bluuebunny/crossref_metadata_2025 huggingface dataset:
Impact of Column Support Stiffness on the Mechanical Performance of Flat Frame Structural Systems Supporting Thin-Walled Folded Roofs
Authors: Abramczyk Jacek , Chrzanowska Katarzyna
Published: December 2024

This article presents a new parametric method for shaping flat transverse frame structural systems supporting thin-walled roofs made of flat sheets folded unidirectionally and transformed elastically to various shell forms. The parameterization was limited to one independent variable, that is the stiffness of the support joints. For different discrete values of simulated stiffness, the surface areas of the cross sections of the tensile and compressed elements and the section modulus of the bending elements were calculated so as to obtain the optimized work of the frame and its elements in the assumed load environment. The developed method allows for optimizing the work of frames considered as flat bar structural systems of building halls, taking into account the ultimate and serviceability limit states. The operation of the method is illustrated with an example concerning the formation of a flat frame working under a load characteristic for buildings located in a lowland area in a moderate climate. The authors intend to successively extend the method with new types of frame systems so as to obtain increasingly accurate and universal models defined by means of an increasing number of independent variables. These parameters are related to different forms and inclinations of columns and girders, and different external load types. The successive increase in the parameters defining the computational parametric model of the frame requires the use of increasingly advanced artificial intelligence algorithms to describe the static and strength performance of the buildings shaped, which makes the proposed method universal and the created structural systems effective in various external environments.
Effect of Si Addition on Structure and Corrosion Resistance of FeCoNiCr High-Entropy Alloy Coating
Authors: Li Wenqiang , Lian Jie , Wang Dengfeng , Zhang Suo , Han Chengfu , Du Zhenyu , Li Fushan
Published: December 2024

In this study, Fe60Co10−xNi15Cr15Six (x = 0, 4, and 8) powders were successfully prepared using the aerosol method and employed to produce high-entropy coatings on Q235 steel via laser cladding. The microstructure and phase composition of the coatings were analyzed using scanning electron microscopy, energy-dispersive X-ray spectroscopy, and X-ray diffraction. Corrosion resistance and potential were evaluated through electrochemical analysis and Kelvin probe force microscopy. The results show that the Fe60Co10−xNi15Cr15Six coatings exhibit excellent metallurgical bonding with no visible porosity or cracks. The coating primarily consists of an FCC structure; however, as the Si content increases, the structure transitions to a mixed FCC + BCC phase. The addition of Si also refines the grain size in the alloy system. Electrochemical analysis reveals that the Si0 and Si4 coatings exhibit similar corrosion behavior, while the Si8 coating shows a significant drop in corrosion potential, reducing its corrosion resistance. As the Si content increases, grain refinement leads to more grain boundaries, but the corrosion resistance decreases due to the lower corrosion performance of Si compared to Co. Considering both cost and corrosion resistance, the Si4 coating offers a balance of low cost and excellent corrosion resistance.
A Novel and Efficient Iterative Approach to Approximating Solutions of Fractional Differential Equations
Authors: Filali Doaa , Eljaneid Nidal H. E. , Alatawi Adel , Alshaban Esmail , Ali Montaser Saudi , Khan Faizan Ahmad
Published: December 2024

This study presents a novel and efficient iterative approach to approximating the fixed points of contraction mappings in Banach spaces, specifically approximating the solutions of nonlinear fractional differential equations of the Caputo type. We establish two theorems proving the stability and convergence of the proposed method, supported by numerical examples and graphical comparisons, which indicate a faster convergence rate compared to existing methods, including those by Agarwal, Gursoy, Thakur, Ali and Ali, and D∗∗. Additionally, a data dependence result for approximate operators using the proposed method is provided. This approach is applied to achieve the solutions for Caputo-type fractional differential equations with boundary conditions, demonstrating the efficacy of the method in practical applications.
Complete Homogeneous Symmetric Polynomials with Repeating Variables
Authors: González-Serrano Luis Angel , Maximenko Egor A.
Published: December 2024

In this paper, we consider complete homogeneous symmetric polynomials evaluated for variables repeated with given multiplicities; in other words, we consider polynomials obtained from complete homogeneous polynomials by identifying some subsets of their variables. We represent such polynomials as linear combinations of the powers of the variables, where all exponents are equal to the degree of the original polynomial. We give two proofs for the proposed formulas: the first proof uses the decomposition of the generating function into partial fractions, and the second involves the inverse of the confluent Vandermonde matrix. We also discuss the computational feasibility of the proposed formulas.
Sensitivity Analysis of MTPA Control to Angle Errors for Synchronous Reluctance Machines
Authors: Petrun Martin , Černelič Jernej
Published: December 2024

This study investigated the sensitivity of maximum torque per ampere (MTPA) control in synchronous reluctance machines (SynRMs) to angle errors, examining specifically how deviations in the reference control trajectory affected performance. Analytical and numerical methods were employed to analyze this sensitivity systematically, including the impact of magnetic saturation. Two MTPA control implementation schemes were evaluated, with torque and current amplitude as the reference variables, using a template SynRM from the open-source simulation tool SyR-e. The results indicated that performance sensitivity to angle errors was moderately low near the MTPA trajectory, allowing for significant angle deviations with minimal performance loss. Although magnetic saturation increased this sensitivity slightly, reducing the allowable error range by up to 25%, the maximum angle deviation for up to 1% of the performance decrease still corresponded to approximately ±3∘ around the MTPA trajectory. The findings of this study suggest potential for simplifying control implementations, reducing component costs through less precise position determination (sensor-based or sensorless), and achieving additional control objectives such as torque ripple reduction.
An Advanced Time-Varying Capital Asset Pricing Model via Heterogeneous Autoregressive Framework: Evidence from the Chinese Stock Market
Authors: Zhao Bohan , Yin Hong , Long Yonghong
Published: December 2024

