bluuebunny/crossref_metadata_2025 huggingface dataset:
Dry and Minimum Quantity Lubrication Machining of Additively Manufactured IN718 Produced via Laser Metal Deposition
Authors: Ozaner Ozan Can , Kapil Angshuman , Sato Yuji , Hayashi Yoshihiko , Ikeda Keiichiro , Suga Tetsuo , Tsukamoto Masahiro , Karabulut Sener , Bilgin Musa , Sharma Abhay
Published: December 2023

Inconel 718 (IN718), a Ni-based superalloy, is immensely popular in the aerospace, nuclear, and chemical industries. In these industrial fields, IN718 parts fabricated using conventional and additive manufacturing routes require subsequent machining to meet the dimensional accuracy and surface quality requirements of practical applications. The machining of IN718 has been a prominent research topic for conventionally cast, wrought, and forged parts. However, very little attention has been given to the machinability of IN718 additively manufactured using laser metal deposition (LMD). This lack of research can lead to numerous issues derived from the assumption that the machining behavior corresponds to conventionally fabricated parts. To address this, our study comprehensively assesses the machinability of LMDed IN718 in dry and minimum quantity lubrication (MQL) cutting environments. Our main goal is to understand how LMD process variables and the cutting environment affect cutting forces, tool wear, surface quality, and energy consumption when working with LMDed IN718 walls. To achieve this, we deposited IN718 on SS309L substrates while varying the following LMD process parameters: laser power, powder feed rate, and scanning speed. The results unveil that machining the deposited wall closer to the substrate is significantly more difficult than away from the substrate, owing to the variance in hardness along the build direction. MQL greatly improves machining across all processing parameters regardless of the machining location along the build direction. Laser power is identified as the most influential parameter, along with the recommendation for a specific combination of power feed rate and scanning speed, providing practical guidelines for optimizing the machining process. While MQL positively impacts machinability, hourly energy consumption remains comparable to dry cutting. This work offers practical guidance for improving the machinability of LMDed IN718 walls and the successful adoption of LMD and the additive–subtractive machining chain. The outcomes of this work provide a significant and critical understanding of location-dependent machinability that can help develop targeted approaches to overcome machining difficulties associated with specific areas of the LMDed structure. The finding that MQL significantly improves machining across all processing parameters, particularly in the challenging bottom region, offers practical guidance for selecting optimal cutting conditions. The potential economic benefits of MQL in terms of tool longevity without a substantial increase in energy costs is also highlighted, which has implications for incorporating MQL in several advanced manufacturing processes.
Preparation and Tribological Behavior of Nitrogen-Doped Willow Catkins/MoS2 Nanocomposites as Lubricant Additives in Liquid Paraffin
Authors: Xing Yaping , Liu Ebo , Ren Bailin , Liu Lisha , Liu Zhiguo , Zhu Bocheng , Wang Xiaotian , Jia Zhengfeng , Han Weifang , Bai Yungang
Published: December 2023

In this study, willow catkins/MoS2 nanoparticles (denoted as WCMSs) have been prepared using a hydrothermal method. The WCMSs were modified with oleic acid (OA) to improve dispersion in base oil. The friction and wear properties of WCMSs in liquid paraffin (LP) for steel balls were investigated using a four-ball wear tester. The results have shown that at a high reaction temperature, willow catkins (being used as a template) and urea (being used as a nitrogen resource) can effectively decrease the wear scar diameters (WSDs) and coefficients of friction (COFs). At a concentration of 0.5 wt.%, the WSD and COF of steel balls, when lubricated using LP containing modified WCMS with urea, decreased from 0.65 mm and 0.175 of pure LP to 0.46 mm and 0.09, respectively. The addition of urea and hydroxylated catkins can generate a significant number of loose nano-sheets and even graphene-like sheets. The weak van der Waals forces, decreasing the shear forces that the steel balls must overcome, provide effective lubrication during rotation. On the other hand, the tribo-films containing MoS2, FeS, azide, metal oxides and other compounds play important roles in reducing friction and facilitating anti-wear properties.
Dynamometric Investigation on Airborne Particulate Matter from Automobile Brake: Impact of Disc Materials on Brake Emission Factor
Authors: Jeong Mu Hyeok , Shin Won Cheol , Oh Yoon-Suk , Lee Jungju , Huh Seung Hun , Pee Jae-Hwan , Seo Hyungjo , Jang Ho , Kim Jong-Young
Published: December 2023

In this work, we evaluated the impact of disc rotors of gray cast iron (GCI), nitrocarburized (NC), and superhard ceramic-coated (SCC) GCI on the brake wear PM emissions of passenger vehicles using dynamometric measurements. The brake emission factor (BEF) of the SCC was greatly reduced by more than a factor of 1/5 compared with those for the GCI and NC for both low-steel and non-steel friction materials. Surface topological and microstructural analyses confirmed that more severe wear was pronounced for the NC rotor compared with the SCC, as evidenced by large concave pits in the wear tracks. Analysis of the size-classified airborne PM suggests that reduced micron-sized particles, which originated from the GCI disc, were responsible for the lower BEF due to the increased hardness of the SCC.
Study on Aerodynamic Drag Reduction by Plasma Jets for 600 km/h Vacuum Tube Train Sets
Authors: Li Ang , Cui Hongjiang , Guan Ying , Deng Jichen , Zhang Ying , Deng Wu
Published: December 2023

