bluuebunny/crossref_metadata_2025 huggingface dataset:
Adoption of Multiphase and Variable Flux Motors in Automotive Applications
Authors: Arribas Beñat , Almandoz Gaizka , Egea Aritz , Madina Patxi , Iturbe Ion
Published: November 2024

This paper investigates the incorporation of multiphase (MP) and variable flux (VF) permanent magnet motors to electric vehicles (EVs). A literature review is carried out first, which covers the characteristics, benefits and challenges of both motor configurations. MP motors, with their increased phase number, offer enhanced fault tolerance, reduced torque ripple, and improved efficiency, among other benefits. VF technology allows for dynamic adjustment of the magnetic field, optimising motor performance across various operating conditions. By integrating these technologies, this study aims to harness the benefits of both MP configurations and VF capabilities. For this reason, the Finite Element Method (FEM) is used with three-phase, MP, VF, and VF-MP motors. The main contribution is that both technologies have been implemented in a single motor to evaluate and quantify their impact together, obtaining higher torque and constant power values, lower torque ripples, and higher efficiencies in the whole working range.
The Applications and Challenges of Digital Twin Technology in Smart Grids: A Comprehensive Review
Authors: Mchirgui Nabil , Quadar Nordine , Kraiem Habib , Lakhssassi Ahmed
Published: November 2024

This comprehensive review explores the applications and challenges of Digital Twin (DT) technology in smart grids. As power grid systems rapidly evolve to meet the increasing energy demands and the new requirements of renewable source integration, DTs offer promising solutions to enhance the monitoring, control, and optimization of these systems. In this paper, we examine the concept of DTs in the context of smart grids, and their requirements, challenges, and integration with the Internet of Things (IoT) and Artificial Intelligence (AI). We also discuss different applications in asset management, system operation, and disaster response. This paper analyzes current challenges, including data management, interoperability, cost, and ethical considerations. Through case studies from various sectors in Canada, we illustrate the real-world implementation and impact of DTs. Finally, we discuss emerging trends and future directions, highlighting the potential of DTs to revolutionize smart grid networks and contribute to more efficient, reliable, and sustainable power systems.
Analysis of the Existing Air Emissions Detection Methods for Stationary Pollution Sources Monitoring
Authors: Neftissov Alexandr , Biloshchytskyi Andrii , Kazambayev Ilyas , Kirichenko Lalita , Zhalmagambetova Ultuar , Biloshchytska Svitlana
Published: November 2024

The application of coal technologies for energy generation leads to high pollutant emissions. Thus, governmental and international organizations have created new programs and laws for monitoring emissions. Recently, the government of Kazakhstan has introduced regulations for the measurement of emissions produced by factories and power plants. However, the requirements and Corecommendations for the monitoring methods have not been defined. Therefore, this article addresses the problem and focuses on determining the measurement errors made by optical SGK510 and electrochemical POLAR devices used for coal power plants. The hypothesis is based on the fact that there are currently no systems for monitoring probe drying, and its implementation is expensive. The main methods are analyzed, namely their operation, taking into account the presence of water particles in samples, and the possibility of using adjustment coefficients is considered. The main pollutants chosen for analysis are CO, NO, NO2, NOx, SO2, and O2. Using the Broich–Pagan test, homoscedasticity was determined, and the Fisher test showed the possibility of using tuning coefficients. The data for the optical method were compared to measurements taken using Inspector 500. The error for SO2 determination was 7.19% for NO, 44.0985% for NO2, 733.26% for NOx, 7.39% for O2, 2.75% for CO, 60.81%. The comparison between SGK510 and POLAR demonstrated the following errors: for CO—1.5%, for NOx—82.4405%, for SO2—41.17%, for O2—11.61%. According to the Fisher criteria analysis of the optical method, only SO2 and CO values measured by SGK510 in comparison to Inspector 500 had close similarity, while others demonstrated high deviations. The significance tests were carried out by Fisher’s, t-test, and ANOVA methods. For the electrochemical measurement, only CO values had close similarity. In the future, methods will be proposed to improve the accuracy of the system while reducing maintenance costs, as well as cleaning sampling systems. The multicomponent analysis application for accuracy improvement with the exhaust gas humidity, temperature, and flow consideration was recommended as a possible solution.
Trajectory Control Approach for Single-Stage Soft-Switching Grid-Tied Inverters
Authors: Baek Seunghun
Published: November 2024