The capital asset pricing model (CAPM) is a foundational asset pricing model that is widely applied and holds particular significance in the globally influential Chinese stock market. This study focuses on the banking sector, enhancing the performance of the CAPM and further assessing its applicability within the Chinese stock market context. This study incorporates a heterogeneous autoregressive (HAR) component into the CAPM framework, developing a CAPM-HAR model with time-varying beta coefficients. Empirical analysis based on high-frequency data demonstrates that the CAPM-HAR model not only enhances the capability of capturing market fluctuations but also significantly improves its applicability and predictive accuracy for stocks in the Chinese banking sector.
A New Fault Diagnosis Method for Rolling Bearings with the Basis of Swin Transformer and Generalized S Transform
Authors: Yan Jin , Zhu Xu , Wang Xin , Zhang Dapeng
Published: December 2024

In view of the rolling bearing fault signal non-stationarity, strong noise can lead to low fault diagnosis accuracy. A Swin Transformer and generalized S Transform fault diagnosis method is proposed to solve the problems of difficult signal feature extraction and low diagnostic accuracy. Generalized S transform is used to improve the resolution of bearing fault signals, the Swin Transformer model is used to master the shallow weight required for identifying rolling bearing faults for highly fault characteristic expression signals, and the deep weight is obtained by backpropagation training. Finally, the extracted features are input into the improved Softmax classifier for fault classification. The various signal processing methods for the bearing signal processing ability are compared, and this model’s diagnosis ability and the ability to resist noise are verified. The experimental results show that the method has a remarkable ability and an accuracy of above 90% in the anti-noise test and also has a good robustness.
Deep Reinforcement Learning Algorithm with Long Short-Term Memory Network for Optimizing Unmanned Aerial Vehicle Information Transmission
Authors: He Yufei , Hu Ruiqi , Liang Kewei , Liu Yonghong , Zhou Zhiyuan
Published: December 2024

The optimization of information transmission in unmanned aerial vehicles (UAVs) is essential for enhancing their operational efficiency across various applications. This issue is framed as a mixed-integer nonconvex optimization challenge, which traditional optimization algorithms and reinforcement learning (RL) methods often struggle to address effectively. In this paper, we propose a novel deep reinforcement learning algorithm that utilizes a hybrid discrete–continuous action space. To address the long-term dependency issues inherent in UAV operations, we incorporate a long short-term memory (LSTM) network. Our approach accounts for the specific flight constraints of fixed-wing UAVs and employs a continuous policy network to facilitate real-time flight path planning. A non-sparse reward function is designed to maximize data collection from internet of things (IoT) devices, thus guiding the UAV to optimize its operational efficiency. Experimental results demonstrate that the proposed algorithm yields near-optimal flight paths and significantly improves data collection capabilities, compared to conventional heuristic methods, achieving an improvement of up to 10.76%. Validation through simulations confirms the effectiveness and practicality of the proposed approach in real-world scenarios.
Multiplicity Results of Solutions to the Fractional p-Laplacian Problems of the Kirchhoff–Schrödinger–Hardy Type
Authors: Kim Yun-Ho
Published: December 2024

This paper is devoted to establishing multiplicity results of nontrivial weak solutions to the fractional p-Laplacian equations of the Kirchhoff–Schrödinger type with Hardy potentials. The main features of the paper are the appearance of the Hardy potential and nonlocal Kirchhoff coefficients, and the absence of the compactness condition of the Palais–Smale type. To demonstrate the multiplicity results, we exploit the fountain theorem and the dual fountain theorem as the main tools, respectively.
Exploring the 2-Part of Class Groups in Quadratic Fields: Perspectives on the Cohen–Lenstra Conjectures
Authors: Wang Yong , Zhang Huili , Zhou Ying , Deng Haopeng , Li Lingyue
Published: December 2024

Cohen and Lenstra introduced conjectures concerning the distribution of class numbers in quadratic fields, though many of these conjectures remain unproven. This paper investigates the 2-part of class groups in imaginary quadratic fields and examines their alignment with the Cohen–Lenstra heuristics. We provide detailed proofs of key theorems related to ideal decompositions and modular homomorphisms, and we explore the distribution of class groups of imaginary quadratic fields. Our analysis includes constructing imaginary quadratic fields with prescribed 2-class groups and discussing the implications of these findings on the Cohen–Lenstra conjecture.
Noether’s Problem for p-Groups with Abelian Normal Subgroups and Central p-Powers
Authors: Michailov Ivo M. , Dimitrov Ivailo A.
Published: December 2024

This paper addresses Noether’s problem for p-groups G, having an abelian normal subgroup of index p, under the condition Gp={gp:g∈G}≤Z(G)—the center of G. We prove that the fixed field K(G)=K(x(g):g∈G)G is rational over K in such cases, focusing on both the classification and structural analysis of these groups. Our results extend existing work by removing restrictive assumptions and providing a refined understanding of p-groups and their representations.
Gradient Method with Step Adaptation
Authors: Krutikov Vladimir , Tovbis Elena , Gutova Svetlana , Rozhnov Ivan , Kazakovtsev Lev
Published: December 2024

