bluuebunny/crossref_metadata_2025 huggingface dataset:
Proteomics and EPS Compositional Analysis Reveals Desulfovibrio bisertensis SY-1 Induced Corrosion on Q235 Steel by Biofilm Formation
Authors: Wang Yanan , Zhang Ruiyong , Mathivanan Krishnamurthy , Zhang Yimeng , Yang Luhua , Guan Fang , Duan Jizhou
Published: October 2024

Microorganisms that exist in the seawater form microbial biofilms on materials used in marine construction, especially on metal surfaces submerged in seawater, where they form biofilms and cause severe corrosion. Biofilms are mainly composed of bacteria and their secreted polymeric substances. In order to understand how biofilms promote metal corrosion, planktonic and biofilm cells of Desulfovibrio bizertensis SY-1 (D. bizertensis) from Q235 steel were collected and analyzed as to their intracellular proteome and extracellular polymeric substances (EPS). The intracellular proteome analysis showed that the cellular proteins were strongly regulated in biofilm cells compared to planktonic cells, e.g., along with flagellar proteins, signaling-related proteins were significantly increased, whereas energy production and conversion proteins and DNA replication proteins were significantly regulated. The up-and-down regulation of proteins revealed that biofilm formation by bacteria on metal surfaces is affected by flagellar and signaling proteins. A significant decrease in DNA replication proteins indicated that DNA is no longer replicated and transcribed in mature biofilms, thus reducing energy consumption. Quantitative analysis and lectin staining of the biofilm on the metal’s surface revealed that the bacteria secreted a substantial amount of EPS when they began to attach to the surface, and proteins dominated the main components of EPS. Further, the infrared analysis showed that the secondary structure of the proteins in the EPS of the biofilm was mainly dominated by β-sheet and 3-turn helix, which may help to enhance the adhesion of EPS. The functional groups of EPS analyzed using XPS showed that the C element of EPS in the biofilm mainly existed in the form of combinations with N. Furthermore, the hydroxyl structure in the EPS extracted from the biofilm had a stronger hydrogen bonding effect, which could maintain the stability of the EPS structure and biofilm. The study results revealed that D. bizertensis regulates the metabolic pathways and their secreted EPS structure to affect biofilm formation and cause metal corrosion, which has a certain reference significance for the study of the microbially influenced corrosion (MIC) mechanism.
Influence of Equal Channel Angular Pressing and Cyclic Extrusion Compression on the Microstructure Evolution and Mechanical Properties of Pure Aluminum
Authors: Abd El Aal Mohamed Ibrahim
Published: October 2024

The influence of equal channel angular pressing (ECAP) and cyclic extrusion compression (CEC) of Al-1080 on the pressing load, microstructure, and tensile properties was investigated. The pressing peak loads of the CEC were 218.8–265.4% higher than those of the ECAP, with a more complex load behavior in the CEC process. The deformation morphology of the ECAP samples indicates an improvement in the deformation homogeneity with the number of passes. Shear band morphology with a decrease in the shear band width from the center to the outer surface makes up the predominant pattern of the CEC samples. The ECAP samples have 13.9–44% smaller average grain sizes, with 3.8–8.1% higher high-angle grain boundaries (HAGBs) than the CECed samples. The ECAP and CEC processing improve the tensile strength. However, the ECAP sample’s tensile strength (UTS) and the proof strength (σ0.2) were 11.5–20.6 and 2.6–16.4% higher than that of CEC, without noticeable differences in elongation. The σ0.2 values were predicted accurately with a deviation range of 1.8–7.3% from the experimental one. The ECAP samples are easy to process under lower loads. Moreover, ECAP samples have an equiaxed grain microstructure with a higher degree of deformation homogeneity and tensile strength.
A Group-Enriched Viscoelastic Model for High-Damping Vitrimers with Many Dangling Chains
Authors: Li Yan , Feng Haibo , Xiong Jing , Li Li
Published: October 2024

Classical viscoelastic models usually only consider the motion of chain segments and the motion of the entire molecular chain; therefore, they will cause inevitable errors when modeling self-healing vitrimer materials with many group movements. In this paper, a group-enriched viscoelastic model is proposed for self-healing vitrimers where the group effect cannot be neglected. We synthesize a specific damping vitrimer with many dangling chains, surpassing the limited loss modulus of conventional engineering materials. Due to the dangling chains, the damping capability can be improved and the group effect cannot be neglected in the synthesized damping vitrimer. The group-enriched viscoelastic model accurately captures the experimental damping behavior of the synthesized damping vitrimer. Our results indicate that the group-enriched viscoelastic model can improve the accuracy of classical viscoelastic models. It is shown that the group effect can be ignored at low frequencies since the chain segments have sufficient time for extensive realignment; however, the group effect can become significant in the case of high frequency or low temperature.
Tensile and Bending Strength of Birch and Beech Lamellas Finger Jointed with Conventional and Newly Developed Finger-Joint Profiles
Authors: Stolze Hannes , Militz Holger
Published: October 2024

