) of 2.09 kg/m2. The overweight group exhibited significantly higher α-diversity than the other BMI groups at the level of gut microbial genes. Furthermore, there were significant variations observed in the single-nucleotide polymorphisms (SNP) density of 732 contigs between these three BMI groups. The BMI prediction model, reliant on the 62 most contributing contigs, exhibited a model R2 of 0.72 and a MAE of 1.56 kg/m2. The model predicting body type from 44 contigs correctly identified 93.55% of the study participants.
Conclusion: Based on metagenomic data from a healthy Chinese population, we demonstrate the potential of genetic traits of gut bacteria to predict an individual's BMI. This discovery suggests a novel method for determining the body type of suspects in forensic applications using the genetic traits of the gut microbiome and holds great promise for forensic individual identification.
This work was supported by National Natural Science Foundation of China Youth Science Fund Project (81701865), Hebei Province Natural Science Foundation Project (H2020206107).
Transarterial chemoembolization for advanced hepatocellular carcinoma after failure of first-line systemic treatment: a single-center case series
Authors: Leng Bin , Diao Lingfeng , You Ran , YU Zeyu , Xu Qingyu , Yin Guowen 
Published: September 2023

Abstract

Purpose:To demonstrate the potential benefits of additional transarterial chemoembolization (TACE) for advanced hepatocellular carcinoma (HCC) after the failure of first-line systemic treatment (ST).Methods: This retrospective single-center study was conducted between January 2020 and December 2022 on patients with advanced HCC who failed to respond to initial first-line ST. Patients who had previously undergone TACE were excluded. Eligible patients underwent on-demand TACE in addition to ST and were followed until death or until March 2023. The duration of response was recorded. Overall survival (OS) was calculated from the date of failure of first-line ST to the date of death or last follow-up. The primary outcomes were OS and safety, and the secondary outcomes were time to progression (TTP) and objective response rate (ORR).Results: In total, 18 patients were included; 8 patients had failed to respond to lenvatinib or sorafenib monotherapy, and 10 had failed to respond to a combination therapy. The most common progression pattern was the development of new intrahepatic lesions. Salvage treatment consisted of 16 triple therapies and 2 dual therapies, including TACE. The median duration of follow-up was 9.5 months. The median OS from the start of second-line treatment was 24 months. The median TTP was 3.5 months. The ORR was 55.6%, and disease control was achieved in 94.4% of patients. Treatment-related adverse events were common but acceptable.Conclusion: Patients with advanced HCC who face significant treatment challenges could potentially benefit from the addition of TACE to second-line ST.