bluuebunny/crossref_metadata_2025 huggingface dataset:
How Will Concrete Piles for Offshore Wind Power Be Damaged Under Seawater Erosion? Insights from a Chemical-Damage Coupling Meshless Method
Authors: Wu Caihong , Chen Bo , Wang Hao , Dai Jialin , Fan Shenghua , Yu Shuyang
Published: December 2024

Based on the background of the continuously rising global demand for clean energy, offshore wind power, as an important form of renewable energy utilization, is booming. However, the pile foundations of offshore wind turbines are subject to long-term erosion in the harsh marine environment, and the problem of corrosion damage is prominent, which seriously threatens the safe and stable operation of the wind power system. In view of this, a meshless numerical simulation method based on smoothed particle hydrodynamics (SPH) and a method for generating the concrete meso-structures are developed. Concrete pile foundation models with different aggregate contents, particle sizes, and ion concentration diffusion coefficients are established to simulate the corrosion damage processes under various conditions. The rationality of the numerical algorithm is verified by a typical example. The results show that the increase in the aggregate percentage gradually reduces the diffusion rate of chemical ions, and the early damage development also slows down. However, as time goes, the damage will still accumulate continuously; when the aggregate particle size increases, the ion diffusion becomes more difficult, the damage initiation is delayed, and the early damage is concentrated around the large aggregates. The increase in the ion diffusion coefficient significantly accelerates the ion diffusion process, promotes the earlier and faster development of damage, and significantly deepens the damage degree. The research results contribute to a deeper understanding of the corrosion damage mechanisms of pile foundations and providing important theoretical support for optimizing the durability design of pile foundations. It is of great significance for ensuring the safe operation of offshore wind power facilities, prolonging the service life, reducing maintenance costs, and promoting the sustainable development of offshore wind power.
The Effect of Absorbed Hydrogen on the Rotors of Steel Machining Products During Powerful Turbo Aggregate Repairs
Authors: Balitskii Alexander I. , Syrotyuk Andriy M. , Kolesnikov Valerii O. , Balitska Valentina O. , Ivaskevych Ljubomyr M. , Havrilyuk Maria R.
Published: December 2024

Rotor shafts are the most heavily loaded and accident-prone parts of powerful turbine generators, which are cooled using hydrogen. To eliminate damage sustained during operations, repair work was carried out, including the removal of defective parts, surfacing, and turning. This study tested the machinability of the rotor shaft using prototypes made from 38KhN3MFA steel. A section of the shaft was degraded due to prolonged operation (250 thousand hours), and compared to the central part, a decrease in the average grain size from 21.57 μm to 12.72 μm and an increase in the amount of hydrogen absorbed during operation from 2.27 to 7.54 ppm were observed. With the frequency of dry turning increasing from 200 to 315 RPM, the chips changed their form from mostly rectangular with linear dimensions of 10 to 20 mm to large spiral rings with a diameter of 15 to 20 mm and a length of more than 50 mm. Cracks of 1 to 4 mm in length were found in most chip particles at both rotational speeds. Increasing the rotational speed from 200 to 315 and up to 500 RPM led to the formation of an oxide film on the surface of the specimens, as evidenced by the appearance of oxygen during local analyses of the elemental content on the chip surface. The saturation of specimens by hydrogen gas led to the formation of finer chips compared to the non-hydrated material, and the roughness of the machined surface increased at hydrogen contents of 6 and 8 ppm. In both dry and coolant cutting operations, surface roughness reflects the degradation of the rotor shaft or experimental prototypes due to hydrogenation, which can be used to diagnose the condition of the rotor after long-term operation.
Propagation of a Fatigue Crack Through a Hole
Authors: Neto Diogo , Jesus Joel , Branco Ricardo , Sérgio Edmundo , Antunes Fernando
Published: December 2024

The stop-hole technique is a well-known strategy to extend the fatigue life of cracked components. The ability to estimate fatigue life after the hole is important for safety reasons. The objective here is to develop strategies for the accurate prediction of initiation and propagation life ahead of the stop-hole. Experimental work was developed in a Compact-Tension (CT) specimen made of 7050-T7451 aluminium alloy and with a 3 mm diameter hole. A total number of 625,000 load cycles were required to re-initiate the crack after the hole. Crack initiation life after the hole was estimated using the Theory of Critical Distances combined with the Smith–Watson–Topper parameter. A value of a0 = 31.83 µm was obtained for El Haddad parameter, which was used to define the critical distance. The predicted life was found to be only 4% lower than the experimental value. The fatigue crack growth (FCG) rate was calculated using a node release strategy, assuming that cyclic plastic deformation is the main damage mechanism and that cumulative plastic strain is the crack driving parameter. A good agreement was found between the numerical predictions of da/dN and the experimental results. The main result, however, is the proposed methodology, which allows predicting the initiation and propagation lives in notched components.
Compressive Load Capacity of Concrete Structures Made of Hollow Blocks with Voids Filled with Concrete of Various Features
Authors: Griniov Vadim , Yurkova Kseniya , Prusak Rafał
Published: December 2024