The paper solves the problem of constructing step adjustment algorithms for a gradient method based on the principle of the steepest descent. The expansion of the step adjustment principle, its formalization and parameterization led the researchers to gradient-type methods with incomplete relaxation or over-relaxation. Such methods require only the gradient of the function to be calculated at the iteration. Optimization of the parameters of the step adaptation algorithms enables us to obtain methods that significantly exceed the steepest descent method in terms of convergence rate. In this paper, we present a universal step adjustment algorithm that does not require selecting optimal parameters. The algorithm is based on orthogonality of successive gradients and replacing complete relaxation with some degree of incomplete relaxation or over-relaxation. Its convergence rate corresponds to algorithms with optimization of the step adaptation algorithm parameters. In our experiments, on average, the proposed algorithm outperforms the steepest descent method by 2.7 times in the number of iterations. The advantage of the proposed methods is their operability under interference conditions. Our paper presents examples of solving test problems in which the interference values are uniformly distributed vectors in a ball with a radius 8 times greater than the gradient norm.
Exploring the Pharmacological Potential of Carrageenan Disaccharides as Antitumor Agents: An In Silico Approach
Authors: Silva Ohana Leticia Tavares , Alves Monique Gabriela das Chagas Faustino , Rocha Hugo Alexandre Oliveira
Published: December 2024

Carrageenans have demonstrated enhanced antitumor activity upon depolymerization into disaccharides. However, the pharmacological viability of these disaccharides and their mechanisms of antitumor action remains to be fully elucidated. This study aimed to employ computational tools to investigate the pharmacological properties and molecular targets pertinent to cancer of the disaccharides derived from the primary carrageenans. Analyses of pharmacological properties predicted by the pkCSM and SwissADME servers indicated that the disaccharides possess a favorable pharmacokinetic profile, although they encounter permeability challenges primarily due to their high polarity and low lipophilicity. Target prediction using SwissTarget and PPB2 identified five carbonic anhydrases, which are also targets of oncology drugs, as common targets for the disaccharides. Molecular docking performed with AutoDock Vina revealed that the binding energies of the disaccharides with carbonic anhydrases were comparable to or greater than those of existing drugs that target these lyases. Notably, six of the complexes formed exhibited interactions between the disaccharides and the zinc cofactor, which represents a primary mechanism of inhibition for these targets. Furthermore, molecular dynamics simulations conducted using GROMACS demonstrated a stable interaction between the disaccharides and carbonic anhydrases. These findings offer new insights into the pharmacological properties and mechanisms of action of carrageenan-derived disaccharides, highlighting their potential for further exploration in clinical trials and experimental studies.
Using the Cardiac–Electrophysiological Balance Index to Predict Arrhythmia Risk After Colonoscopy
Authors: Polatkan Seyit Ali Volkan , Gunay-Polatkan Seyda , Isik Ozgen , Sigirli Deniz
Published: December 2024

Background and Objectives: Colorectal cancer is the second leading cause of cancer-related deaths in the U.S., and colonoscopy is a critical tool for colon cancer screening and diagnosis. Electrolyte disturbances and autonomic nervous system dysfunction that may occur due to bowel preparation and the colonoscopy procedure itself may play a role in the development of cardiac arrhythmia. This study aimed to assess the index of cardiac–electrophysiological balance (iCEB) to predict ventricular arrhythmia risk related to colonoscopy. Materials and Methods: Patients undergoing elective colonoscopy with a normal sinus rhythm were included. Electrocardiography (ECG) recordings both before bowel preparation and after the colonoscopy procedure were obtained. Values of the index of cardiac–electrophysiological balance (iCEB) were compared. Results: Among 36 patients, it was determined that the heart rate values of the patients before bowel preparation were higher than the heart rate values after colonoscopy [74.5 (60–108) bpm vs. 68.5 (53–108) bpm, p = 0.021]. The duration of QT interval increased (370.9 ± 27.8 ms vs. 398.7 ± 29.4 ms, p < 0.001) and the iCEB increased from 4.1 ± 0.5 to 4.5 ± 0.6 (p < 0.001), indicating a significant post-procedural risk of ventricular arrhythmias. Conclusions: These findings suggest that routine iCEB assessment post-colonoscopy could identify high-risk patients requiring closer monitoring.
The Potential of SHAP and Machine Learning for Personalized Explanations of Influencing Factors in Myopic Treatment for Children
Authors: Chen Jun-Wei , Chen Hsin-An , Liu Tzu-Chi , Wu Tzu-En , Lu Chi-Jie
Published: December 2024