This paper presents a trajectory control model using finite state machines for a single-stage soft-switching grid-tied inverter designed with a fast dynamic response. The targeted application is a module-integrated inverter for a single photovoltaic (PV) panel which interfaces distributed energy sources with the grid. To minimize switching lossd provide advanced grid-connected functionality, the soft-switching operation is achieved through a resonant filter using a trajectory control scheme. In recent years, controllers based on digital signal processing platforms have been able to handle complex and high-speed control algorithms with precision for real-time control. In real-time control applications, the finite state machine (FSM) approach enhances responsiveness by minimizing latency with limited memory resources by executing rapid state transitions. The proposed model effectively manages the switching states of the single-stage soft-switching inverters during complex DC/AC bidirectional operations. By directly controlling the energy within the series resonant circuit, the model delivers a fast transient response while minimizing switching actions across all quadrants of operation. The control scheme has been digitally implemented on a Texas Instruments (TI) digital signal processor and validated through Hardware-In-the-Loop (HIL) testing.
Spatio-Temporal Variability of Water Temperature of Arctic Rivers in Russia over the Past 60 Years
Authors: Vasilenko Alexander , Frolova Natalia , Grigoriev Vadim Yu , Magritsky Dmitry , Shevchenko Artem , Winde Frank
Published: November 2024

This article presents the findings of a comprehensive statistical analysis based on one of the largest and most up-to-date datasets on average monthly water temperatures at 286 hydrological stations from 1961 to 2021. Through this analysis, a detailed examination of the factors influencing temperature formation in different landscape-diverse regions in the Russian Arctic has been conducted. It has been determined that air temperature plays a crucial role in determining water temperature, although its influence is constrained by geographical factors, primarily geographical latitude. An analysis of discontinuities in uniformity and the presence of trends was carried out, along with a regression analysis of the relationships between air and water temperatures. The results of estimating changes in river water temperature were simultaneously compared both with respect to generally accepted climatic periods (1961–1990 and 1991–2020) and with respect to revealed change point years. The results of the statistical analysis indicate a relatively slow increase in water temperature in the Arctic rivers of Russia over the past 60 years, by 0.11–0.74 K/decade. These changes are mainly due to changes in air temperature (about 70% of cases), which in turn are influenced by the altitude of the location of the objects and other local factors.
Efficient Trans-Dimensional Bayesian Inversion of C-Response Data from Geomagnetic Observatory and Satellite Magnetic Data
Authors: Guo Rongwen , Tian Shengqi , Liu Jianxin , Cui Yi-an , Cao Chuanghua
Published: November 2024

To investigate deep Earth information, researchers often utilize geomagnetic observatories and satellite data to obtain the conversion function of geomagnetic sounding, C-response data, and employ traditional inversion techniques to reconstruct subsurface structures. However, the traditional gradient-based inversion produces geophysical models with artificial structure constraint enforced subjectively to guarantee a unique solution. This method typically requires the model parameterization knowledge a priori (e.g., based on personal preference) without uncertainty estimation. In this paper, we apply an efficient trans-dimensional (trans-D) Bayesian algorithm to invert C-response data from observatory and satellite geomagnetic data for the electrical conductivity structure of the Earth’s mantle, with the model parameterization treated as unknown and determined by the data. In trans-D Bayesian inversion, the posterior probability density (PPD) represents a complete inversion solution, based on which useful inversion inferences about the model can be made with the requirement of high-dimensional integration of PPD. This is realized by an efficient reversible-jump Markov-chain Monte Carlo (rjMcMC) sampling algorithm based on the birth/death scheme. Within the trans-D Bayesian algorithm, the model parameter is perturbated in the principal-component parameter space to minimize the effect of inter-parameter correlations and improve the sampling efficiency. A parallel tempering scheme is applied to guarantee the complete sampling of the multiple model space. Firstly, the trans-D Bayesian inversion is applied to invert C-response data from two synthetic models to examine the resolution of the model structure constrained by the data. Then, C-response data from geomagnetic satellites and observatories are inverted to recover the global averaged mantle conductivity structure and the local mantle structure with quantitative uncertainty estimation, which is consistent with the data.
Application of the Insect Cell-Baculovirus Expression Vector System in Adeno-Associated Viral Production
Authors: Wang Fei , Sun Jiawen , Guo Wenyan , Wu Yang
Published: November 2024