In order to break through the speed bottleneck, researchers envision using tubes to cover high-speed maglev trains and extract some of the air inside the tubes, creating a low-density environment on the ground, greatly reducing the aerodynamic drag of the trains, and in a relatively economical and feasible way, making high subsonic (600 km/h and above) and even supersonic ground transportation possible. The faster the running speed of high-speed trains, the greater the impact of aerodynamic drag on their energy consumption. Studying the aerodynamic characteristics of trains with a speed of 600 km/h can help optimize the aerodynamic shape of the train, reduce aerodynamic drag, and reduce energy consumption. This has positive implications for improving train energy efficiency, reducing energy consumption, and environmental impact. This paper adopts the numerical simulation method to study the drag reduction effect of the plasma arrangement and different excitation speeds on the train set in four positions when the incoming wind speed is 600 km/h, to analyze the mechanism of drag reduction, and then to analyze the combination of working conditions in order to investigate the drag reduction effect of plasma on the vacuum tube train set with an ambient pressure of 10,000 Pa. The findings demonstrate that the plasma induces the directional flow of the gas close to the wall to move the flow separation point backward and delay the separation of the flow, thereby reducing the front and rear differential pressure drag of the train set and lowering the aerodynamic drag coefficient of the entire train. The plasma arrangement is located at the rear of the flow separation point and in close proximity to the flow separation point. The pneumatic drag reduction effect peaks when the excitation speed reaches 0.2 times the train speed and the pneumatic drag reduction ratio is around 0.88%; the pneumatic drag reduction ratio of the rear car peaks when the excitation speed reaches 0.25 times the train speed and the pneumatic drag reduction ratio is 1.62%. The SDBD (Surface Dielectric Barrier Discharge) device is installed at the flow separation point around the nose tip of the rear car.
Deep Learning-Based Approach for Autonomous Vehicle Localization: Application and Experimental Analysis
Authors: Markó Norbert , Horváth Ernő , Szalay István , Enisz Krisztián
Published: December 2023

In a vehicle, wheel speed sensors and inertial measurement units (IMUs) are present onboard, and their raw data can be used for localization estimation. Both wheel sensors and IMUs encounter challenges such as bias and measurement noise, which accumulate as errors over time. Even a slight inaccuracy or minor error can render the localization system unreliable and unusable in a matter of seconds. Traditional algorithms, such as the extended Kalman filter (EKF), have been applied for a long time in non-linear systems. These systems have white noise in both the system and in the estimation model. These approaches require deep knowledge of the non-linear noise characteristics of the sensors. On the other hand, as a subset of artificial intelligence (AI), neural network-based (NN) algorithms do not necessarily have these strict requirements. The current paper proposes an AI-based long short-term memory (LSTM) localization approach and evaluates its performance against the ground truth.
A Technique for Bearing Fault Diagnosis Using Novel Wavelet Packet Transform-Based Signal Representation and Informative Factor LDA
Authors: Maliuk Andrei , Ahmad Zahoor , Kim Jong-Myon
Published: December 2023

This paper proposes a new method for bearing fault diagnosis using wavelet packet transform (WPT)-based signal representation and informative factor linear discriminant analysis (IF-LDA). Time–frequency domain approaches for analyzing bearing vibration signals have gained wide acceptance due to their effectiveness in extracting information related to bearing health. WPT is a prominent method in this category, offering a balanced approach between short-time Fourier transform and empirical mode decomposition. However, the existing methods for bearing fault diagnosis often overlook the limitations of WPT regarding its dependence on the mother wavelet parameters for feature extraction. This work addresses this issue by introducing a novel signal representation method that employs WPT with a new rule for selecting the mother wavelet based on the power spectrum energy-to-entropy ratio of the reconstructed coefficients and a combination of the nodes from different WPT trees. Furthermore, an IF-LDA feature preprocessing technique is proposed, resulting in a highly sensitive set of features for bearing condition assessment. The k-nearest neighbors algorithm is employed as the classifier, and the proposed method is evaluated using datasets from Paderborn and Case Western Reserve universities. The performance of the proposed method demonstrates its effectiveness in bearing fault diagnosis, surpassing existing techniques in terms of fault identification and diagnosis performance.
Generalized Permutants and Graph GENEOs
Authors: Ahmad Faraz , Ferri Massimo , Frosini Patrizio
Published: December 2023

This paper is part of a line of research devoted to developing a compositional and geometric theory of Group Equivariant Non-Expansive Operators (GENEOs) for Geometric Deep Learning. It has two objectives. The first objective is to generalize the notions of permutants and permutant measures, originally defined for the identity of a single “perception pair”, to a map between two such pairs. The second and main objective is to extend the application domain of the whole theory, which arose in the set-theoretical and topological environments, to graphs. This is performed using classical methods of mathematical definitions and arguments. The theoretical outcome is that, both in the case of vertex-weighted and edge-weighted graphs, a coherent theory is developed. Several simple examples show what may be hoped from GENEOs and permutants in graph theory and how they can be built. Rather than being a competitor to other methods in Geometric Deep Learning, this theory is proposed as an approach that can be integrated with such methods.
Statistical Analysis of Imbalanced Classification with Training Size Variation and Subsampling on Datasets of Research Papers in Biomedical Literature
Authors: Dixon Jose , Rahman Md
Published: December 2023