A masonry made of hollow concrete blocks in modern constructions differs from the traditional one in that the empty space (up to 70%) makes it possible to create complex high-strength load-bearing structures by filling the voids with monolithic or reinforced concrete. The aim of this study was to examine specimens of concrete structures made of hollow blocks with voids filled with concretes with various features. The research methodology is based on the results of numerical and experimental tests. Laboratory studies were conducted to determine the influence of the concrete filling on strength, deformability and the nature of destruction of the experimental specimens. The numerical analysis was performed on the basis of FEM with the use of the ANSYS 2021 R1 software. The method for determining the load capacity of multi-component structures using strain diagrams of constituent materials has been improved. There is strong agreement between the numerical and experimental results for all masonry prisms. Additionally, a good correlation was observed between the experimental results and the analytical calculations performed using the proposed methodology.
The Effect of Elastomer Content and Annealing on the Physical Properties of Upcycled Polyethylene Terephthalate-Maleated Styrene Ethylene Butylene Styrene Blends for Additive Manufacturing
Authors: Bermudez Diego , Moreno Stephanie , Roberson David A.
Published: December 2024

In the work presented here, we explore the upcycling of polyethylene terephthalate (PET) that was derived from water bottles. The material was granulated and extruded into a filament compatible with fused filament fabrication (FFF) additive manufacturing platforms. Three iterations of PET combined with a thermoplastic elastomer, styrene ethylene butylene styrene with a maleic anhydride graft (SEBS-g-MA), were made with 5, 10, and 20% by mass elastomer content. The elastomer and specific mass percentages were chosen based on prior successes involving acrylonitrile butadiene styrene (ABS), in which the maleic anhydride graft enabled compatibility between different materials. The rheological properties of PET and the PET/SEBS blends were characterized by the melt flow index and dynamic mechanical analysis. The addition of SEBS-g-MA did not have a significant impact on mechanical properties, as determined by tensile and impact testing, where all test specimens were manufactured by FFF. Delamination of the tensile specimens convoluted the ability to discern differences in the mechanical properties, particularly % elongation. Annealing of the specimens enabled the observation of the effect of elastomer content on the mechanical properties, particularly in the case of impact testing, where the impact strength increased with the increase in SEBS content. However, annealing led to shrinkage of the specimens, detracting from the realized benefits of the thermal process. Scanning electron microscopy of spent tensile specimens revealed that, in the non-annealed condition, SEBS formed nodules that would detach from the PET matrix during the tensile test, indicating that a robust bond was not present. The addition of SEBS-g-MA did allow for shape memory property characterization, where deformation of tensile specimens occurred at room temperature. Specimens from the 20% by mass elastomer content sample group exhibited a shape fixation ratio on the order of 99% and a shape recovery ratio on the order of 80%. This work demonstrates a potential waste reduction strategy to tackle the problem of polymer waste by upcycling discarded plastic into a feedstock material for additive manufacturing with shape memory properties.
Sustainable Alkali-Activated Self-Compacting Concrete for Precast Textile-Reinforced Concrete: Experimental–Statistical Modeling Approach
Authors: Kryzhanovskyi Vitalii , Orlowsky Jeanette
Published: December 2024

Industrial and construction wastes make up about half of all world wastes. In order to reduce their negative impact on the environment, it is possible to use part of them for concrete production. Using experimental–statistical modeling techniques, the combined effect of brick powder, recycling sand, and alkaline activator on fresh and hardened properties of self-compacting concrete for the production of textile-reinforced concrete was investigated. Experimental data on flowability, passing ability, spreading speed, segregation resistance, air content, and density of fresh mixtures were obtained. The standard passing ability tests were modified using a textile mesh to maximize the approximation to the real conditions of textile concrete production. To determine the dynamics of concrete strength development, compression and flexural tests at the ages of 1, 3, 7, and 28 days and splitting tensile strength tests of 28 days were conducted. The preparation technology of the investigated modified mixtures depending on the composition is presented. The resulting mathematical models allow for the optimization of concrete compositions for partial replacement of slag cement with brick powder (up to 30%), and natural sand with recycled sand (up to 100%) with the addition of an alkaline activator in the range of 0.5–1% of the cement content. This allows us to obtain sustainable, alkali-activated high-strength self-compacting recycling concrete, which significantly reduces the negative impact on the environment and promotes the development of a circular economy in the construction industry.
Thermal–Fluid–Structure Interaction Analysis of the Impact of Structural Modifications on the Stress and Flow Parameters in a Nozzle Box Made of StE460 Steel
Authors: Bryk Mateusz , Lemański Marcin , Madejski Paweł
Published: December 2024

This study explores the impact of structural modifications on the stress distribution and flow characteristics of a nozzle box in a steam turbine, specifically targeting the components made from high-strength StE460 steel. Using Computational Fluid Dynamics (CFDs) and Thermal–Fluid–Structure Interaction (Thermal–FSI) simulations, we examine the effects of shortening the nozzle guide vanes by 7 mm. This novel approach significantly reduces the stress levels within the nozzle box segments, bringing them below the critical thresholds and thus enhancing component durability. Moreover, the modification leads to improved flow efficiency, evidenced by the higher outlet velocities, temperatures, and mass flow rates, all of which contribute to increased turbine power output without negatively impacting the downstream flow dynamics. This balance between durability and flow performance underscores the value of targeted structural innovations in high-temperature, high-stress environments. This study’s findings suggest that such modifications can substantially improve turbine efficiency and operational longevity, marking an important advancement in industrial applications where reliability and efficiency are paramount. Future work will assess the long-term effects under variable operational conditions to further optimize these benefits.
Dynamic In-Plane Compression and Fracture Growth in a Quasi-Isotropic Carbon-Fiber-Reinforced Polymer Composite
Authors: Kumar Yogesh , Rezasefat Mohammad , Zaiemyekeh Zahra , Li Haoyang , Dolez Patricia , Hogan James
Published: December 2024