In this study, the tensile and bending strength of birch and beech lamellas finger jointed with conventional (Standard) and newly developed finger-joint profiles (New) are presented. Polyurethane (PUR), Melamine-Urea-Formaldehyde (MUF) and Phenol-Resorcinol-Formaldehyde (PRF) adhesive systems were used to bond the finger joints. The objective of the New profiles was to reduce the stress concentrations within the finger joint by cutting the cross-grooved fingers perpendicular to the main orientation of the finger-joint profile. In the first trials of the development, larger cross-grooved fingers were cut with the aim to improve the stress distribution and to reinforce the finger joint by filling gaps in the finger joint with adhesive. As the study progressed, initial optimisations of the New profile were made. Smaller cross-grooved fingers were cut as it was assumed that they are beneficial for the manufacturing and integrity of the New profile. In combination with the MUF adhesive system, the New profile achieved the highest increase in the bending and tensile strengths compared to the Standard profile. In addition to the increased strength, other advantages such as reduced cracking in the finger joint were observed when using the New profile. The high strength and stiffness of hardwoods or other high-performance materials used in timber construction can probably be better exploited in combination with the New profile. Further tests will be carried out by considering different configurations of the New profile and different materials.
Influence of the Pulse Mode of Manual Metal Arc Welding on Weldment Distortions
Authors: Ferdinandov Nikolay , Gospodinov Danail , Ilieva Mariana , Radev Rossen , Hristov Georgi
Published: October 2024

As a result of the thermo-mechanical impact during welding, distortions are generated in welded structures. These distortions significantly influence the geometric and dimensional accuracy of welded structures, in many cases lowering their working characteristics and reliability. An optimal design for welded structures is a prerequisite for increased reliability and reduction in manufacturing cost, and such an optimal design can be achieved knowing the distortions in weldments. Despite the fact that pulsed metal inert gas welding and metal active gas welding have been broadly applied in the last few decades, nowadays, few manufacturers, for instance, Fronius, EWM, Redco, and Perfect Power Welders, offer such an option for manual arc welding. This work aims to determine the influence of the parameters of pulsed welding modes on distortions that are generated during manual arc welding. Two different inverter welding power sources were used, and the welding distortions were measured by 3D scanning. The results showed that the pulsed mode during manual arc welding led to a reduction in distortions compared to the conventional welding mode. The crucial part of the manual welding system proved to be the qualification and performance of the welder.
Dissolution of Volcanic Ash in Alkaline Environment for Cold Consolidation of Inorganic Binders
Authors: Dal Poggetto Giovanni , Douwe Philippe , Stroscio Antonio , Kamseu Elie , Lancellotti Isabella , Elimbi Antoine , Leonelli Cristina
Published: October 2024

A systematic study on the dissolution in concentrated alkali of two volcanic ashes from Cameroon, denoted as DAR and VN, is presented here. One volcanic ash, DAR, was 2 wt% richer in Fe and Ca and 4 wt% lower in Si than the other, designated as VN. Such natural raw materials are complex mixtures of aluminosilicate minerals (kaersutite, plagioclase, magnetite, diopside, thenardite, forsterite, hematite, and goethite) with a good proportion of amorphous phase (52 and 74 wt% for DAR and VN, respectively), which is more reactive than the crystalline phase in alkaline environments. Dissolution in NaOH + sodium silicate solution is the first step in the geopolymerisation process, which, after hardening at room temperature, results in solid and resistant building blocks. According to XRD, the VN finer ash powders showed a higher reactivity of Al-bearing soluble amorphous phases, releasing Al cations in NaOH, as indicated by IPC-MS. In general, dissolution in a strong alkaline environment did not seem to be affected by the NaOH concentration, provided that it was kept higher than 8 M, or by the powder size, remaining below 75 µm, while it was affected by time. However, in the time range studied, 1–120 min, the maximum element release was reached at about 100 min, when an equilibrium was reached. The hardened alkali activated materials show a good reticulation, as indicated by the low weight loss in water (10 wt%) when a hardening temperature of 25 °C was assumed. The same advantage was found for of the room-temperature consolidated specimens’ mechanical performance in terms of resistance to compression (4–6 MPa). The study of the alkaline dissolution of volcanic ash is, therefore, an interesting way of predicting and optimising the reactivity of the phases of which it is composed, especially the amorphous ones.
Deformation Control in Mesoscale Micro-Milling of Curved Thin-Walled Structures
Authors: Yi Jie , Wang Xinyao , Zhu Yichen , Wang Xurui , Xiang Junfeng
Published: October 2024

The micro-machining scale effect makes it challenging to forecast and control the process parameters of the micro-milling process, which makes the micro-flanking-milling of weak-rigidity micro-thin-walled parts prone to deformation. To determine the critical cutting parameters for chip formation in the micro-milling of curved thin-walled parts at the mesoscale, the strain-softening effect of titanium alloy during high-speed milling and the scale effect of mesoscale cutting were comprehensively considered and a finite element prediction model for curved micro-thin-wall micro-milling was established to determine the critical milling parameters for effective material removal. Based on the determined milling parameters, an experimental design of response surface optimization was carried out. Based on the response surface methodology, a data-driven quantitative model with milling process parameters as design variables and deformation amounts as response variables was established to reveal the influence mechanism of multiple milling process parameters on machining accuracy. Based on the process requirements for deformation control in the micro-milling of curved thin-walled structures, dynamic optimization of the milling process parameters was performed using an improved NSGA-III algorithm to obtain non-dominated solutions. A visual ranking and a determination of the unique solution were conducted using the entropy weight–TOPSIS method. Finally, micro-milling validation experiments were carried out using the optimal parameter combination. The optimal solution for the process parameters of the arc-shaped micro-thin-wall micro-milling of titanium alloy established by the institute provides a relevant reference and guidance for mesoscale arc-shaped thin-wall micro-milling.
Properties of Sn-Doped PBZT Ferroelectric Ceramics Sintered by Hot-Pressing Method
Authors: Brzezińska Dagmara , Bochenek Dariusz , Zubko Maciej , Niemiec Przemysław , Matuła Izabela
Published: October 2024