The overall purpose of this paper is to demonstrate how data preprocessing, training size variation, and subsampling can dynamically change the performance metrics of imbalanced text classification. The methodology encompasses using two different supervised learning classification approaches of feature engineering and data preprocessing with the use of five machine learning classifiers, five imbalanced sampling techniques, specified intervals of training and subsampling sizes, statistical analysis using R and tidyverse on a dataset of 1000 portable document format files divided into five labels from the World Health Organization Coronavirus Research Downloadable Articles of COVID-19 papers and PubMed Central databases of non-COVID-19 papers for binary classification that affects the performance metrics of precision, recall, receiver operating characteristic area under the curve, and accuracy. One approach that involves labeling rows of sentences based on regular expressions significantly improved the performance of imbalanced sampling techniques verified by performing statistical analysis using a t-test documenting performance metrics of iterations versus another approach that automatically labels the sentences based on how the documents are organized into positive and negative classes. The study demonstrates the effectiveness of ML classifiers and sampling techniques in text classification datasets, with different performance levels and class imbalance issues observed in manual and automatic methods of data processing.
Optimizing Multi-Layer Perovskite Solar Cell Dynamic Models with Hysteresis Consideration Using Artificial Rabbits Optimization
Authors: Bayoumi Ahmed Saeed Abdelrazek , El-Sehiemy Ragab A. , Badawy Mahmoud , Elhosseini Mostafa , Aljohani Mansourah , Abaza Amlak
Published: December 2023

Perovskite solar cells (PSCs) exhibit hysteresis in their J-V characteristics, complicating the identification of appropriate electrical models and the determination of the maximum power point. Given the rising prominence of PSCs due to their potential for superior performance, there is a pressing need to address this challenge. Existing solutions in the literature have not fully addressed the hysteresis issue, especially in the context of dynamic modeling. To bridge this gap, this study introduces Artificial Rabbits Optimization (ARO) as an innovative method for optimizing the parameters of an enhanced PSC dynamic model. The proposed model is constructed based on experimental J-V data sets of PSCs, ensuring that it accounts for the hysteresis characteristics observed in both forward and backward scans. The study conducted a rigorous statistical analysis to validate the Modified Two-Diode Model performance with that of the Energy Balance (MTDM_E) optimized using the innovative ARO algorithm. The performance metric utilized for validation was the Root mean square error (RMSE), a widely recognized degree of the differences between values predicted by a model and the values observed. The statistical analysis encompassed 30 independent runs to ensure the robustness and reliability of the results. The summary statistics for the MTDM_E model under the ARO algorithm demonstrated a minimum RMSE of 4.84E−04, a maximum of 6.44E−04, and a mean RMSE of 5.14E−04. The median RMSE was reported as 5.07E−04, with a standard deviation of 3.17E−05, indicating a consistent and tight clustering of results around the mean, which suggests a high level of precision in the model’s performance. Validated using root mean square error (RMSE) across 30 runs, the ARO algorithm showcased superior precision in parameter determination for the MTDM_E model, with a mean RMSE of 5.14E−04, outperforming other algorithms like GWO, PSO, SCA, and SSA. This affirms ARO’s robustness in optimizing solar cell models.
The Genotypic Imperative: Unraveling Disease-Permittivity in Functional Modules of Complex Diseases
Authors: Kaba Abdoul K. , Vomo-Donfack Kelly L. , Morilla Ian
Published: December 2023

In complex diseases, the interactions among genes are commonly elucidated through the lens of graphs. Amongst these genes, certain ones form bi-functional modules within the graph, contingent upon their (anti)correlation with a specific functional state, such as susceptibility to a genetic disorder of non-Mendelian traits. Consequently, a disease can be delineated by a finite number of these discernible modules. Within each module, there exist allelic variants that pose a genetic risk, thus qualifying as genetic risk factors. These factors precipitate a permissive state, which if all other modules also align in the same permissive state, can ultimately lead to the onset of the disease in an individual. To gain a deeper insight into the incidence of a disease, it becomes imperative to acquire a comprehensive understanding of the genetic transmission of these factors. In this work, we present a non-linear model for this transmission, drawing inspiration from the classic theory of the Bell experiment. This model aids in elucidating the variances observed in SNP interactions concerning the risk of disease.
Commodity Pricing and Replenishment Decision Strategy Based on the Seasonal ARIMA Model
Authors: Liu Jiaying , Liu Bin
Published: December 2023

As a crucial component of enterprise marketing strategy, commodity pricing and replenishment strategies often play a pivotal role in determining the profit of retailers. In pursuit of profit maximization, this work delved into the realm of fresh food supermarket commodity pricing and replenishment strategies. We classified commodities into six distinct categories and proceeded to examine the relationship between the total quantity sold in these categories and cost-plus pricing through Pearson correlation analysis. Furthermore, a Seasonal ARIMA model was established for the prediction of replenishment quantities and pricing strategies for each of the categories over a seven-day period. To ensure precise data, we extended our forecasting to individual products for a single day, employing 0–1 integer programming. To align the inquiry with real-world scenarios, we took into account various factors, including refunds, waste, discounts, and the requirement that individual products fall within specific selling ranges. The results show that the profit will be maximized when the replenishment of chili is 39.874 kg and the replenishment of edible mushrooms is 43.257 kg in the future week. We assume that the residual of the model is white noise. By testing the white noise of the model, the analysis of the residual Q statistic results shows that it is not significant in level, which can prove that the model meets the requirements and the obtained results are reliable. This research provides valuable insights into the realm of commodity pricing and replenishment strategy, offering practical guidance for implementation.
Closed-Loop Continuous-Time Subspace Identification with Prior Information
Authors: Yu Miao , Wang Wanli , Wang Youyi
Published: December 2023