Background and Objectives: The rising prevalence of myopia is a significant global health concern. Atropine eye drops are commonly used to slow myopia progression in children, but their long-term use raises concern about intraocular pressure (IOP). This study uses SHapley Additive exPlanations (SHAP) to improve the interpretability of machine learning (ML) model predicting end IOP, offering clinicians explainable insights for personalized patient management. Materials and Methods: This retrospective study analyzed data from 1191 individual eyes of 639 boys and 552 girls with myopia treated with atropine. The average age of the whole group was 10.6 ± 2.5 years old. The refractive error of spherical equivalent (SE) in myopia degree was base SE at 2.63D and end SE at 3.12D. Data were collected from clinical records, including demographic information, IOP measurements, and atropine treatment details. The patients were divided into two subgroups based on a baseline IOP of 14 mmHg. ML models, including Lasso, CART, XGB, and RF, were developed to predict the end IOP value. Then, the best-performing model was further interpreted using SHAP values. The SHAP module created a personalized and dynamic graphic to illustrate how various factors (e.g., age, sex, cumulative duration, and dosage of atropine treatment) affect the end IOP. Results: RF showed the best performance, with superior error metrics in both subgroups. The interpretation of RF with SHAP revealed that age and the recruitment duration of atropine consistently influenced IOP across subgroups, while other variables had varying effects. SHAP values also offer insights, helping clinicians understand how different factors contribute to predicted IOP value in individual children. Conclusions: SHAP provides an alternative approach to understand the factors affecting IOP in children with myopia treated with atropine. Its enhanced interpretability helps clinicians make informed decisions, improving the safety and efficacy of myopia management. This study demonstrates the potential of combining SHAP with ML models for personalized care in ophthalmology.
The Impact of the Metabolic Syndrome Severity on the Appearance of Primary and Permanent DNA Damage
Authors: Milić Mirta , Kazensky Luka , Matovinović Martina
Published: December 2024

The prevalence of metabolic syndrome (MetS) worldwide is rapid and significant on a global scale. A 2022 meta-analysis of data from 28 million individuals revealed a global prevalence of 45.1%, with notably higher rates in the Eastern Mediterranean Region and the Americas, particularly in high-income countries. MetS is associated with impaired antioxidant defense mechanisms, resulting in the excessive generation of reactive oxygen and nitrogen species (RONS) and elevated levels of DNA damage. Unrepaired damage can lead to DNA base changes, chromosomal mutations, genomic loss and instability, and disrupted gene and protein expression. Such changes contribute to an increased risk of tumorigenesis, cancer progression, and mortality. The alkaline comet and micronucleus cytome assay are commonly used assays for DNA damage evaluation. The estimation of damage with those two techniques demonstrated the link between the increased risk of cancer and mortality. Incorporating these techniques in a set of biomarkers to assess the MetS severity holds promise; however, comprehensive literature reviews featuring large-scale studies integrating both assays remain scarce. This systematic review aims to integrate and critically evaluate the existing scientific literature regarding this topic.
Carbon Nanofiber-Reinforced Carbon Black Support for Enhancing the Durability of Catalysts Used in Proton Exchange Membrane Fuel Cells Against Carbon Corrosion
Authors: Sung Minki , Yi Hyeonseok , Han Jimin , Lee Jong Beom , Yoon Seong-Ho , Park Joo-Il
Published: December 2024

This study addresses the critical challenge of carbon corrosion in proton exchange membrane fuel cells (PEMFCs) by developing hybrid supports that combine the high surface area of carbon black (CB) with the superior crystallinity and graphitic structure of carbon nanofibers (CNFs). Two commercially available CB samples were physically activated and composited with two types of CNFs synthesized via chemical vapor deposition using different carbon sources. The structure, morphology, and crystallinity of the resulting CNF–CB hybrid supports were characterized, and the performances of these hybrid supports in mitigating carbon corrosion and enhancing the PEMFC performance was evaluated through full-cell testing in collaboration with a membrane electrode assembly (MEA) manufacturer (VinaTech, Seoul, Republic, of Korea), adhering to industry-standard fabrication and evaluation procedures. Accelerated stress tests following the US Department of Energy protocols revealed that incorporating CNFs enhanced the durability of the CB-based hybrid supports without compromising their performance. The improved performance of the MEAs with the hybrid carbon support is attributed to the ability of the CNF to act as a structural backbone, facilitate water removal, and provide abundant edge plane sites for anchoring the platinum catalyst, which promoted the oxygen reduction reaction and improved catalyst utilization. The findings of this study highlight the potential of CNF-reinforced CB supports for enhancing the durability and performance of PEMFCs.
Determination of Diffusion Coefficients of Nickel and Vanadium into Stainless and Duplex Steel and Titanium
Authors: Vávrová Šárka , Švec Martin , Moravec Jaromír , Klápště Daniel
Published: December 2024

When heterogeneous joints are created, problems with the formation of intermetallic phases arise. There are various ways to reduce the formation of intermetallics. One of the ways that is discussed in this article is to use a suitable interlayer of appropriate thickness when forming the joint. A too-thin interlayer does not protect against the formation of brittle intermetallic phases. On the other hand, a too-thick interlayer increases the heterogeneity of the joint and, thus, decreases its useful properties. Within this paper, the formation of diffusion joints between the base material (AISI 304 steel, duplex steel, AISI 316L steel, or titanium grade 2) and the 0.2 mm thick intermediate layer (nickel or vanadium) was studied. Initial diffusion joints were prepared in a Gleeble 3500 machine, and samples for the study of diffusion kinetics were subsequently heat-treated in a vacuum furnace. The result of the research was the determination of specific diffusion parameters of nickel and vanadium into all four tested base materials. The initial diffusion depth (simple heating to the target temperature without holding at this temperature) of nickel was 4.46 µm into duplex steel and 5.48 µm into Ti Gr. 2 at 950 °C. At the same temperature, the initial diffusion depth of vanadium was 14.54 µm into duplex steel and 14.32 µm into Ti Gr. 2. In addition, general equations for the calculation of diffusion coefficients for the mentioned materials in the temperature range of 850 to 1150 °C were established.
Sparse Convolution FPGA Accelerator Based on Multi-Bank Hash Selection
Authors: Xu Jia , Pu Han , Wang Dong
Published: December 2024