This work investigated the structure, microstructure, and ferroelectric and dielectric behavior of (Pb0.97Ba0.03)(Zr0.98Ti0.02)1−xSnxO3 (PBZT_xSn) solid solution with variable tin content in the range x = 0.00–0.08. Synthesis was carried out using the powder calcination method, and sintering was carried out using the hot-pressing method. For all the PBZT_xSn samples at room temperature, X-ray diffractograms confirmed the presence of an orthorhombic (OR) crystal structure with space group Pnnm, and the microstructure is characterized by densely packed and properly shaped grains with an average size of 1.36 µm to 1.73 µm. At room temperature, PBZT_xSn materials have low permittivity values ε′ ranging from 265 to 275, whereas, at the ferroelectric–paraelectric phase transition temperature (RE–C), the permittivity is high (from 8923 to 12,141). The increase in the tin dopant in PBZT_xSn lowers permittivity and dielectric loss and changes the scope of occurrence of phase transitions. The occurring dispersion of the dielectric constant and dielectric loss at low frequencies, related to the Maxwell–Wagner behavior, decreases with increasing tin content in the composition of PBZT_xSn. Temperature studies of the dielectric and ferroelectric properties revealed anomalies related to the phase transitions occurring in the PBZT_xSn material. With increasing temperature in PBZT_xSn, phase transitions occur from orthorhombic (OR) to rhombohedral (RE) and cubic (C). The cooling cycle shifts the temperatures of the phase transitions towards lower temperatures. The test results were confirmed by XRD Rietveld analysis at different temperatures. The beneficial dielectric and ferroelectric properties suggest that the PBZT_xSn materials are suitable for micromechatronic applications as pulse capacitors or actuator elements.
Long-Range Bird Species Identification Using Directional Microphones and CNNs
Authors: Garcia Tiago , Pina Luís , Robb Magnus , Maria Jorge , May Roel , Oliveira Ricardo
Published: October 2024

This study explores the integration of directional microphones with convolutional neural networks (CNNs) for long-range bird species identification. By employing directional microphones, we aimed to capture high-resolution audio from specific directions, potentially improving the clarity of bird calls over extended distances. Our approach involved processing these recordings with CNNs trained on a diverse dataset of bird calls. The results demonstrated that the system is capable of systematically identifying bird species up to 150 m, reaching 280 m for species vocalizing at frequencies greater than 1000 Hz and clearly distinct from background noise. The furthest successful detection was obtained at 510 m. While the method showed promise in enhancing the identification process compared to traditional techniques, there were notable limitations in the clarity of the audio recordings. These findings suggest that while the integration of directional microphones and CNNs for long-range bird species identification is promising, further refinement is needed to fully realize the benefits of this approach. Future efforts should focus on improving the audio-capture technology to reduce ambient noise and enhance the system’s overall performance in long-range bird species identification.
An Enhanced Tree Ensemble for Classification in the Presence of Extreme Class Imbalance
Authors: Safi Samir K. , Gul Sheema
Published: October 2024

Researchers using machine learning methods for classification can face challenges due to class imbalance, where a certain class is underrepresented. Over or under-sampling of minority or majority class observations, or solely relying on model selection for ensemble methods, may prove ineffective when the class imbalance ratio is extremely high. To address this issue, this paper proposes a method called enhance tree ensemble (ETE), based on generating synthetic data for minority class observations in conjunction with tree selection based on their performance on the training data. The proposed method first generates minority class instances to balance the training data and then uses the idea of tree selection by leveraging out-of-bag (ETEOOB) and sub-samples (ETESS) observations, respectively. The efficacy of the proposed method is assessed using twenty benchmark problems for binary classification with moderate to extreme class imbalance, comparing it against other well-known methods such as optimal tree ensemble (OTE), SMOTE random forest (RFSMOTE), oversampling random forest (RFOS), under-sampling random forest (RFUS), k-nearest neighbor (k-NN), support vector machine (SVM), tree, and artificial neural network (ANN). Performance metrics such as classification error rate and precision are used for evaluation purposes. The analyses of the study revealed that the proposed method, based on data balancing and model selection, yielded better results than the other methods.
The Propagation of Congestion on Transportation Networks Analyzed by the Percolation Process
Authors: Chen Jieming , Wu Yiwei
Published: October 2024