This study presents an experimental investigation of the quasi-static and dynamic behavior of a quasi-isotropic carbon-fiber-reinforced composite subjected to in-plane compressive loading. The experiments were performed at strain rates ranging from 4×10−5 to ∼1200 s−1 to quantifythe strain-rate-dependent response, failure propagation, and damage morphology using advanced camera systems. Fiber bridging, kink band formation, dominance of interlaminar failure, and inter-fiber failure fracture planes are evidenced through post-mortem analysis. The evolution of the in-plane compressive strength, failure strength, and stiffness are quantified across the strain rates considered in this study. For an in-depth understanding of the failure propagation, crack speeds were determined in two subsets; (i) primary and secondary cracking, and (ii) the interfaces participating in the crack propagation. Lastly, a modified Zhu–Wang–Tang viscoelastic constitutive model was used to characterize the dynamic stress-strain and compressive behavior of the quasi-isotropic composite under in-plane compression.
Application of a Gyroid Structure for Thermal Insulation in Building Construction
Authors: Anwajler Beata , Szołomicki Jerzy , Noszczyk Paweł
Published: December 2024

This paper concerns research into the use of 3D-printed gyroid structures as a modern thermal insulation material in construction. The study focuses on the analysis of open-cell gyroid structures and their effectiveness in insulating external building envelopes. Gyroid composite samples produced using DLP 3D-printing technology were tested to determine key parameters such as thermal conductivity (λ), thermal resistance (R) and heat transfer coefficient (U) according to ISO 9869-1:2014. In addition, the authors carried out a comprehensive analysis of the annual energy balance of four different residential buildings, including older and modern structures, using Arcadia software v9.0. The results showed that 100 mm-thick multi-layer gyroid structures achieve exceptionally low thermal conductivity (approximately 0.023 W/(m·K)), significantly outperforming traditional materials such as mineral wool or polystyrene foam in terms of insulation efficiency. These structures also have high mechanical strength and low density, making them both lightweight and highly durable. As a result of these properties, the structures studied represent a promising solution for designing energy-efficient buildings, effectively reducing heating energy demand and improv the overall energy balance of buildings.
Sensitivity Analysis of Factors Influencing Coal Prices in China
Authors: Lyu Jingye , Li Chong , Zhou Wenwen , Zhang Jinsuo
Published: December 2024

A scientific assessment of the sensitivity of the Chinese coal market has become an important research topic. This paper combines Gaussian Process Regression (GPR) and Sobol sensitivity analysis to construct a GPR–Sobol hybrid model innovatively applied to the Chinese coal market, thus addressing a gap in the economic applications of this method. The model is used to analyze the sensitivity of factors influencing coal prices in China. The GPR–Sobol model effectively handles nonlinear relationships, enabling an in-depth exploration of key factors affecting price volatility and quantifying their impacts, thus overcoming the limitations of traditional econometric models in nonlinear data processing. The results indicate that economic growth, energy prices, interest rates, exchange rates, and uncertainty factors exhibit high sensitivity and significantly impact coal price fluctuations in China. Coal prices in northwest China are more sensitive to interest rates and geopolitical risks, while prices in east and south China are more responsive to exchange rates but less so to economic policy uncertainty. Additionally, coal prices in north, south, and east China are highly sensitive to international energy prices, indicating that coal prices are dominated by the global energy market, yet their weak response to macroeconomic indicators suggests these regions is still insufficiently mature.
A Self-Rewarding Mechanism in Deep Reinforcement Learning for Trading Strategy Optimization
Authors: Huang Yuling , Zhou Chujin , Zhang Lin , Lu Xiaoping
Published: December 2024

Reinforcement Learning (RL) is increasingly being applied to complex decision-making tasks such as financial trading. However, designing effective reward functions remains a significant challenge. Traditional static reward functions often fail to adapt to dynamic environments, leading to inefficiencies in learning. This paper presents a novel approach, called Self-Rewarding Deep Reinforcement Learning (SRDRL), which integrates a self-rewarding network within the RL framework. The SRDRL mechanism operates in two primary phases: First, supervised learning techniques are used to learn from expert knowledge by employing advanced time-series feature extraction models, including TimesNet and WFTNet. This step refines the self-rewarding network parameters by comparing predicted rewards with expert-labeled rewards, which are based on metrics such as Min-Max, Sharpe Ratio, and Return. In the second phase, the model selects the higher value between the expert-labeled and predicted rewards as the RL reward, storing it in the replay buffer. This combination of expert knowledge and predicted rewards enhances the performance of trading strategies. The proposed implementation, called Self-Rewarding Double DQN (SRDDQN), demonstrates that the self-rewarding mechanism improves learning and optimizes trading decisions. Experiments conducted on datasets including DJI, IXIC, and SP500 show that SRDDQN achieves a cumulative return of 1124.23% on the IXIC dataset, significantly outperforming the next best method, Fire (DQN-HER), which achieved 51.87%. SRDDQN also enhances the stability and efficiency of trading strategies, providing notable improvements over traditional RL methods. The integration of a self-rewarding mechanism within RL addresses a critical limitation in reward function design and offers a scalable, adaptable solution for complex, dynamic trading environments.
A New Class of Bivariate Distributions: Properties, Estimation, and Modeling
Authors: Darwish Jumanah Ahmed , Shahbaz Saman Hanif , Shahbaz Muhammad Qaiser
Published: December 2024