Reconfigurable processor-based acceleration of deep convolutional neural network (DCNN) algorithms has emerged as a widely adopted technique, with particular attention on sparse neural network acceleration as an active research area. However, many computing devices that claim high computational power still struggle to execute neural network algorithms with optimal efficiency, low latency, and minimal power consumption. Consequently, there remains significant potential for further exploration into improving the efficiency, latency, and power consumption of neural network accelerators across diverse computational scenarios. This paper investigates three key techniques for hardware acceleration of sparse neural networks. The main contributions are as follows: (1) Most neural network inference tasks are typically executed on general-purpose computing devices, which often fail to deliver high energy efficiency and are not well-suited for accelerating sparse convolutional models. In this work, we propose a specialized computational circuit for the convolutional operations of sparse neural networks. This circuit is designed to detect and eliminate the computational effort associated with zero values in the sparse convolutional kernels, thereby enhancing energy efficiency. (2) The data access patterns in convolutional neural networks introduce significant pressure on the high-latency off-chip memory access process. Due to issues such as data discontinuity, the data reading unit often fails to fully exploit the available bandwidth during off-chip read and write operations. In this paper, we analyze bandwidth utilization in the context of convolutional accelerator data handling and propose a strategy to improve off-chip access efficiency. Specifically, we leverage a compiler optimization plugin developed for Vitis HLS, which automatically identifies and optimizes on-chip bandwidth utilization. (3) In coefficient-based accelerators, the synchronous operation of individual computational units can significantly hinder efficiency. Previous approaches have achieved asynchronous convolution by designing separate memory units for each computational unit; however, this method consumes a substantial amount of on-chip memory resources. To address this issue, we propose a shared feature map cache design for asynchronous convolution in the accelerators presented in this paper. This design resolves address access conflicts when multiple computational units concurrently access a set of caches by utilizing a hash-based address indexing algorithm. Moreover, the shared cache architecture reduces data redundancy and conserves on-chip resources. Using the optimized accelerator, we successfully executed ResNet50 inference on an Intel Arria 10 1150GX FPGA, achieving a throughput of 497 GOPS, or an equivalent computational power of 1579 GOPS, with a power consumption of only 22 watts.
Enhancing the Performance of Vibration Energy Harvesting Based on 2:1:2 Internal Resonance in Magnetically Coupled Oscillators
Authors: Dowlati Shakiba , Kacem Najib , Bouhaddi Noureddine
Published: December 2024

An electromagnetic vibration energy harvester with a 2:1:2 internal resonance (IR) is proposed, allowing for the simultaneous activation of two IRs within the system in order to enhance its performance in terms of bandwidth and harvested power. The device consists of three magnetically coupled oscillators separated by an adjustable gap to tune the system eigenfrequencies and achieve a 2:1:2 IR. Numerical investigations are conducted to predict the behavior of the proposed device, and a multi-objective optimization procedure is employed to enhance the harvester’s performance by introducing mass perturbations. The experimental validation of the optimized design is performed while highlighting the benefits of internal resonance, and the obtained results are in good agreement with the theoretical findings. The results indicate that incorporating two internal resonances into the harvester enhances its performance compared to the harvesters reported in the literature. The harvester achieves an SFoMBW of 7600 kg/m3, reflecting a high average power density over a broad bandwidth.
A Novel Temperature Drift Compensation Algorithm for Liquid-Level Measurement Systems
Authors: Li Shanglong , Gao Wanjia , Liu Wenyi
Published: December 2024

Aiming at the problem that ultrasonic detection is greatly affected by temperature drift, this paper investigates a novel temperature compensation algorithm. Ultrasonic impedance-based liquid-level measurement is a crucial non-contact, non-destructive technique. However, temperature drift can severely affect the accuracy of experimental measurements based on this technology. Theoretical analysis and experimental research on temperature drift phenomena are conducted in this study, accompanied by the proposal of a new compensation algorithm. Leveraging an external fixed-point liquid-level detection system experimental platform, the impact of temperature drift on ultrasonic echo energy and actual liquid-level height is examined. Experimental results demonstrate that temperature drift affects the speed and attenuation of ultrasonic waves, leading to decreased accuracy in measuring liquid levels. The proposed temperature compensation method yields an average relative error of 3.427%. The error range spans from 0.03 cm to 0.336 cm. The average relative error reduces by 21.535% compared with before compensation, showcasing its applicability across multiple temperature conditions and its significance in enhancing the accuracy of ultrasonic-based measurements.
The Characterization of L-Asparaginase with Low L-Glutaminase Activity Produced by the Marine Pseudomonas sp. Strain GH-W2b
Authors: Yu Woon-Jong , Lee Ha Young , Kwon Yong Min , Bae Seung Seob , Choi Grace , Hwang Hyun-Ju , Chung Dawoon
Published: December 2024