Percolation theory has been widely employed in network systems as an effective tool to analyze phase transitions from functional to nonfunctional states. In this paper, we analyze the propagation of congestion on transportation networks and its influence on origin–destination (OD) pairs using the percolation process. This approach allows us to identify the most critical links within the network that, when disrupted due to congestion, significantly impact overall network performance. Understanding the role of these critical links is essential for developing strategies to mitigate congestion effects and enhance network resilience. Building on this analysis, we propose two methods to adjust the capacities of these critical links. First, we introduce a greedy method that incrementally adjusts the capacities based on their individual impact on network connectivity and traffic flow. Second, we employ a Particle Swarm Optimization (PSO) method to strategically increase the capacities of certain critical links, considering the network as a whole. These capacity adjustments are designed to enhance the network’s resilience by ensuring it remains functional even under conditions of high demand and congestion. By preventing the propagation of congestion through strategic capacity enhancements, the transportation network can maintain connectivity between OD pairs, reduce travel times, and improve overall efficiency. Our approach provides a systematic method for improving the robustness of transportation networks against congestion propagation. The results demonstrate that both the greedy method and the PSO method effectively enhance network performance, with the PSO method showing superior results in optimizing capacity allocations. This research is crucial for maintaining efficient and reliable mobility in urban areas, where congestion is a persistent challenge, and offers valuable insights for transportation planners and policymakers aiming to design more resilient transportation infrastructures.
Formalizing and Simulating the Token Aspects of Blockchain-Based Research Collaboration Platform Using Game Theory
Authors: Udokwu Chibuzor
Published: October 2024

Small and medium-scale enterprises (SMEs) need a platform that actively enables collaboration with research institutions and consultants as SMEs lack the financial resources to conduct independent research. Such a platform will require a verifiable manipulation-free system to enable, execute, and record collaboration activities and to track reputations among the organizations and individuals that use the platform. Blockchain provides an opportunity to build such a collaborative platform by enabling the verifiable recording of the results of the collaborations, aggregating the resulting reputation of the collaborating parties, and offering tokenized incentives to reward positive contributions to the platform. Cryptocurrencies from which blockchain tokens are derived are volatile, thereby reducing business organizations’ interest in blockchain applications. Hence, there is a need to design a self-sustaining valuable token model that incentivizes user behaviours that positively contribute to the platform. This paper explores the application of game theory in analyzing token-based economic interactions between various groups of users in an implemented blockchain-based collaboration platform to design and simulate a token distribution system that provides a fair reward mechanism for users while also providing a dynamic pricing model for the utility value provided by platform tokens. To achieve this objective, we adopted the design science research method, a running case of a blockchain collaboration platform that enables research collaboration, and extensive form games in game theory, first to analyze and simulate token outcomes of users of the collaboration platform. Secondly, the research used a logarithmic model to show the dynamic utility pricing property of the developed token model where the self-sustainability of the token is backed by the availability of an internal resource within the platform. Thirdly, we applied a qualitative approach to analyze potential risks in the designed token model and proposed risk mitigation strategies. Thus, the resulting models and their simulations, such as token distribution models and a dynamic token utility model, as well as the identified token risks and their mitigation strategies, represent the main contributions of this work.
Similarity Measures of Probabilistic Interval Preference Ordering Sets and Their Applications in Decision-Making
Authors: Wei Qi , Wang Rui , Ruan Chuan-Yang
Published: October 2024

The concept of probabilistic interval preference ordering sets (PIPOSs) provides a scientific and intuitive framework for solving real-life multi-criteria group decision-making problems. In some areas such as investment decision-making and supplier selection, PIPOSs have a wider application space, and the development of similarity and distance measures based on PIPOSs holds great significance. Similarity measure is a basic and prominent tool for dealing with imperfect and ambiguous information in fuzzy sets, but it can also be used to deal with uncertain information in preference ordering. These metrics play an important role in the actual decision-making process, as they effectively quantify the degree of similarity between two PIPOSs, and further allow for the prioritization of different scenarios. In this article, we sort out the definitions and arithmetic rules of PIPOSs, and creatively propose several new similarity measures based on PIPOSs. Then, we propose a group decision-making method based on similarity measures and conduct a comparative study with three existing similarity measures to illustrate its advantages over existing metrics. Finally, we confirm its validity through numerical illustrations in the case study, and also conduct a comparative assessment to verify the scientific validity and effectiveness of the newly introduced measure against the existing metrics.
Robust Leader–Follower Formation Control Using Neural Adaptive Prescribed Performance Strategies
Authors: Xie Fengxi , Liang Guozhen , Chien Ying-Ren
Published: October 2024

This paper introduces a novel leader–follower formation control strategy for autonomous vehicles, aimed at achieving precise trajectory tracking in uncertain environments. The approach is based on a graph guidance law that calculates the desired yaw angles and velocities for follower vehicles using the leader’s reference trajectory, improving system stability and predictability. A key innovation is the development of a Neural Adaptive Prescribed Performance Controller (NA-PPC), which incorporates a Radial Basis Function Neural Network (RBFNN) to approximate nonlinear system dynamics and enhances disturbance estimation accuracy. The proposed method enables high-precision trajectory tracking and formation maintenance under random disturbances, which are vital for autonomous vehicle logistics and detection technologies. Leveraging a graph-based guidance law reduces control complexity and improves robustness against external disturbances. The inclusion of second-order filters and adaptive RBFNNs further enhances nonlinear error handling, improving control performance, stability, and accuracy. The integration of guidance laws, leader–follower control strategies, backstepping techniques, and RBFNNs creates a robust formation control system capable of maintaining performance under dynamic conditions. Comprehensive computer simulations validate the effectiveness of this controller, highlighting its potential to advance autonomous vehicle formation control.
Electrochemical–Thermal Fluid Coupled Analysis and Statistical Analysis of Cooling System for Large Pouch Cells
Authors: Lee Hamin , Park Seokjun , Kim Chang-Wan
Published: October 2024