This paper presents a closed-loop continuous-time subspace identification method using prior information. Based on a rational inner function, a generalized orthonormal basis can be constructed, and the transformed noises have ergodicity features. The continuous-time stochastic system is converted into a discrete-time stochastic system by using generalized orthogonal basis functions. As is known to all, incorporating prior information into identification strategies can increase the precision of the identified model. To enhance the precision of the identification method, prior information is integrated through the use of constrained least squares, and principal component analysis is adopted to achieve the reliable estimate of the system. Moreover, the identification of open-loop models is the primary intent of the continuous-time system identification approaches. For closed-loop systems, the open-loop subspace identification methods may produce biased results. Principal component analysis, which reliably estimates closed-loop systems, provides a solution to this problem. The restricted least-squares method with an equality constraint is used to incorporate prior information into the impulse response following the principal component analysis. The input–output algebraic equation yielded an optimal multi-step-ahead predictor, and the equality constraints describe the prior information. The effectiveness of the proposed method is provided by numerical simulations.
A Mathematically Exact and Well-Determined System of Equations to Close Reynolds-Averaged Navier–Stokes Equations
Authors: Ryu Sungmin
Published: December 2023

Since Sir Osborne Reynolds presented the Reynolds-averaged Navier–Stokes (RANS) equations in 1895, the construction of complete closure for RANS equations has been regarded as extremely challenging. Taking into account that the Navier–Stokes equations are not coherent for instantaneous and mean flows, a body of knowledge outside the scope of classical mechanics may be amenable to the closure problem. In this regard, the methodology of physics-to-geometry transformation, which is coherent for both flows, is applied to RANS equations to construct six additional equations. The proposed equations stand out from existing RANS closure models and turbulence quantity transport equations in two respects: they are mathematically exact and well-determined.
Use of Infrared Thermography in Medical Diagnosis, Screening, and Disease Monitoring: A Scoping Review
Authors: Kesztyüs Dorothea , Brucher Sabrina , Wilson Carolyn , Kesztyüs Tibor
Published: December 2023

Thermography provides non-invasive, radiation-free diagnostic imaging. Despite the extensive literature on medical thermography, a comprehensive overview of current applications is lacking. Hence, the aim of this scoping review is to identify the medical applications of passive infrared thermography and to catalogue the technical and environmental modalities. The diagnostic performance of thermography and the existence of specific reference data are evaluated, and research gaps and future tasks identified. The entire review process followed the Joanna Briggs Institute (JBI) approach and the results are reported according to PRISMA-ScR guidelines. The scoping review protocol is registered at the Open Science Framework (OSF). PubMed, CENTRAL, Embase, Web of Science, OpenGrey, OSF, and PROSPERO were searched using pretested search strategies based on the Population, Concept, Context (PCC) approach. According to the eligibility criteria, references were screened by two researchers independently. Seventy-two research articles were identified describing screening, diagnostic, or monitoring studies investigating the potential of thermography in a total of 17,314 participants within 38 different health conditions across 13 therapeutic areas. The use of several camera models from various manufacturers is described. These and other facts and figures are compiled and presented in a detailed, descriptive tabular and visual format. Thermography offers promising diagnostic capabilities, alone or in addition to conventional methods.
Correlation Theory of the Maxillary Central Incisor, Face and Dental Arch Shape in the Serbian Population
Authors: Kostić Milena , Đorđević Nadica S. , Gligorijević Nikola , Jovanović Marija , Đerlek Ermin , Todorović Kosta , Jovanović Goran , Todić Jelena , Igić Marko
Published: December 2023

Background and Objectives: According to the modified Williams theory, the shape of the maxillary central incisor corresponds to the shape of the maxillary alveolar ridge (dental arch) and the shape of the face. Moreover, the standards of beauty suggest that the center of the face of an individual with a full set of teeth should match the center of the maxillary and mandibular dental arches. The purpose of this study is to conduct a comparative cross-sectional study on the matching of the shape of the face, maxillary central incisor and maxillary dental arch as well as the matching of the midfacial line and dental arches in subjects with complete dentition. Materials and Methods: The study included 90 subjects of both sexes. The matching of the shape of the face and midfacial line, i.e., dental arches and maxillary incisors, was determined by analysing photographs, whereas the shape of the dental arch was determined by analysing plaster models. Results: No significant gender-related differences were found either in the shape of the maxillary central incisor that matched the shape of the maxillary dental arch (p = 0.349) or in the shape of the dental arch that matched the shape of the face (p = 0.697). However, a significant difference was noted in the shape of the teeth that matched the shape of the face (p = 0.043), which was more significantly impaired in men. In addition, the matching of the mid-face and the mid-dental arch was significantly greater in women (p = 0.016). Conclusions: The modified Williams theory was confirmed in most subjects, thus it can be considered a relevant guideline when determining the shape of teeth after their loss. The highest percentage of matching in both sexes was with the shape of the face and dental arch. There was no positive correlation between the middle of the maxillary and mandibular dental arch in most cases.
A Comprehensive Overview of the Past, Current, and Future Randomized Controlled Trials in Hepatic Encephalopathy
Authors: Ilie Ovidiu-Dumitru , Duta Raluca , Nita Ilinca-Bianca , Dobrin Irina , Gurzu Irina-Luciana , Girleanu Irina , Huiban Laura , Muzica Cristina , Ciobica Alin , Popescu Roxana , Cianga Petru , Stanciu Carol , Cimpoesu Diana , Trifan Anca
Published: December 2023