The development of bivariate distributions is a challenging area of research, and a novel class of bivariate distributions is proposed in this paper. Certain useful mathematical characteristics of the proposed class of bivariate distributions are explored in general. These properties include the joint and conditional and joint survival function moments and measures of dependence. The parameters of the proposed class of distributions are estimated using the maximum likelihood method of estimation. A multivariate version of the proposed class is also proposed, and some necessary properties are discussed. The multivariate dependence measures are obtained for the proposed multivariate class of distributions. A new bivariate power function distribution is proposed using the power function distribution as a baseline distribution in the proposed bivariate class. Some useful properties of the proposed bivariate distribution are studied. The parameters of the proposed bivariate distribution are estimated using the maximum likelihood method. An extensive simulation study has been conducted to see the performance of the estimation method. The new bivariate power function distribution is used to model some real data.
On Diophantine Equations 2x ± (2kp)y = z2 and −2x + (2k3)y = z2
Authors: Li Yuan , Lloyd Torre , Clinton Angel
Published: December 2024

In this paper, we solve three Diophantine equations: 2x±(2kp)y=z2 and −2x+(2k3)y=z2 with k≥0 and prime p≡±3(mod8). We obtain all the non-negative integer solutions by using elementary methods and the database of elliptic curves in “The L-functions and modular forms database” (LMFDB).
A Navigation Algorithm Based on the Reinforcement Learning Reward System and Optimised with Genetic Algorithm
Authors: Cabezas-Olivenza Mireya , Zulueta Ekaitz , Azurmendi-Marquinez Iker , Fernandez-Gamiz Unai , Rico-Melgosa Danel
Published: December 2024

Regarding autonomous vehicle navigation, reinforcement learning is a technique that has demonstrated significant results. Nevertheless, it is a technique with a high number of parameters that need to be optimised without prior information, and correctly performing this is a complicated task. In this research study, a system based on the principles of reinforcement learning, specifically on the concept of rewards, is presented. A mathematical expression was proposed to control the vehicle’s direction based on its position, the obstacles in the environment and the destination. In this equation proposal, there was only one unknown parameter that regulated the degree of the action to be taken, and this was optimised through the genetic algorithm. In this way, a less computationally expensive navigation algorithm was presented, as it avoided the use of neural networks. The controller’s time to obtain the navigation instructions was around 6.201·10−4 s. This algorithm is an efficient and accurate system which manages not to collide with obstacles and to reach the destination from any position. Moreover, in most cases, it has been found that the proposed navigations are also optimal.
Fuzzy Rough Set Models Based on Fuzzy Similarity Relation and Information Granularity in Multi-Source Mixed Information Systems
Authors: Zhang Pengfei , Zhao Yuxin , Wang Dexian , Zhang Yujie , Yu Zheng
Published: December 2024

As a pivotal research method in the field of granular computing (GrC), fuzzy rough sets (FRSs) have garnered significant attention due to their successful overcoming of the limitations of traditional rough sets in handling continuous data. This paper is dedicated to exploring the application potential of FRS models within the framework of multi-source complex information systems, which undoubtedly holds profound research significance. Firstly, a novel multi-source mixed information system (MsMIS), encompassing five distinct data types, is introduced, thereby enriching the dimensions of data processing. Subsequently, a similarity function, designed based on the unique attributes of the data, is utilized to accurately quantify the similarity relations among objects. Building on this foundation, fuzzy T-norm operators are employed to integrate the similarity matrices derived from different data types into a cohesive whole. This integration not only lays a solid foundation for subsequent model construction but also highlights the value of multi-source information fusion in the analysis of the MsMIS. The integrated results are subsequently utilized to develop FRS models. Through rigorous examination from the perspective of information granularity, the rationality of the FRS model is proven, and its mathematical properties are explored. This paper contributes to the theoretical advancement of FRS models in GrC and offers promising prospects for their practical implementation.
An Integrated Algorithm with Feature Selection, Data Augmentation, and XGBoost for Ovarian Cancer
Authors: Cai Jingxun , Lee Zne-Jung , Lin Zhihxian , Hsu Chih-Hung , Lin Yun
Published: December 2024