In large-format pouch cells for electric vehicles, the issues of elevated and non-uniform temperatures resulting from heat generation are intensified, necessitating the use of liquid cooling systems. The design factors of the liquid cooling system influence the maximum temperature and temperature differences in the module as well as the pumping power of the cooling system. Although it is known that these design factors interact, research on these interactions and their effects is currently lacking. In this study, the individual as well as interaction effects of design factors on the performance of the liquid cooling system for a large-format pouch cell module were investigated using design of experiment and analyzed through statistical methods. Electrochemical–thermal fluid coupled analysis was used to calculate the performance according to the design factors of the liquid cooling system. The wall and channel widths are factors that directly determine the coolant flow velocity and cooling plate heat capacity, and they exhibited major effects on all three responses. Moreover, the influence of each design factor tended to change in response to variations in the other design factors. Thus, the effects of each factor individually and of interactions between factors were quantitatively compared and evaluated for significance. The width of the walls was found to contribute the most to the maximum temperature (36.00%) and pumping power (57.56%), while the width of the channels contributed the most to the temperature difference (38.24%), indicating that they are the main influencing factors.
Application of Bispectral Analysis to Assess the Effect of Drought on the Photosynthetic Activity of Lettuce Plants Lactuca sativa L.
Authors: Astashev Maxim E. , Burmistrov Dmitriy E. , Yanykin Denis V. , Grishin Andrey A. , Knyazeva Inna V. , Dorokhov Alexey S. , Gudkov Sergey V.
Published: October 2024

This article proposes a new method for determining the pathological state of a plant, based on a combination of the method for measuring the dynamics of photosystem II pigment fluorescence in the leaves of L. sativa plants and analyzing the resulting time series using bispectral analysis based on the wavelet transform. The article theoretically shows a possible mechanism for the appearance of a peak on the map of bispectrum indexes during nonlinear analog conversion of a physiological signal in a biological object. The phenomenon of increasing the degree of nonlinearity in the transmission of an external periodic signal in plant signaling systems has been experimentally demonstrated.
Mechanisms of Action of Sea Cucumber Triterpene Glycosides Cucumarioside A0-1 and Djakonovioside A Against Human Triple-Negative Breast Cancer
Authors: Menchinskaya Ekaterina S. , Chingizova Ekaterina A. , Pislyagin Evgeny A. , Yurchenko Ekaterina A. , Klimovich Anna A. , Zelepuga Elena. A. , Aminin Dmitry L. , Avilov Sergey A. , Silchenko Alexandra S.
Published: October 2024

Breast cancer is the most prevalent form of cancer in women worldwide. Triple-negative breast cancer is the most unfavorable for patients, but it is also the most sensitive to chemotherapy. Triterpene glycosides from sea cucumbers possess a high therapeutic potential as anticancer agents. This study aimed to identify the pathways triggered and regulated in MDA-MB-231 cells (triple-negative breast cancer cell line) by the glycosides cucumarioside A0-1 (Cuc A0-1) and djakonovioside A (Dj A), isolated from the sea cucumber Cucumaria djakonovi. Using flow cytometry, fluorescence microscopy, immunoblotting, and ELISA, the effects of micromolar concentrations of the compounds on cell cycle arrest, induction of apoptosis, the level of reactive oxygen species (ROS), mitochondrial membrane potential (Δψm), and expression of anti- and pro-apoptotic proteins were investigated. The glycosides caused cell cycle arrest, stimulated an increase in ROS production, and decreased Δψm in MDA-MB-231 cells. The depolarization of the mitochondrial membrane caused by cucumarioside A0-1 and djakonovioside A led to an increase in the levels of APAF-1 and cytochrome C. This, in turn, resulted in the activation of caspase-9 and caspase-3 and an increase in the level of their cleaved forms. Glycosides also affected the expression of Bax and Bcl-2 proteins, which are associated with mitochondria-mediated apoptosis in MDA-MB-231 cells. These results indicate that cucumarioside A0-1 and djakonovioside A activate the intrinsic apoptotic pathway in triple-negative breast cancer cells. Additionally, it was found that treatment with Cuc A0-1 resulted in in vivo inhibition of tumor growth and metastasis of murine solid Ehrlich adenocarcinoma.
An Uncommon Overlap Syndrome Between Ankylosing Spondylitis and Amyotrophic Lateral Sclerosis—Case Report
Authors: Banciu Christian , Chiriac Sorin , Pojoga Cristina , Marian Loredana , Fabian Antonio , Gogulescu Armand , Simu Mihaela , Parvanescu Ramona , Mioc Alexandra , Racoviceanu Roxana , Munteanu Andreea
Published: October 2024