Background: Hepatic encephalopathy (HE) caused by cirrhosis has severe consequences on an individual’s lifespan, leading to long-term liver complications and potentially life-threatening outcomes. Despite recent interest in this condition, the effectiveness of secondary prophylaxis involving rixafimin, lactulose, or L-ornithine L-aspartate (LOLA) may be hindered by the unique microbial profiles each patient possesses. Methods: Thus, in this manuscript, we aimed to search, identify, and gather all randomized controlled trials (RCTs) published between 2000–2023 (November) in four major academic databases such as PubMed, ISI Web of Science, Scopus, and ScienceDirect by using a controlled terminology and web strings that reunite six main keywords. We complementarily retrieved data on the ongoing RCTs. Results: Regardless of the relatively high number of results displayed (n = 75), 46.66% (n = 35) were initially deemed eligible after the first evaluation phase after removing duplicates, n = 40 (53.34%). At the second assessment stage, we eliminated 11.42% (n = 4) studies, of which n = 22 finally met the eligibility criteria to be included in the main body of the manuscript. In terms of RCTs, otherwise found in distinct stages of development, n = 3 target FMT and n = 1 probiotics. Conclusions: Although we benefit from the necessary information and technology to design novel strategies for microbiota, only probiotics and synbiotics have been extensively studied in the last decade compared to FMT.
Atopic Dermatitis and the Risk of Infection in End-Stage Renal Disease
Authors: Momin Rushan I. , Baer Stephanie L. , Waller Jennifer L. , Young Lufei , Tran Sarah , Taskar Varsha , Bollag Wendy B.
Published: December 2023

Background and Objectives: Atopic dermatitis (AD), also known as eczema, is a common chronic inflammatory skin condition affecting 16.5 million adults in the United States. AD is characterized by an impaired epidermal barrier that can predispose individuals to infection. End-stage renal disease (ESRD) is also commonly complicated by infections due to chronic vascular access and immune-system dysfunction, possibly related to uremia. Multiple studies have reported that renal disease is a common comorbidity in adults with atopic dermatitis. The aim of this study was to determine whether AD is a risk factor for certain infections in patients with ESRD. Materials and Methods: Using the United States Renal Data System, a retrospective cohort analysis was conducted on adult ESRD patients initiating dialysis between 2004 and 2019 to investigate associations between infections and AD in this population. Results: Of 1,526,266 patients, 2290 were identified with AD (0.2%). Infectious outcomes of interest were bacteremia, septicemia, cellulitis, herpes zoster, and conjunctivitis. In all infectious outcomes except for conjunctivitis, patients with the infectious outcomes were more likely to carry a diagnosis of AD. After controlling for demographic and clinical covariates, AD was associated with an increased risk of cellulitis (adjusted relative risk (aRR) = 1.39, 95% confidence interval (CI) = 1.31–1.47) and herpes zoster (aRR = 1.67, CI = 1.44–1.94), but not with bacteremia (aRR = 0.96, CI = 0.89–1.05), septicemia (aRR = 1.02, CI = 0.98–1.08), or conjunctivitis (aRR = 0.97, CI = 0.740–1.34). Conclusions: Overall, after controlling for demographic and clinical covariates and adjusting for person-years-at-risk, AD was associated with an increased risk for some, but not all, infections within the population of patients with ESRD.
The Effect of Deformation Temperature on the Yield Stress of Ultrafine-Grained Al-Cu-Zr Alloy Containing Grain Boundary Nanoprecipitates
Authors: Gutkin Mikhail Yu. , Orlova Tatiana S. , Skiba Nikolai V.
Published: December 2023

A theoretical model is suggested that describes the effect of deformation temperature on the yield stress of an ultrafine-grained (UFG) Al-Cu-Zr alloy structured with severe plastic deformation. Within the model, nanoprecipitates (NPs) of Al2Cu act as sources of lattice dislocations in the presence of a number of extrinsic grain-boundary dislocations (EGBDs) near the NPs. It is shown that the number of EGBDs near the NPs decreases with a drop in the deformation temperature that increases the yield stress of the Al-Cu-Zr alloy. The proposed model is in good quantitative agreement with available experimental results.
The Influence of Reagents on the Shape, Stability, and Toxicity of AgNPs and Their Use to Produce Polymer-AgNPs Composites
Authors: Velgosova Oksana , Mačák Lívia , Mára Vladimír , Múdra Erika , Vojtko Marek , Lisnichuk Maksym , Čižmárová Elena
Published: December 2023