Insect Cell-Baculovirus Expression Vector System (IC-BEVS) is an efficient protein expression platform, which is famous for its high-level expression of complex protein in insect cells. The system is based on baculoviruses such as Autographa californica multiple nucleopolyhedrovirus (AcMNPV), and the expression efficiency of the target proteins has been significantly improved by optimizing the viral vectors and cell lines. In recent years, IC-BEVS have shown great potential for Adeno-Associated Virus (AAV) production, particularly excelling in AAV structural protein expression and recombinant AAV production. The system not only improves the yield and purity of AAV, but also shortens the production cycle, providing an efficient and reliable tool for gene therapy. However, the system also has some challenges, including protein modification differences, limitations in expression levels, and production costs. This paper reviews the development of the insect baculovirus expression system, its application in AAV production, and its prospects in gene therapy, aiming to provide a systematic reference and outlook for research in related fields.
MAMRS: Mining Automatic Meter Reading System Based on Improved Deep Learning Algorithm Using Quadruped Robots
Authors: Chen Linxingzi , Peng Pingan , Wang Liguan
Published: November 2024

The meter reading work in the power distribution room of a mine is traditionally carried out by manual inspection, which requires several workers and often lacks timeliness and efficiency. Owing to the widespread use of quadruped robots, this paper proposes a Mining Automatic Meter Reading System, named MAMRS, to identify and read pointer and digital meters in mine distribution rooms using quadruped robots. The new method consists of three stages. Initially, this technique identifies the type of meter using the ResNet18 convolutional neural network model, then proceeds to extract the dial area image using the YOLOv5 object detection algorithm, and finally reads the pointer and digital meters’ data using the U2-net algorithm and SVM, respectively. Experimental results show that the recognition accuracy rates for meter classification, pointer meter reading, and digital meter reading are 99.87%, 85.35%, and 90.73%, respectively. The MAMRS fulfills the need for fully automated and intelligent inspection of mine distribution rooms, resulting in significantly enhanced accuracy, flexibility, and innovation in inspection processes. Moreover, it reduces labor costs and improves inspection efficiency. The findings of this study serve as a reliable reference for intelligent inspection practices in the power distribution rooms of metal mines.
Challenges in Singapore Aquaculture and Possible Solutions
Authors: Vij Shubha , Lee Yeng Sheng , Purushothaman Kathiresan , Jerry Dean
Published: November 2024

Singapore’s aquaculture sector is critical to achieving the nation’s ‘30 by 30’ food security goal, which aims to produce 30% of its nutritional needs locally by 2030. However, the sector faces several significant challenges. Limited land and water resources, high operational costs, disease outbreaks, reliance on imported seedstock, and environmental impact are among the key issues. Additionally, the industry struggles with a shortage of skilled manpower and high dependency on foreign labour. This study explores these challenges in detail and suggests potential solutions to enhance the sustainability and productivity of Singapore’s aquaculture. Innovative farming techniques such as recirculating aquaculture systems (RASs) and vertical farming, advanced water quality management, and the adoption of renewable energy sources are recommended to address space and cost constraints. Developing local breeding facilities, enhancing education and training programs, and adopting sustainable practices are also crucial. The establishment of a national hatchery and increased investment in research and development (R&D) are essential for long-term growth. By implementing these strategies, Singapore can overcome the challenges in its aquaculture sector and ensure a sustainable future for local food production.
Current Situation and Prospect of Geospatial AI in Air Pollution Prediction
Authors: Wu Chunlai , Lu Siyu , Tian Jiawei , Yin Lirong , Wang Lei , Zheng Wenfeng
Published: November 2024