Ovarian cancer is one of the most aggressive gynecological cancers due to its high invasion and chemoresistance. It not only has a high incidence rate but also tops the list of mortality rates. Its subtle early symptoms make subsequent diagnosis difficult, significantly delaying timely treatment for patients. Once ovarian cancer reaches an advanced stage, the complexity and difficulty of treatment increase substantially, affecting patient survival rates. Therefore, it is crucial for both medical professionals and patients to remain highly vigilant about the early signs of ovarian cancer to ensure timely intervention. In recent years, ovarian cancer prediction research has advanced, allowing for the analysis of the likelihood and type of cancer based on patients’ genetic data. With the rapid development of machine learning, numerous efficient classification prediction models have emerged. These new technologies offer significant opportunities and potential for developing ovarian cancer diagnostic prediction methods. However, traditional approaches often struggle to achieve satisfactory classification accuracy in high-dimensional genetic datasets with small sample sizes. This research offers a prediction model utilizing genomic data to enhance the early diagnosis rate of ovarian cancer, incorporating feature selection, data augmentation through adversarial conditional generative adversarial networks (AC-GAN), and an extreme gradient boosting (XGBoost) classifier. First, we can simplify the original genetic dataset through feature selection methods, removing irrelevant variables and noise, thereby improving the model’s predictive accuracy. Following dimensionality reduction, AC-GAN enriches the data, producing more realistic genetic samples to enhance the model’s generalization capacity. Finally, the XGBoost classifier is applied to classify the augmented data, achieving efficient predictions for ovarian cancer. These research findings strongly demonstrate that the diagnostic method proposed in this paper has a significant advantage in the predictive diagnosis of ovarian cancer, with an accuracy of 99.01% that surpasses the current technologies in use. Additionally, the algorithm identifies twelve genes highly relevant to ovarian cancer, providing valuable insights for physicians during diagnosis.
The CaO Enhanced Defluorination and Air-Jet Separation of Cathode-Active Material Coating for Direct Recycling Li-Ion Battery Electrodes
Authors: Siwak Piotr , Leshchynsky Volf , Strumban Emil , Pantea Mircea , Garbiec Dariusz , Maev Roman
Published: December 2024

With the rapid growth of the lithium-ion battery (LIBs) market, recycling and re-using end-of-life LIBs to reclaim the critical Li, Co, Ni, and Mn has become an urgent task. Presently, high temperature, strong acid, and alkali conditions are required to extract blended critical metals (CM) from the typical battery cathode. Hence, there is a need for more effective recycling processes for recycling blended Li, Co, Ni, and their direct regeneration for re-use in LIBs. The goal of the offered paper is the development of recycling technology for degraded battery cathode-active materials based on the thermal decomposition of polyvinylidene fluoride (PVDF) using calcination and air-jet stripping of active materials. The proposed air-jet erosion method of calcined cathode material stripping from Al foil allows for the flexible industry-applicable separation process, which is damage-free for both particles and substrate. The CaO calcination air-jet separation process and equipment can significantly improve the PVDF decomposition and the separation efficiency of the cathode materials. It is demonstrated that low-temperature CaO calcination at 350–450 °C associated with air-jet separation of active material is characterized by low environmental impact, high purity of the recycled material, and low cost as compared to pyro- and hydrometallurgical methods.
Editorial for the Topic: MEMS in Italy
Authors: Corigliano Alberto
Published: December 2024

Microsystems or microelectromechanical systems (MEMSs) over the last thirty years have seen impressive development in terms of potentialities and diffusion [...]
Respiratory Flora Intervention: A New Strategy for the Prevention and Treatment of Occupationally Related Respiratory Allergy in Healthcare Workers
Authors: Gao Linglin , Chen Xi , Jiang Ziyi , Zhu Jie , Wang Qiang
Published: December 2024

Occupational allergic respiratory disease in healthcare workers due to occupational exposure has received widespread attention. At the same time, evidence of altered respiratory flora associated with the development of allergy has been found in relevant epidemiologic studies. It is of concern that the composition of nasopharyngeal flora in healthcare workers differs significantly from that of non-healthcare workers due to occupational factors, with a particularly high prevalence of carriage of pathogenic and drug-resistant bacteria. Recent studies have found that interventions with upper respiratory tract probiotics can significantly reduce the incidence of respiratory allergies and infections. We searched PubMed and other databases to describe the burden of allergic respiratory disease and altered respiratory flora in healthcare workers in this narrative review, and we summarize the mechanisms and current state of clinical research on the use of flora interventions to ameliorate respiratory allergy, with the aim of providing a new direction for protecting the respiratory health of healthcare workers.
Proline Improves Pullulan Biosynthesis Under High Sugar Stress Condition
Authors: Liu Keyi , Wang Junqing , Li Feng , Wang Ruiming , Zeng Qingming , Zhang Zhenxing , Liu Hongwei , Li Piwu
Published: December 2024