This case report describes an uncommon overlap syndrome between ankylosing spondylitis (AS) and amyotrophic lateral sclerosis (ALS). Initially, the patient was diagnosed with AS, for which he received various specific treatments, including TNF-α inhibitors. After five years of treatment with TNF-α inhibitor etanercept, the patient was referred for a full neurological assessment after he reported balance disturbances, postural instability, muscle weakness, and other neurological symptoms that indicated the presence of a neurological disorder. After a thorough investigation, the patient was diagnosed with ALS. This case report aims to contribute to the limited literature by providing a detailed case study regarding the crosstalk between AS and ALS while also exploring the potential underlying mechanisms and the possible link between TNF-α inhibitors therapy and ALS.
A Prospective Study of the Medication Regimen Complexity Index and Hospitalization Due to Adverse Drug Reactions Among People Living with HIV
Authors: Poojar Basavaraj , Kamath Ashwin , Rao Sathish B. , Ullal Sheetal Dinkar , Ramapuram John , Yadiyal Muralidhar B. , Shenoy Ashok K.
Published: October 2024

Background and Objective: The complexity of antiretroviral therapy (ART) regimens in people living with HIV (PLHIV) poses significant challenges for medication management, impacting adherence and overall health outcomes. The Medication Regimen Complexity Index (MRCI) is a tool that quantifies regimen complexity, yet its correlation with hospitalization rates and adverse drug reactions (ADRs) in PLHIV remains underexplored. Materials and Methods: This prospective study, which was conducted at a government-funded antiretroviral treatment center, investigated the relationships among MRCI scores, hospitalization due to ADRs, and the ADR rates in 285 PLHIV participants over 18 months. Results: The study revealed a significant association between higher baseline MRCI scores and hospitalization due to ADRs, with a threshold MRCI score of 8 indicating increased risk. There was no significant association between average MRCI scores and overall ADR rates or non-ADR-related hospitalizations. Conclusions: These findings emphasize the importance of monitoring medication regimen complexity in PLHIV, particularly in the context of preventing hospitalizations related to ADRs. Further research is needed to understand the multifactorial influences on ADR occurrence and to optimize ART regimens for better patient outcomes.
Fouling of Reverse Osmosis (RO) and Nanofiltration (NF) Membranes by Low Molecular Weight Organic Compounds (LMWOCs), Part 1: Fundamentals and Mechanism
Authors: Maeda Yasushi
Published: October 2024

Reverse osmosis (RO) and nanofiltration (NF) are ubiquitous technologies in modern water treatment, finding applications across various sectors. However, the availability of high-quality water suitable for RO/NF feed is diminishing due to droughts caused by global warming, increasing demand, and water pollution. As concerns grow over the depletion of precious freshwater resources, a global movement is gaining momentum to utilize previously overlooked or challenging water sources, collectively known as “marginal water”. Fouling is a serious concern when treating marginal water. In RO/NF, biofouling, organic and colloidal fouling, and scaling are particularly problematic. Of these, organic fouling, along with biofouling, has been considered difficult to manage. The major organic foulants studied are natural organic matter (NOM) for surface water and groundwater and effluent organic matter (EfOM) for municipal wastewater reuse. Polymeric substances such as sodium alginate, humic acid, and proteins have been used as model substances of EfOM. Fouling by low molecular weight organic compounds (LMWOCs) such as surfactants, phenolics, and plasticizers is known, but there have been few comprehensive reports. This review aims to shed light on fouling behavior by LMWOCs and its mechanism. LMWOC foulants reported so far are summarized, and the role of LMWOCs is also outlined for other polymeric membranes, e.g., UF, gas separation membranes, etc. Regarding the mechanism of fouling, it is explained that the fouling is caused by the strong interaction between LMWOC and the membrane, which causes the water permeation to be hindered by LMWOCs adsorbed on the membrane surface (surface fouling) and sorbed inside the membrane pores (internal fouling). Adsorption amounts and flow loss caused by the LMWOC fouling were well correlated with the octanol-water partition coefficient (log P). In part 2, countermeasures to solve this problem and applications using the LMWOCs will be outlined.
Advances in Low-Temperature Nitriding and Carburizing of Stainless Steels and Metallic Materials: Formation and Properties
Authors: Borgioli Francesca , Adachi Shinichiro , Lindner Thomas
Published: October 2024

Surface engineering techniques are currently used to overcome the limitations of metal alloys and improve their surface hardness, tribological properties, fatigue resistance and corrosion resistance in specific environments [...]
Research on the Prediction of Roll Wear in a Strip Mill
Authors: Wei Jianhua , Zhao Aimin
Published: October 2024