The aim of this work was to propose a simple method for synthesizing differently shaped AgNPs and to find a suitable stabilizing/capping agent to ensure the non-toxicity of AgNPs. Using a chemical method, by simply changing the volume of reducing agents, we successfully prepared colloids of differently shaped AgNPs (spherical (~10 nm), triangular (~40 nm), rodlike (~30 nm), and a mixture of these shapes). The nanoparticle sizes and shapes affect the solution color. UV-VIS spectroscopy was used to evaluate the colloidal solutions, and transmission electron microscopy was used to analyze the shape and size of the nanoparticles. To create non-toxic and stable AgNPs, it is necessary to modify the surface properties of the nanoparticles; one possibility is to create a biocompatible layer on the nanoparticle surface. We successfully applied a combination of trisodium citrate and polyvinylpyrrolidone, thereby preventing the release of silver ions, which are responsible for the toxic effects of AgNPs. The synthesized nanoparticles show very low, mostly negligible antibiofilm activity against the green algae Chlorella kessleri. AgNPs were used to prepare polymer-AgNP composite thin layers and fibers. It was proved that AgNPs can influence polymer matrix properties.
Using Ground- and Drone-Based Surface Emission Monitoring (SEM) Data to Locate and Infer Landfill Methane Emissions
Authors: Abichou Tarek , Bel Hadj Ali Nizar , Amankwah Sakina , Green Roger , Howarth Eric S.
Published: December 2023

Ground- and drone-based surface emission monitoring (SEM) campaigns were performed at two municipal solid waste landfills, during the same week as mobile tracer correlation method (TCM) testing was used to measure the total methane emissions from the same landfills. The G-SEM and the D-SEM data, along with wind data, were used as input into an inverse modeling approach combined with an optimization-based methane emission estimation method (implemented in a tool called SEM2Flux). This approach involves the use of backward dispersion modeling to estimate the whole-site methane emissions from a given landfill and the identification of locations and emission rates of major leaks. SEM2Flux is designed to exploit the measured surface methane concentration concurrently with wind data and tackle two problems: (1) inferring the estimates of methane rates from individual landfills, and (2) identifying the likely locations of the main emission sources. SEM2Flux results were also compared with emission estimates obtained using TCM. In Landfill B, the average TCM-measured methane emissions was 1178 Kg/h, with a standard deviation of 271 Kg/h. In Landfill C, the average TCM-measured emission rate was 601 Kg/h, with a standard deviation of 292 Kg/h. For both landfills, the D-SEM data yielded statistically similar estimates of methane emissions as the TCM-measured emissions. On the other hand, the G-SEM data yielded comparable estimates of emissions to TCM-measured emissions only for Landfill C, where the D-SEM and G-SEM data were statistically not different. The results of this study showcase the ability of this method using surface concentrations to provide a rapid and simple estimation of fugitive methane emissions from landfills. Such an approach can also be used to assess the effectiveness of different remedial actions in reducing fugitive methane emissions from a given landfill.
Characterization of Lactococcus lactis 11/19-B1 Isolated from Kiwi Fruit as a Potential Probiotic and Paraprobiotic
Authors: Ishioka Ken , Miyazaki Nozomu , Nishiyama Kyoko , Suzutani Tatsuo
Published: December 2023

Probiotics are live bacteria used as food additives that are beneficial to human health. Lactococcus lactis 11/19-B1 strain isolated from kiwi fruit stimulates innate immunity in silkworms. Intake of yogurt containing the living 11/19-B1 strain significantly decreases the level of low-density lipoproteins (LDLs) in high-LDL volunteers and improves atopic dermatitis in humans. In this study, the probiotic properties of the 11/19-B1 strain, such as sensitivity to antimicrobial compounds, biogenic amine production, some virulence genes for human health, antimicrobial activity, tolerance to gastric acid and bile acids, and ability to adhere to the intestinal mucosa, were evaluated. The 11/19-B1 strain did not show resistance to the tested antimicrobial compounds except cefoxitin and fosfomycin. In addition, no production of amines that can harm humans, the antimicrobial activity required for probiotics, and the absence of adhesion to Caco-2 cells suggest that it is unlikely to attach to the intestinal epithelium. The 11/19-B1 strain grew in 0.3% but not in 1% bile salt. In the presence of 2% skim milk, the survival rate of the 11/19-B1 strain under simulated gastrointestinal tract conditions was 67% even after 4 h. These results indicate that the 11/19-B1 strain may function as a probiotic or paraprobiotic to be utilized in the food industry.
pH-Related Changes in Soil Bacterial Communities in the Sanjiang Plain, Northeast China
Authors: Wang Mingyu , Pu Wenmiao , Wang Shenzheng , Zeng Xiannan , Sui Xin , Wang Xin
Published: December 2023