L-asparaginase (ASNase) hydrolyzes L-asparagine to L-aspartic acid and ammonia and has been used as an antitumor agent for the treatment of acute lymphoblastic leukemia. ASNase has also been used to mitigate the suspected carcinogenic effects of acrylamide in foods. Commercial ASNases currently used in the pharmaceutical and food industries are produced by microorganisms, such as bacteria and fungi. However, their toxicity and poor thermal stability limit their application. Therefore, identifying novel sources of ASNase is critical. In the present study, we identified an asparaginase-producing marine bacterial strain, GH-W2b, as a Pseudomonas species. Based on the plate assay results, GH-W2b produced ASNase with marginal L-glutaminase (GLNase) activity, which has been reported to cause adverse effects in clinical ASNases. The ASNase activity of GH-W2b was maximized at 50–65 °C and pH 7.0–8.5. Notably, the activities were consistent at a wide range of NaCl concentrations (0–15%) at 37 °C. In addition, compared to the control (no pre-incubation), ASNase activities were retained (>87%) by 2 h pre-incubation at 4–37 °C. Overall, our results suggest that GH-W2b ASNase has the potential to serve as a candidate for the development of salt-tolerant and/or alternative ASNases in pharmaceutical and food products.
Evaluation of a Commercial Multiplex Real-Time PCR with Melting Curve Analysis for the Detection of Mycobacterium tuberculosis Complex and Five Nontuberculous Mycobacterial Species
Authors: Kim Keun Ju , Chang Yunhee , Yun Seung Gyu , Nam Myung-Hyun , Cho Yunjung
Published: December 2024

Background: Accurate and timely diagnosis of mycobacterial infections, including Mycobacterium tuberculosis complex (MTBC) and nontuberculous mycobacteria (NTM), is crucial for effective disease management. Methods: This study evaluated the performance of the NeoPlex TB/NTM-5 Detection Kit (NeoPlex assay, Seongnam, Republic of Korea), a multiplex real-time PCR assay that incorporates melting curve analysis, compared with the line-probe assay (LPA). The NeoPlex assay could simultaneously detect and differentiate MTBC from five other NTM species: Mycobacterium intracellulare, Mycobacterium avium, Mycobacterium kansasii, Mycobacterium abscessus, and Mycobacterium massiliense. A total of 91 acid-fast bacillus culture-positive samples, comprising 36 MTBC and 55 NTM isolates, were collected from the Korea University Anam Hospital. Results: The NeoPlex assay successfully detected nucleic acids in 87 of the 91 isolates (95.6%). Notably, it identified additional mycobacterial nucleic acids not detected by the LPA in eight isolates. These findings were confirmed via DNA sequencing. The assay had 100% sensitivity and specificity for M. intracellulare, M. abscessus, M. massilense, NTM, and MTBC, whereas it had 100% specificity and sensitivity of 90.9% and 75.0% for M. avium and M. kansasii, respectively. Conclusions: These results highlight the potential of the NeoPlex assay to enhance rapid and accurate diagnosis of mycobacterial infections, particularly in settings in which prompt treatment initiation is essential.
Investigation of Intestinal Microbes of Five Zokor Species Based on 16S rRNA Sequences
Authors: Zou Yao , Zou Quan , Yang Hui , Han Chongxuan
Published: December 2024

Zokor is a group of subterranean rodents that are adapted to underground life and feed on plant roots. Here, we investigated the intestinal microbes of five zokor species (Eospalax cansus, Eospalax rothschildi, Eospalax smithi, Myospalax aspalax, and Myospalax psilurus) using 16S amplicon technology combined with bioinformatics. Microbial composition analysis showed similar intestinal microbes but different proportions among five zokor species, and their dominant bacteria corresponded to those of herbivores. To visualize the relationships among samples, PCoA and PERMANOVA tests showed that the intestinal microbes of zokors are largely clustered by host species, but less so by genetics and geographical location. To find microbes that differ among species, LefSe analysis identified Lactobacillus, Muribaculaceae, Lachnospiraceae_NK4A136_group, unclassified_f_Christensenellaceae, and Desulfovibrio as biomarkers for E. cansus, E. rothschildi, E. smithi, M. aspalax, and M. psilurus, respectively. PICRUSt metagenome predictions revealed enriched microbial genes for carbohydrate and amino acid metabolism in E. cansus and E. smithi, and for cofactor and vitamin metabolism as well as glycan biosynthesis and metabolism in E. rothschildi, M. aspalax, and M. psilurus. Our results demonstrated differences in the microbial composition and functions among five zokor species, potentially related to host genetics, and host ecology including dietary habits and habitat environment. These works would provide new insight into understanding how subterranean zokors adapt to their habitats by regulating intestinal microbes.
Probiotic Potential and Enhanced Adhesion of Fermented Foods-Isolated Lactic Acid Bacteria to Intestinal Epithelial Caco-2 and HT-29 Cells
Authors: Sim Eun Ah , Kim Seon-Young , Kim SangNam , Mun Eun-Gyung
Published: December 2024

This study evaluated the probiotic potential of lactic acid bacteria (LAB) isolated from fermented milk and soymilk products purchased from local markets. The LAB strains were assessed for acid and bile resistance, antibiotic resistance, and adhesion to human intestinal epithelial models. Streptococcus thermophilus (JAMI_LB_02) and Lactiplantibacillus plantarum (JAMI_LB_05) showed the highest survival rates in artificial gastric and bile juices, at 87.17 ± 0.02% and 96.71 ± 4.10%, respectively, with all strains (except JAMI_LB_03) demonstrating antibiotic resistance. Adhesion ability indicated the superior performance of JAMI_LB_02 and JAMI_LB_05 compared to standard strains. JAMI_LB_02 adhered to Caco-2 cells at 2.10 ± 0.94% and to HT-29 cells at 3.32 ± 0.38%, exceeding standard strains (1.06 ± 0.13% and 1.89 ± 0.58%). JAMI_LB_05 achieved the highest rates at 5.62 ± 1.33% on Caco-2 and 5.76 ± 0.46% on HT-29 cells. Their combination (JAMI_LB_02 + JAMI_LB_05) significantly enhanced adhesion to 18.57 ± 5.49% on Caco-2 and 21.67 ± 8.19% on HT-29 cells, demonstrating strong synergy. These findings highlight the probiotic potential of the isolated LAB strains, particularly in mixed formulations, which may improve intestinal survival, adaptability, and efficacy. Further in vivo studies are warranted to validate their clinical applications and optimize strain combinations for human health benefits.
Effect of Lactic Acid Bacteria and Propionic Acid on Fermentation Characteristics, Chemical Composition, and Aerobic Stability of High-Moisture Corn Grain Silage
Authors: Bao Jinze , Wang Lei , Yu Zhu
Published: December 2024