Pullulan is an extracellular polysaccharide produced via the fermentation of Aureobasidium pullulans. However, high sugar concentrations and hyperosmotic stress limit pullulan biosynthesis during the fermentation process. Therefore, we investigated the effects of proline supplementation on A. pullulans growth and pullulan biosynthesis under high sugar and hyperosmotic stress using physiological, biochemical, and transcriptomic analyses. High sugar concentrations significantly inhibited A. pullulans growth and pullulan biosynthesis. High sugar and hyperosmotic stress conditions significantly increased intracellular proline content in A. pullulans. However, treatment with proline (400 mg/L proline) significantly increased biomass and pullulan yield by 10.75% and 30.06% (174.8 g/L), respectively, compared with those in the control group. To further investigate the effect of proline on the fermentation process, we performed scanning electron microscopy and examined the activities of key fermentation enzymes. Proline treatment preserved cell integrity and upregulated the activities of key enzymes involved in pullulan biosynthesis. Transcriptome analysis revealed that most differentially expressed genes in the proline group were associated with metabolic pathways, including glycolysis/gluconeogenesis, pyruvate metabolism, and sulfur metabolism. Conclusively, proline supplementation protects A. pullulans against high sugar and hyperosmotic stress, providing a new theoretical basis and strategy for the efficient industrial production of pullulans.
Trypanosoma cruzi DNA Identification in Breast Milk from Mexican Women with Chagas Disease
Authors: Crisóstomo-Vázquez María del Pilar , Rodríguez-Martínez Griselda , Jiménez-Rojas Verónica , Eligio-García Leticia , Reyes-López Alfonso , Hernández-Ramírez María , Hernández-Juárez Francisco , Romero-Zamora José Luis , Vivanco-Tellez Silvia Guadalupe , Solorzano-Santos Fortino , Luna-Pineda Victor M. , Campos-Valdez Guillermina
Published: December 2024

(1) Background: Chagas disease is a public health problem affecting nearly 2 million women of reproductive age in Latin America. From these, 4–8% can transmit the infection to the foetus through the vertical route, whereas horizontal transmission through milk during breastfeeding remains controversial. Therefore, the presence of Trypanosoma cruzi (T. cruzi) DNA in the milk of women seropositive for Chagas disease was analysed to determine whether a relationship with the infection of their children can exist. (2) Methods: 260 pairs (mother–child) from four hospitals located in rural areas endemic to T. cruzi (state of Oaxaca) were studied. The presence of anti-T. cruzi antibodies in the serum of lactating women were determined by ELISA, whereas parasitic DNA in either breast milk or newborn’s blood was identified by PCR; (3) Results: The seroprevalence of infection in lactating women was 5.76%, and the frequency of infection detected by PCR in breast milk was 1.92%, while the frequency of infection in the blood of newborns was 1.92%. Pochutla-Oaxaca presented the highest number of positive cases in both breast milk and blood. The only risk factor found was the presence of the vector in the geographical area analysed, favouring the parasite’s transmission. Overall, the results suggest a probable transmission of T. cruzi, although whether it was through breastfeeding or through the blood during delivery could not be determined. (4) Conclusions: T. cruzi DNA was identified in lactating women’s milk and newborn blood, which is probable evidence of transmission through breastfeeding; nevertheless, future studies must be performed to confirm the presence of the parasite, alive or dead.
Transcriptome Analysis of the Harmful Dinoflagellate Heterocapsa bohaiensis Under Varied Nutrient Stress Conditions
Authors: Peng Peng , Han Fangxin , Gong Xue , Guo Xiangyuan , Su Ying , Zhang Yiwen , Zhan Jingjing
Published: December 2024

The increasing prevalence of harmful algal blooms (HABs) driven by eutrophication, particularly in China’s nearshore waters, is a growing concern. Dinoflagellate Heterocapsa bohaiensis blooms have caused significant ecological and economic damage, as well as mass mortality, in cultivated species. Nutrients are one of the primary inducers of H. bohaiensis blooms. However, the transcriptomic studies of H. bohaiensis remain sparse, and its metabolic pathways are unknown. This study analyzed the transcriptome of H. bohaiensis under varying nutrient conditions (nitrogen at 128, 512, and 880 μM; phosphate at 8, 6, and 32 μM), focusing on differential gene expression. The results indicated that deviations in nutrient conditions (higher or lower N:P ratios) led to a higher number of differentially expressed genes compared to the control (N:P ratios = 27.5), thereby underscoring their pivotal role in growth. Gene Ontology (GO) enrichment analyses showed that nutrient limitation upregulated the biosynthesis and catabolism processes while downregulating the cell cycle and division functions. The Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that, under nitrogen limitation, the proteasome pathways were upregulated, while photosynthesis and carbon fixation were downregulated; under phosphorus limitation, the proteasome pathways were upregulated and nitrogen metabolism was downregulated. These findings suggest that H. bohaiensis adapts to nutrient stress by adjusting its metabolic processes.
Gram Negative Biofilms: Structural and Functional Responses to Destruction by Antibiotic-Loaded Mixed Polymeric Micelles
Authors: Damyanova Tsvetozara , Stancheva Rumena , Leseva Milena N. , Dimitrova Petya A. , Paunova-Krasteva Tsvetelina , Borisova Dayana , Kamenova Katya , Petrov Petar D. , Veleva Ralitsa , Zhivkova Ivelina , Topouzova-Hristova Tanya , Haladjova Emi , Stoitsova Stoyanka
Published: December 2024