Soil bacteria are crucial components of terrestrial ecosystems, playing an important role in soil biogeochemical cycles. Although bacterial community diversity and composition are regulated by many abiotic and biotic factors, how soil physiochemical properties impact the soil bacteria community diversity and composition in wetland ecosystems remains largely unknown. In this study, we used high-throughput sequencing technology to investigate the diversity and composition of a soil bacterial community, as well as used the structural equation modeling (SEM) method to investigate the relationships of the soil’s physicochemical properties (i.e., soil pH, soil organic carbon (SOC), total nitrogen (TN), ammonium nitrogen (NH4+N), electrical conductivity (EC) and nitrate nitrogen (NO3−N)), and soil bacterial community structures in three typical wetland sites in the Sanjiang Plain wetland. Our results showed that the soil physicochemical properties significantly changed the α and β-diversity of the soil bacteria communities, e.g., soil TN, NH4+N, NO3−N, and SOC were the main soil factors affecting the soil bacterial α-diversity. The soil TN and pH were the key soil factors affecting the soil bacterial community. Our results suggest that changes in soil pH indirectly affect soil bacterial communities by altering the soil nitrogenous nutrient content.
Dry Stamping Coral Powder: An Effective Method for Isolating Coral Symbiotic Actinobacteria
Authors: Becerril-Espinosa Amayaly , Mateos-Salmón Carolina , Burgos Asdrubal , Rodríguez-Zaragoza Fabián A. , Meza-Canales Iván D. , Juarez-Carrillo Eduardo , Rios-Jara Eduardo , Ocampo-Alvarez Héctor
Published: December 2023

Actinobacteria are important sources of antibiotics and have been found repeatedly in coral core microbiomes, suggesting this bacterial group plays important functional roles tied to coral survival. However, to unravel coral–actinobacteria ecological interactions and discover new antibiotics, the complex challenges that arise when isolating symbiotic actinobacteria must be overcome. Moreover, by isolating unknown actinobacteria from corals, novel biotechnological applications may be discovered. In this study, we compared actinobacteria recovery from coral samples between two widely known methods for isolating actinobacteria: dry stamping and heat shock. We found that dry stamping was at least three times better than heat shock. The assembly of isolated strains by dry stamping was unique for each species and consistent across same-species samples, highlighting that dry stamping can be reliably used to characterize coral actinobacteria communities. By analyzing the genomes of the closest related type strains, we were able to identify several functions commonly found among symbiotic organisms, such as transport and quorum sensing. This study provides a detailed methodology for isolating coral actinobacteria for ecological and biotechnological purposes.
Adsorption Behaviors of Lanthanum (III) and Yttrium (III) Ions on Gibbsite
Authors: Zhou Zongke , Wan Quan , Yu Wenbin , Nie Xin , Yang Shuguang , Yang Shuqin , Qin Zonghua
Published: December 2023

The enrichment process of rare earth elements in ion-adsorbed rare earth ores and bauxite is potentially related to the adsorption of rare earth elements by gibbsite. In this paper, lanthanum and yttrium were selected as surrogates of light rare earth elements and heavy rare earth elements, respectively. The effects of adsorption time, solution pH, and background electrolyte concentration on the adsorption of rare earth ions by gibbsite were investigated through batch adsorption experiments. The results showed that the adsorption of rare earth ions by gibbsite can approach equilibrium in 72 h. There is mainly electrostatic repulsion between gibbsite and rare earth ions at pH 4–7, and the adsorption efficiency increases with the increase in solution pH value and background electrolyte concentration. The adsorption process of rare earth ions by gibbsite is more consistent with the pseudo-second-order kinetic and Langmuir single-layer adsorption models. Moreover, based on the structural correlation between clay minerals and gibbsite, the causes for the differences in the adsorption behaviors of rare earth elements on the minerals are discussed. The results of this study help to understand the role of aluminum hydroxide in the migration and fate of rare earth elements in epigenetic environments.
The Influence of Micro-Heterogeneity on Water Injection Development in Low-Permeability Sandstone Oil Reservoirs
Authors: Li Mao , Qu Zhan , Wang Mu , Ran Wang
Published: December 2023

Micro-heterogeneity in low-permeability sandstone oil reservoirs significantly influences the uniformity of water injection during development. This leads to the formation of preferred channels for water injection, causing premature water breakthroughs in oil wells. Not only does this reduce oil displacement efficiency, but it also enriches residual oil in the formation, which ultimately impacts the overall recovery rate. This study employed various methods, including thin-section casting, qualitative analysis through scanning electron microscopy, quantitative analysis of X-ray diffraction, high-pressure mercury intrusion and particle size, and experimental techniques, such as wettability and micro-displacement, to investigate the impact mechanism of micro-heterogeneity on water injection development in low-permeability oil reservoirs. A typical low-permeability sandstone oil reservoir in the Ordos Basin was used as a case study. The results reveal that the reservoir’s micro-heterogeneity is determined by the heterogeneity of the interstitial material, porosity, and particle size. Micro-heterogeneity plays a critical role in the flow characteristics and oil displacement efficiency of low-permeability oil reservoirs. The less the micro-heterogeneity, the better the water injection development outcome. This study suggests a technical policy adjustment method that is critical for guiding the development of low-permeability water injection oil reservoirs, thereby improving the effectiveness of water injection development.
Chronological and Mineralogical Records of the Langqi Pluton, Fuzhou: Constraints on the Magma Mixing Process
Authors: Chen Zhouxin , Wang Liyuan , Yan Xue
Published: December 2023