In the process of hot rolling silicon steel, roll wear directly affect its shape. Accurate prediction of roll wear is an important condition for rolling qualified silicon steel strips. The traditional roll wear prediction model is established by the slicing method. The wear of F5–F7 work rolls used for finishing rolling silicon steel on a 2250 mm production line in a steel mill was predicted by this model. It was found that there was deviation between the predicted results and the actual wear, and the prediction accuracy of the model was insufficient. Therefore, the wear of the surfaces of the rolls used for rolling silicon steel on this production line was studied. Based on the analysis of the work roll wear’s form and the rolling parameters that affect the roll wear, the traditional roll wear prediction model was optimized by the genetic algorithm. Finally, the optimized model was verified, and the prediction accuracy of the wear prediction model improved. The accurate prediction results provide a basis for the formulation of a shape control strategy when rolling silicon steel on this production line.
Molecular Dynamics Simulation of Temperature and Ti Volume Fraction on Compressive Properties of Ti/Al Layered Composites
Authors: Chen Shuqin , Wang Haonan , Yan Pengxiang , Li Shoufu , Zhang Huang , Zhan Haifei
Published: October 2024

Based on molecular dynamics simulation, this work investigated the influences of temperature and Ti volume fractions on the compressive deformation of Ti/Al layered composites. According to the simulation, the initial dislocations during compression are concentrated on the Al side, dominated by 1/6<211> and 1/6<112> dislocations, and the 1/2<101> and 1/6<211> dislocations cross the Ti/Al interface from the Al side to the Ti side. It is found that an increase in temperature helps dislocations to form at lower strains, which leads to a decrease in the compressive strength and an increase in the plasticity of the structure. As expected, the Ti volume fraction has a significant impact on the compressive properties of Ti/Al layered composites, and the compressive strength of the material increases with the increase in the Ti volume fraction. At temperatures above 400 K, the reduction rate of compressive strength becomes smaller, which is due to the formation of new ordered metal compounds between Ti and Al. When the volume fraction of Ti is lower than that of Al, plastic deformation mainly occurs on the Ti side, dominated by 1/6<112> dislocations. In contrast, the types of dislocations across the Ti/Al interface and on the Al side are dominated by 1/2<110> and 1/2<011>. When the Ti volume fraction becomes comparable with that of Al, the plastic deformation is transferred from the Ti side to the Al side, and the plasticity of the sample decreases. The optimal compressive properties of Ti/Al layered composites are observed at a Ti volume fraction of 40%, which provides guidance for the structural design of Ti/Al layered composites.
Causal Metabolomic and Lipidomic Analysis of Circulating Plasma Metabolites in Autism: A Comprehensive Mendelian Randomization Study with Independent Cohort Validation
Authors: Li Zhifan , Li Yanrong , Tang Xinrong , Xing Abao , Lin Jianlin , Li Junrong , Ji Junjun , Cai Tiantian , Zheng Ke , Lingampelly Sai Sachin , Li Kefeng
Published: October 2024

Background: The increasing prevalence of autism spectrum disorder (ASD) highlights the need for objective diagnostic markers and a better understanding of its pathogenesis. Metabolic differences have been observed between individuals with and without ASD, but their causal relevance remains unclear. Methods: Bidirectional two-sample Mendelian randomization (MR) was used to assess causal associations between circulating plasma metabolites and ASD using large-scale genome-wide association study (GWAS) datasets—comprising 1091 metabolites, 309 ratios, and 179 lipids—and three European autism datasets (PGC 2015: n = 10,610 and 10,263; 2017: n = 46,351). Inverse-variance weighted (IVW) and weighted median methods were employed, along with robust sensitivity and power analyses followed by independent cohort validation. Results: Higher genetically predicted levels of sphingomyelin (SM) (d17:1/16:0) (OR, 1.129; 95% CI, 1.024–1.245; p = 0.015) were causally linked to increased ASD risk. Additionally, ASD children had higher plasma creatine/carnitine ratios. These MR findings were validated in an independent US autism cohort using machine learning analysis. Conclusion: Utilizing large datasets, two MR approaches, robust sensitivity analyses, and independent validation, our novel findings provide evidence for the potential roles of metabolomics and circulating metabolites in ASD diagnosis and etiology.
Accurate Technique for the Calibration of High-Voltage Capacitance and Dissipation Factor Bridges up to 1 kHz
Authors: Agazar Mohamed , Saadeddine Hanane
Published: October 2024

This paper presents a comprehensive methodology for the precise calibration of high-voltage capacitance and dissipation factor (DF) bridges. The technique involves meticulous adjustments using a digital high-precision phase and ratio-measuring system to determine correction factors for DF and capacitance measurements. Unlike other methods that are limited to a narrow range, this approach allows calibration across the entire operational working spectrum of any bridge. While the method has been developed up to 1 kHz, its adaptability for future requirements is facilitated by the developed software. This method has been carried out by calibrating a highly accurate bridge for a capacitor ratio of up to 100, with DFs ranging from −0.01 to 0.01 and currents ranging from 0.1 mA to 1 A. Linear correction factors are established, with their accuracies being rigorously quantified. This methodology achieves expanded uncertainties as low as 3.5 µF/F (3.5 ppm) for capacitance and 2.2 × 10−⁶ for DFs, significantly enhancing measurement reliability across diverse high-voltage capacitor applications.
LDF-BNN: A Real-Time and High-Accuracy Binary Neural Network Accelerator Based on the Improved BNext
Authors: Wan Rui , Cen Rui , Zhang Dezheng , Wang Dong
Published: October 2024