Biofilms are a well-known multifactorial virulence factor with a pivotal role in chronic bacterial infections. Their pathogenicity is determined by the combination of strain-specific mechanisms of virulence and the biofilm extracellular matrix (ECM) protecting the bacteria from the host immune defense and the action of antibacterials. The successful antibiofilm agents should combine antibacterial activity and good biocompatibility with the capacity to penetrate through the ECM. The objective of the study is the elaboration of biofilm-ECM-destructive drug delivery systems: mixed polymeric micelles (MPMs) based on a cationic poly(2-(dimethylamino)ethyl methacrylate)-b-poly(ε-caprolactone)-b-poly(2-(dimethylamino)ethyl methacrylate) (PDMAEMA35-b-PCL70-b-PDMAEMA35) and a non-ionic poly(ethylene oxide)-b-poly(propylene oxide)-b-poly(ethylene oxide) (PEO100-b-PPO65-b-PEO100) triblock copolymers, loaded with ciprofloxacin or azithromycin. The MPMs were applied on 24 h pre-formed biofilms of Escherichia coli and Pseudomonas aeruginosa (laboratory strains and clinical isolates). The results showed that the MPMs were able to destruct the biofilms, and the viability experiments supported drug delivery. The biofilm response to the MPMs loaded with the two antibiotics revealed two distinct patterns of action. These were registered on the level of both bacterial cell-structural alterations (demonstrated by scanning electron microscopy) and the interaction with host tissues (ex vivo biofilm infection model on skin samples with tests on nitric oxide and interleukin (IL)-17A production).
LA-ICP-MS Trace Element Characteristics and Geological Significance of Stibnite in the Zhaxikang Pb–Zn–Ag–Sb Deposit, Southern Tibet, SW China
Authors: Qiu Zijun , Wu Jinchao , Voudouris Panagiotis , Tombros Stylianos , Liu Jiajun , Zhai Degao
Published: December 2024

Discovered within the North Himalayan Metallogenic Belt (NHMB), the Zhaxikang Pb–Zn–Ag–Sb deposit stands as the sole super-large scale ore deposit in the region. This deposit holds significant quantities of Pb and Zn (2.066 million tons at 6.38% average grade), Ag (2661 tons at an average of 101.64 g/t), and Sb (0.235 million tons at 1.14% average grade), making it one of China’s foremost Sb–polymetallic deposits. Stibnite represents the main carrier of Sb in this deposit and has been of great attention since its initial discovery. However, the trace element composition of stibnite in the Zhaxikang deposit has not yet been determined. This study carried out an analysis of the distribution patterns and substitution processes of trace elements within stibnite gathered from the Zhaxikang deposit, aiming to provide crucial information on ore-forming processes. Utilizing high-precision laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS), we discovered that the studied stibnite is notably enriched in arsenic (~100 ppm) and lead (~10 ppm). Furthermore, the notably consistent time-resolved profiles suggest that elements such as Fe, Cu, As, In, Sn, Hg, and Pb predominantly exist as solid solutions within stibnite. Consequently, it is probable that the enrichment of Cu, Pb, and Sn in stibnite is due to isomorphic substitution reactions, including 3Pb2+↔2Sb3+, Cu+ + Pb2+↔Sb3+, and In3+ + Sn3+↔2Sb3+. Apart from that, Mn, Pb, and Hg with the spiky signals indicate their existence within stibnite as micro-inclusions. Overall, we found that the trace element substitutions in stibnite from the Zhaxikang Pb–Zn–Ag–Sb deposit are complicated. Incorporations of trace elements such as Pb, Cu, and In into stibnite are largely influenced by a variety of factors. The simple lattice structure and constant trace elements in studied stibnite indicate a low-temperature hydrothermal system and a relatively stable process for stibnite formation.
Generation of Pre-Caldera Qixiangzhan and Syn-Caldera Millennium Rhyolites from Changbaishan Volcano by Shallow Remelting: Evidence from Zircon Hf–O Isotopes
Authors: Zou Haibo , Tong Jie
Published: December 2024

The Changbaishan volcano is well known for its major caldera-forming Millennium Eruption (ME) in 946 CE (Common Era). We report Hf–O isotopes of zircon grains from pre-caldera Qixiangzhan (QXZ) and syn-caldera eruptions of the Changbaishan (Baitoushan) volcano to constrain magma chamber processes. Zircon grains from the pre-caldera QXZ comendite lavas have δ18O ranging from 4.46 to 5.16 (lower than mantle values) and εHf ranging from −4.47 to +4.37. Zircon grains from the syn-caldera ME1 charcoal-bearing non-welded comendite pyroclastic flow deposits have δ18O ranging from 2.25 (lower than mantle values) to 5.51 and εHf from −3.75 to +3.31. By comparison, zircon grains from the ME2 welded trachytes have δ18O ranging from 5.66 to 6.20 (higher than mantle zircon values) and εHf from −1.97 to +6.23. There are no correlations between O and Hf isotopes for all zircon grains in QXZ and ME1 comendites and ME2 trachyte. The ubiquitous occurrence of low-δ18O zircon grains in QXZ and ME1 comendites indicates shallow remelting of hydrothermally altered low-δ18O juvenile rocks. By contrast, ME2 trachyte zircons (except for two zircon grains) have normal δ18O (5.66 to 6.10) values, indicating a lack of remelting processes. Similar zircon Hf–O isotopes between pre-caldera QXZ comendites and syn-caldera ME1 comendites indicate tapping of the upper portion of a zoned magma chamber. Higher δ18O in ME2 trachyte zircons indicate tapping of the deeper portion of a zoned magma chamber free from shallow remelting. The lack of significant correlations between zircon O and Hf isotopes, and the relatively high εHf values for all Changbai zircon grains, argue against partial melting of ancient continental crust or significant contaminations by ancient crustal rocks as an origin for these felsic magmas. The QXZ and ME1 comendites were formed by shallow remelting of hydrothermally altered juvenile volcanic rocks, and ME2 trachytes were formed by evolution of mantle-derived basaltic magmas free of hydrothermal assimilations. A proto-caldera likely formed prior to the generation of QXZ lavas at 10 ka.
Interaction Between Nonionic Surfactants and Alkyl Amidoamine Cationic Collector in the Reverse Flotation of Iron Ore
Authors: Junior José Tadeu Gouvêa , Silvas Flávia Paulucci Cianga , Bittencourt Christian Lariguet Taques , de Morais Vantuir Jorge , Neisiani Ali Asimi , de Salles Leal Filho Laurindo
Published: December 2024