The mafic microgranular enclaves (MMEs) from Mesozoic intermediate-acid magmatic rocks, widely developed along the Fujian coast, are considered to be the results of large-scale crust–mantle interaction by magma mixing. This paper is based on zircon U-Pb chronology, along with zircon Hf isotope and mineral analyses for the host granite and MMEs from Langqi Island, in order to investigate the magma mixing mechanism of the Langqi pluton in Fuzhou, Southeast China. The results indicate that the MMEs were emplaced during the late Early Cretaceous (98.9 ± 2.2 Ma), identical to the age of the granite (100.1 ± 1.1 Ma) within the error range. The zircon εHf(t) values for the granite and MMEs are in the ranges of −2.1~0.0 and −1.7~+1.1. The zircon Hf isotope data indicate that both the granite and MMEs were predominantly derived from the ancient crustal basement of Cathaysia, with a partial mantle-derived contribution. The An values of plagioclase phenocrysts with oscillatory zoning patterns in the MMEs show oscillatory changes from the core to the rim, indicating multiple mixing events between the two magmas with different compositions. Amphiboles in the MMEs show characteristics of crust–mantle contamination, and the Ti migrated from the mafic magma with high concentration to the felsic magma with low concentration during the magma mixing process. Biotites in the host rock and MMEs belong to primary biotite, and they have relatively high MgO contents (ave. 12.78 wt.%) and relatively low FeOT/(MgO + FeOT) ratios (ave. 0.56), showing characteristics of crust–mantle contamination. The crust–mantle magma interaction in a crystal, mushy state played a significant role in controlling the formation and evolution of the Langqi pluton. The magmatism was predominantly sourced from mixing between the mantle-derived mafic magma and the crust-derived felsic magma during the subduction of the Paleo-Pacific Plate, resulting in the formation of the Langqi doleritic veins, granites, and MMEs.
Gravity Data Enhancement Using the Exponential Transform of the Tilt Angle of the Horizontal Gradient
Authors: Pham Luan Thanh , Oliveira Saulo Pomponet , Le Cuong Van Anh , Bui Nhung Thi , Vu An Hoa , Nguyen Duong Anh
Published: December 2023

Detecting the boundaries of geologic structures is one of the main tasks in interpreting gravity anomalies. Many methods based on the derivatives of gravity anomalies have been introduced to map the source boundaries. The drawbacks of traditional methods are that the estimated boundaries are divergent or false boundaries appear in the output map. Here, we use the exponential transform of the tilt angle of the horizontal gradient to improve the edge detection results. The robustness of the presented method is illustrated using synthetic data and real examples from the Voisey’s Bay Ni-Cu-Co deposit (Canada) and the Tuan Giao (Vietnam). The findings show that the presented technique can produce more precise and clear boundaries.
On-Chip Integration of a Plasmonic FET Source and a Nano-Patch Antenna for Efficient Terahertz Wave Radiation
Authors: Crabb Justin , Cantos-Roman Xavier , Aizin Gregory , Jornet Josep Miquel
Published: December 2023

Graphene-based Field-Effect Transistors (FETs) integrated with microstrip patch antennas offer a promising approach for terahertz signal radiation. In this study, a dual-stage simulation methodology is employed to comprehensively investigate the device’s performance. The initial stage, executed in MATLAB, delves into charge transport dynamics within a FET under asymmetric boundary conditions, employing hydrodynamic equations for electron transport in the graphene channel. Electromagnetic field interactions are modeled via Finite-Difference Time-Domain (FDTD) techniques. The second stage, conducted in COMSOL Multiphysics, focuses on the microstrip patch antenna’s radiative characteristics. Notably, analysis of the S11 curve reveals minimal reflections at the FET’s resonant frequency of 1.34672 THz, indicating efficient impedance matching. Examination of the radiation pattern demonstrates the antenna’s favorable directional properties. This research underscores the potential of graphene-based FETs for terahertz applications, offering tunable impedance matching and high radiation efficiency for future terahertz devices.
Efficient Degradation of Sulfamethoxazole by Diatomite-Supported Hydroxyl-Modified UIO-66 Photocatalyst after Calcination
Authors: Liu Hui-Lai , Zhang Yu , Lv Xin-Xin , Cui Min-Shu , Cui Kang-Ping , Dai Zheng-Liang , Wang Bei , Weerasooriya Rohan , Chen Xing
Published: December 2023

Sulfamethoxazole (SMX) is a widely used antibiotic to treat bacterial infections prevalent among humans and animals. SMX undergoes several transformation pathways in living organisms and external environments. Therefore, the development of efficient remediation methods for treating SMX and its metabolites is needed. We fabricated a photo-Fenton catalyst using an UIO-66 (Zr) metal–organic framework (MOF) dispersed in diatomite by a single-step solvothermal method for hydroxylation (HO-UIO-66). The HO-UIO-66-0/DE-assisted Fenton-like process degraded SMX with 94.7% efficiency; however, HO-UIO-66 (Zr) is not stable. We improved the stability of the catalyst by introducing a calcination step. The calcination temperature is critical to improving the catalytic efficiency of the composite (for example, designated as HO-UIO-66/DE-300 to denote hydroxylated UIO-66 dispersed in diatomite calcined at 300 °C). The degradation of SMX by HO-UIO-66/DE-300 was 93.8% in 120 min with 4 mmol/L H2O2 at pH 3 under visible light radiation. The O1s XPS signatures signify the stability of the catalyst after repeated use for SMX degradation. The electron spin resonance spectral data suggest the role of h+, •OH, •O2−, and 1O2 in SMX degradation routes. The HO-UIO-66/DE-300-assisted Fenton-like process shows potential in degrading pharmaceutical products present in water and wastewater.