This investigation aimed to assess the effect of additives on the aerobic stability, fermentation profile, and chemical composition of high-moisture corn grain silage. The corn grain was milled and divided this into four distinct treatment groups: Lentilactobacillus buchneri, propionic acid, Lactiplantibacillus plantarum, and no additive (control). The capacity of the silos was 1 L and density was 1000 kg/m3. Each group had three replicates and was fermented for 45 d. At silo opening, one part of silage was used for fermentation parameters, chemical composition, and in vitro dry matter digestibility analysis; another part was used for aerobic stability determination. Compared with the control, all additives increased lactic acid and dry matter concentrations (p < 0.001) and decreased neutral detergent fiber level (p < 0.001). In comparison with the control, the application of Lentilactobacillus buchneri and propionic acid improved silage aerobic stability, showed by lower pH level and yeast and mold populations after exposure to air. The findings offer theoretical groundwork and technological backing for the use of high-moisture corn grain silage.
Recovery of Phenolic Compounds with Antioxidant Capacity Through Solid-State Fermentation of Pistachio Green Hull
Authors: Ordoñez-Cano Andrés Javier , Ramírez-Esparza Ulises , Méndez-González Fernando , Alvarado-González Mónica , Baeza-Jiménez Ramiro , Sepúlveda-Torre Leonardo , Prado-Barragán Lilia Arely , Buenrostro-Figueroa José Juan
Published: December 2024

Pistachio green hull (PGH) represents the non-edible fraction obtained after the seed is harvested and is an important source of phenolic compounds. Solid-state fermentation (SSF) is a viable biotechnological and economical technique for extracting phenolic compounds. This study aimed to evaluate the SSF with Aspergillus niger GH1 to recover total phenolic compounds (TPC) with antioxidant capacity (AC) from PGH. For this, the time of higher TPC and AC (DPPH [2,2-diphenyl-1-picrylhydrazyl], ABTS [2,2-azinobis-(3-ethylbenzothiazoline-6-sulfonate)], FRAP [ferric reducing antioxidant power]) was selected. Then, moisture, inoculum concentration, and aeration rate were evaluated. A. niger GH1 was able to grow and colonize the PGH, with the higher value of TPC (23.83 mg/g of dry mass (gdm)) obtained after 24 h of culture, which significantly correlated with AC (Pearson’s R = 0.69). Moisture and aeration rate were the main factors influencing TPC. The highest values for both TPC and AC were achieved in treatment 8 (60% moisture, 5 × 106 spores/mL, and 1 L/Kgwm min), resulting in a 129% and 1039% increase, respectively. Gallic acid 4-O-glucoside and geranine were identified in the PGH extracts using high-performance liquid chromatography coupled with mass spectrometry. The SSF provides eco-friendly alternatives for releasing bioactive compounds from PGH, adding value to this waste.
Geochemistry and Mineralogy of Precipitates from Passive Treatment of Acid Mine Drainage: Implications for Future Management Strategies
Authors: Delgado Joaquín , Lozano Olivia , Ayala Diana , Martín Domingo , Barba-Brioso Cinta
Published: December 2024

Traditional mining activities in Zaruma-Portovelo (SE Ecuador) have led to high concentrations of pollutants in the Puyango River due to acid mine drainage (AMD) from abandoned waste. Dispersed alkaline substrate (DAS) passive treatment systems have shown efficacy in neutralizing acidity and retaining metals and sulfates in acidic waters, achieving near a 100% retention for Fe, Al, and Cu, over 70% for trace elements, and 25% for SO42−. However, significant solid residues are generated, requiring proper geochemical and mineralogical understanding for management. This study investigates the fractionation of elements in AMD precipitates. Results indicate that Fe3+ and Al3+ predominantly precipitate as low-crystallinity oxyhydroxysulfate minerals such as schwertmannite [Fe3+16(OHSO4)12–13O16·10–12H2O] and jarosite [KFe3+3(SO4)2(OH)6], which retain elements like As, Cr, Cu, Pb, and Zn through adsorption and co-precipitation processes. Sulfate removal occurs via salts like coquimbite [AlFe3(SO4)6(H2O)12·6H2O] and gypsum [CaSO4·2H2O]. Divalent metals are primarily removed through carbonate and bicarbonate phases, with minerals such as azurite [Cu(OH)2·2CuCO3], malachite [Cu2(CO3)(OH)2], rhodochrosite [MnCO3], and calcite [CaCO3]. Despite the effectiveness of DAS, leachates from the precipitates exceed regulatory thresholds for aquatic life protection, classifying them as hazardous and posing environmental risks. However, these residues offer opportunities for the recovery of valuable metals.
An Overview of Thermochemical Reduction Processes for Titanium Production
Authors: Matsanga Nyasha , Wa Kalenga Michel , Nheta Willie
Published: December 2024