This paper evaluates the performance of four ethoxylated nonionic surfactants (nonyl phenol vs. C13 alcohols) to act as ancillary collectors with Alkyl Amidoamine (AAA) in the reverse flotation of quartz at pH8 to concentrate iron ores. Compared to 100% AAA, the blend composed of 80% AAA (Flotinor®5530) plus 20% of isotridecyl alcohol ethoxylated with five groups of ethylene oxide (DP-210 RO) improved quartz recovery (from 54% to 63%, p < 0.05) by increasing contact angle (from 55° to 56°, p < 0.05) and decreasing induction time (26 ms to 23 ms, p < 0.05). Compared to 100% AAA (200 g/t), the blend (160 g/t of AAA + 40 g/t of DP-210 RO) improved the flotation performance of iron ore, yielding richer hematite concentrate (65.3% Fe × 61.4% Fe) and less contaminated with quartz (4% SiO2 × 10.2% SiO2), coupled with an increase in Fe recovery from 79.8% × 81.6% in the sunken product as well as SiO2 recovery from 91.7% to 96.9% in the froth. Results from zeta potential, the hydrodynamic diameter of reagent droplets, and the surface tension of the solution provide insights into the synergism between AAA and DP-210 RO.
The Crystal Chemistry and Structure of V-Bearing Silicocarnotite from Andradite–Gehlenite–Pseudowollastonite Paralava of the Hatrurim Complex, Israel
Authors: Galuskin Evgeny V. , Galuskina Irina O. , Książek Maria , Kusz Joachim , Vapnik Yevgeny , Zieliński Grzegorz
Published: December 2024

Silicocarnotite, Ca5[(PO4)(SiO4)](PO4), was first described from slag over 140 years ago. In 2013, it was officially recognised as a mineral after being discovered in the larnite–gehlenite hornfels of the pyrometamorphic Hatrurim Complex. This paper describes the composition and structure of V-bearing silicocarnotite, crystals of which were found in a thin paralava vein cutting through the gehlenite hornfels. A network of thin paralava veins a few centimetres thick is widespread in the gehlenite hornfels of the Hatrurim Basin, Negev Desert, Israel. These veins, typically coarse crystalline rock and traditionally referred to as paralava, have a symmetrical structure and do not contain glass. Silicocarnotite in the paralava, whose primary rock-forming minerals are gehlenite, flamite, Ti-bearing andradite, rankinite and pseudowollastonite, was a relatively late-stage high-temperature mineral, crystallising at temperatures above 1100 °C. It formed from the reaction of a Si-rich residual melt with pre-existing fluorapatite. A single-crystal structural study of silicocarnotite (Pnma, a = 6.72970(12) Å, b = 15.5109(3) Å, c = 10.1147(2) Å) suggests that the phenomenon of Ca1 position splitting observed in this mineral is most likely related to the partial ordering of Si and P in the T2O4 tetrahedrons. Raman studies of silicocarnotite with varying vanadium content have shown that phases with V2O5 content of 3–5 wt.% exhibit additional bands at approximately 864 cm−1, corresponding to vibrations of ν1(VO4)3−.
Adsorption of Methylene Blue on Activated Carbon Surfaces Obtained by Shock Compression of Graphite Using Reactive Molecular Dynamics
Authors: Panczyk Tomasz , Wolski Pawel , Nieszporek Krzysztof , Pietrzak Robert
Published: December 2024

This study explores the formation of functionalized carbon surfaces through shock compression of graphite in the presence of water, modeled using molecular dynamics and the ReaxFF reactive force field. The shock compression method produces activated carbon with surface functionalities, primarily hydroxyl groups, and varying morphological properties. Two approaches, unidirectional and isotropic compression, yield distinct surface structures: the former preserves a relatively flat surface, while the latter generates corrugated features with valleys and ridges. These features significantly impact the adsorption properties of methylene blue (MB), a commonly used dye. Simulations reveal that MB molecules are highly mobile on flat surfaces, aligning with a mobile adsorption model. However, on corrugated surfaces, MB exhibits localized adsorption, with the deepest valleys effectively immobilizing the dye molecules. Additionally, the study highlights the influence of surface hydroxyl groups, which, through interactions with water molecules, prevent MB from occupying these regions. The findings underscore that traditional adsorption models may not fully capture the dynamics of MB adsorption on activated carbons with complex morphologies. These insights are critical for advancing carbon-based adsorbents in water purification applications.