Significant progress has been made in industrial defect detection due to the powerful feature extraction capabilities of deep neural networks (DNNs). However, the high computational cost and memory requirement of DNNs pose a great challenge to the deployment of industrial edge-side devices. Although traditional binary neural networks (BNNs) have the advantages of small storage space requirements, high parallel computing capability, and low power consumption, the problem of significant accuracy degradation cannot be ignored. To tackle these challenges, this paper constructs a BNN with layered data fusion mechanism (LDF-BNN) based on BNext. By introducing the above mechanism, it strives to minimize the bandwidth pressure while reducing the loss of accuracy. Furthermore, we have designed an efficient hardware accelerator architecture based on this mechanism, enhancing the performance of high-accuracy BNN models with complex network structures. Additionally, the introduction of multi-storage parallelism alleviates the limitations imposed by the internal transfer rate, thus improving the overall computational efficiency. The experimental results show that our proposed LDF-BNN outperforms other methods in the comprehensive comparison, achieving a high accuracy of 72.23%, an image processing rate of 72.6 frames per second (FPS), and 1826 giga operations per second (GOPs) on the ImageNet dataset. Meanwhile, LDF-BNN can also be well applied to defect detection dataset Mixed WM-38, achieving a high accuracy of 98.70%.
Mechanical Property of Thermoplastic Polyurethane Vascular Stents Fabricated by Fused Filament Fabrication
Authors: Zhai Yun , Sun Zezhi , Zhang Tie , Zhou Changchun , Kong Xiangpeng
Published: October 2024

Vascular stents have many applications in treating arterial stenosis and other vascular-related diseases. The ideal vascular stent for clinical application should have radial support and axial bending mechanical properties that meet the requirements of vascular deformation coordination. The materials used for vascular stents implanted in the human body should have corresponding biocompatibility to ensure that the stents do not cause coagulation, hemolysis, and other reactions in the blood. This study fabricated four types of vascular stents, including inner hexagon, arrowhead, quadrilateral, and outer hexagonal, using fused filament fabrication technology and thermoplastic polyurethane (TPU) as materials. By evaluating the effects of edge width and wall thickness on the radial support and axial bending performance, it was found that the inner hexagonal stent exhibited the best radial support and axial bending performance under the same conditions. The design and fabrication of vascular stents based on 3D printing technology have promising application prospects in personalized customized vascular repair therapy.
Probiotic Enterococcus faecium CRL 183 Inhibits Candida albicans Biofilm In Vitro
Authors: Lordello Virgínia Barreto , de Annunzio Sarah Raquel , da Silva Eliane Vale , Taranto Maria Pía , Fontana Carla Raquel , Cavallini Daniela Cardoso Umbelino
Published: October 2024

Candida albicans is the most prevalent fungal microorganism of human microbiota and one of the few fungi capable of causing diseases in humans, depending on the host’s immune defense capacity. The similarity between fungal and host cells promotes several adverse effects during antifungal pharmacotherapy, and antimicrobial resistance increase is a major concern. Therefore, the search for alternative treatments and prevention strategies is urgent. In this context, probiotic bacteria, such as the strain Enterococcus faecium CRL 183, seem to be a viable alternative with its benefits to the immune system, activity against pathogens, and safety use well-documented through in vitro, in vivo, and clinical studies. Thus, this study aimed to evaluate if this probiotic strain prevents C. albicans ATCC 90028 biofilm colonization in vitro. To test the anti-Candida activity of the probiotic strain E. faecium CRL 183, we combined polymicrobial biofilms (C. albicans + E. faecium) with different proportions of fungi: a probiotic was formed (1:1, 1:10, 1:100) during the formation (24 h) and maturation (48 h) periods of the biofilm. The results show that E. faecium established itself with C. albicans in polymicrobial biofilms without losing its cellular viability. The probiotic strain significantly antagonized (p < 0.0001) C. albicans biofilm formation (up to 99.9% reduction in 24 h) and maturation (up to 99.43% reduction in 48 h). According to these results, E. faecium CRL183 may be a promising resource to prevent the formation of fungal biofilms.
Identification of Listeria Isolates by Using a Pragmatic Multilocus Phylogenetic Analysis
Authors: Martínez-Murcia Antonio , Navarro Aaron , Miró-Pina Caridad
Published: October 2024

Species identification of Listeria isolates remained a tedious process still based on culturing methods that, in recent years, have led to the description of many species that are not even part of the genus Listeria. It is advisable to provide new precise techniques since this taxon includes two pathogens that are usually transmitted through the food chain, Listeria monocytogenes and L. ivanovii. The approach, so-called multilocus phylogenetic analysis (MLPA) that uses several concatenated housekeeping gene sequences, provides accurate and affordable classification frameworks to easily identify Listeria species by simple Sanger sequencing. Fragments of seven housekeeping genes (gyrA, cpn60, parE, recA, rpoB, atpA, and gyrB) from 218 strains of all Listeria species currently described were used to build an MLPA of the concatenated sequence, a total of 4375 bp. All isolates subjected to identification were clustered within the species of Listeria sensu stricto, L. monocytogenes, L. innocua, and L. welshimeri, and some reference strains were reclassified as L. ivanovii and L. seeligeri. Housekeeping-gene sequencing has been demonstrated to represent a pragmatic tool that can be firmly considered in food control.