Titanium is one of the most abundant metals with superior properties such as excellent mechanical properties, high strength-to-weight ratio, and oxidation and corrosion resistance. However, it is commercially expensive to produce; hence, its use is limited. Currently, the Kroll process remains the most commercially exploited to produce titanium. Therefore, this paper thoroughly reviews some other proposed and developing thermo-reduction methods using the two main precursors titanium dioxide (TiO2) and titanium chloride (TiCl4) together with the environmental impacts they cause. The exorbitant production cost and environmental issues have resulted in enormous research and development to innovate more sustainable methods of titanium production. The various processes were comprehensively analyzed to assess whether they have the potential to expand to be economically viable. From this review, it is apparent that most of the methods still require further research to scale them up to an industrial and commercial level. Recent developments including the Council for Scientific and Industrial Research-Ti (CSIR-Ti), Titanium Reduction Oxide (TiRO), Preform Reduction Process (PRP), and hydrogen-assisted magnesiothermic reduction (HAMR) processes are auspicious for producing high-purity titanium sustainably.
The Dependence of Ilmenite’s Dissolution Rate in Hydrochloric Acid on the Fe(III)/Fe(II) Ratio, with Fe K-Edge XANES Pre-Edge Peak Analysis
Authors: Sun Thomas Y. , Wykes Jeremy L. , Wolmarans Karla , Kappen Peter , Haverkamp Richard G.
Published: December 2024

The complete dissolution of the Ti and Fe content of ilmenite is a necessary first step for the production of TiO2 directly from ilmenite. Hydrochloric acid is one of the possible solubilizing agents. However, the ability to dissolve ilmenite in hydrochloric acid depends on the nature of the source material. Here, we consider the effect that the oxidation state of Fe in the ilmenite has on the dissolution rate. Three placer ilmenite fractions from New Zealand and India were dissolved in concentrated hydrochloric acid in a stirred vessel. The dissolution rate constants for Fe and Ti for each fraction based on a shrinking sphere model were compared with the Fe(III)/Fe(II) ratio. Pre-edge Fe K-edge XANES as a measure of Fe(III)/Fe(II) has been shown to extend to ilmenite, which has a complex pre-edge region due to the involvement of Ti electronic levels. It was found that there is a relationship between the oxidation state of Fe and the dissolution rate, with a higher Fe(II) content resulting in more rapid dissolution. A higher Fe(II) content reflects a younger, less weathered material, closer to the “standard” stoichiometry of ilmenite. These data and the presented correlation may support the design of industrial processes to digest ilmenite in hydrochloric acid from varying feedstocks.
Experimental and Theoretical Study of Sc2O3 Nanoparticles Under High Pressure
Authors: de Jesus Pereira André Luis , Sans Juan Angel , Vilaplana Rosario , Ray Sudeshna , Tadge Prachi , Godoy Armstrong , Horta Isabela M. , da Silva-Sobrinho Argemiro S. , Rodríguez-Hernández Plácida , Muñoz Alfonso , Popescu Catalin , Manjón Francisco J.
Published: December 2024

This study investigates the high-pressure structural and vibrational properties of nano-Sc2O3 using a combination of X-ray diffraction, Raman spectroscopy, and theoretical calculations. Nano-Sc2O3 maintains its cubic bixbyite structure up to 26.4 GPa, without evidence of phase transitions, contrasting with bulk Sc2O3, which transitions to a monoclinic phase around 25–28 GPa. Raman spectroscopy reveals a pressure-induced blue shift in the vibrational modes, indicating lattice compression, and the absence of new modes confirms the retention of the cubic symmetry. Theoretical predictions using density functional theory (DFT) closely match the experimental data, validating the computational approach we use to model the pressure-dependent vibrational behavior of nano-Sc2O3. Comparisons with previous studies seem to show that the nanoscale material exhibits enhanced structural stability compared to its bulk counterpart, likely due to size effects and surface energy contributions. These findings provide new insights into the behavior of nanomaterials under extreme conditions and highlight the potential applications of nano-Sc2O3 in high-pressure environments.
Recovery of Different Cu-Phases from Industrial Wastewater
Authors: Anagnostopoulos Iphigenia Franziska , Heuss-Aßbichler Soraya
Published: December 2024

The dominant treatment process for removing heavy metals from industrial wastewater is chemical neutralisation precipitation using lime milk as a precipitation agent, resulting in a highly voluminous hydroxide sludge with a low heavy metal concentration. These sludges are predominantly landfilled, and the metals are lost to the circular economy. At the same time, metals are urgently needed as raw materials. A new approach is represented by the low-pressure, low-energy Specific Product-Oriented Precipitation process (SPOP). This approach, however, requires the adjustment of various reaction parameters for optimal operation. This study presents the impacts of the stirring rate during the reaction and the Fe concentration in the solution on the recovery of Cu from Cu-enriched electroplating wastewater. Three different recovery options are described: Option (1), the formation of CuO; Option (2), the generation of brochantite, a Cu-hydroxysulphate; and Option (3), the incorporation of Cu into ferrite. Tenorite (CuO) is precipitated at 40 °C reaction temperature at a low stirring rate of 100–200 rpm. At an accelerated stirring rate of 400–500 rpm, brochantite (Cu4(OH)6SO4) is formed. With high Fe concentrations and a molar ratio of Cu:Fe of 1:2, Cu-ferrite (CuFe2O4) is the precipitation product. In any case, the achieved recovery rates in the treated wastewater are better than 99.9%.