Faced with increasingly serious environmental problems, scientists have conducted extensive research, among which the importance of air quality prediction is becoming increasingly prominent. This article briefly reviews the utilization of geographic artificial intelligence (AI) in air pollution. Firstly, this paper conducts a literature metrology analysis on the research of geographical AI used in air pollution. That is, 607 documents are retrieved from the Web of Science (WOS) using appropriate keywords, and literature metrology analysis is conducted using Citespace to summarize research hotspots and frontier countries in this field. Among them, China plays a constructive role in the fields of geographic AI and air quality research. The data characteristics of Earth science and the direction of AI utilization in the field of Earth science were proposed. It then quickly expanded to investigate and research air pollution. In addition, based on summarizing the current status of Artificial Neural Network (ANN), Recurrent Neural Network (RNN), and hybrid neural network models in predicting air quality (mainly PM2.5), this article also proposes areas for improvement. Finally, this article proposes prospects for future research in this field. This study aims to summarize the development trends and research hotspots of the utilization of geographic AI in the prediction of air quality, as well as prediction methods, to provide direction for future research.
A 4D-EnKF Method via a Modified Cholesky Decomposition and Line Search Optimization for Non-Linear Data Assimilation
Authors: Nino-Ruiz Elías D. , Diaz-Rodriguez Jairo
Published: November 2024

This paper introduces an efficient approach for implementing the Four-Dimensional Variational Ensemble Kalman Filter (4D-EnKF) for non-linear data assimilation, leveraging a modified Cholesky decomposition (4D-EnKF-MC). In this method, control spaces at observation times are represented by full-rank square root approximations of background error covariance matrices, derived using the modified Cholesky decomposition. To ensure global convergence, we integrate line-search optimization into the filter formulation. The performance of the 4D-EnKF-MC is evaluated through experimental tests using the Lorenz 96 model, and its accuracy is compared to that of a 4D-Var extension of the Maximum-Likelihood Ensemble Filter (4D-MLEF). Through Root Mean Square Error (RMSE) analysis, we demonstrate that the proposed method outperforms the 4D-MLEF across a range of ensemble sizes and observational network configurations, providing a robust and scalable solution for non-linear data assimilation in complex systems.
Can Tourists’ Summer Vacations Save Energy and Reduce CO2 Emissions? Evidence from China
Authors: Zhang Puwei , Li Xiujiang , Ren Meixuan , Li Rui , Gao Xin
Published: November 2024

This study develops a methodological framework for measuring energy conservation and CO2 emission reductions that considers both origins and destinations. The framework encompasses four key aspects: transportation, accommodation, cooking, and housing rehabilitation. Data were collected through a literature review, questionnaire surveys, and field measurement tracking. Compared to living in the origin, senior tourists from Nanchang visiting Zhongyuan Township in China for summer tourism can save 5.747 MJ of energy and reduce CO2 emissions by 3.303 kg per capita per day. An in-depth analysis indicated that the research site could further enhance energy conservation and reduce CO2 emissions by improving public transportation services, optimizing the energy structure of the destination, and diversifying the available recreational offerings. Depending on the characteristics of the destination and the primary origin, summer or winter tourism in various countries or regions can employ the methodological framework to evaluate energy conservation and CO2 emission reductions after identifying specific parameters. The improved pathways identified through this research can serve as a checklist for other countries or regions aiming to explore energy conservation and CO2-emission-reduction pathways for summer or winter tourism. Enhancing climate-driven tourism development may offer a new avenue for the tourism industry to contribute to carbon reduction targets.
Fixed-Point Results with Applications in Generalized Neutrosophic Rectangular b-Metric Spaces
Authors: Hussain Nawab , Alharbi Nawal , Basendwah Ghada
Published: November 2024

In this paper, we introduce several new concepts: generalized neutrosophic rectangular b-metric-like spaces (GNRBMLSs), generalized intuitionistic rectangular b-metric-like spaces (GIRBMLSs), and generalized fuzzy rectangular b-metric-like spaces (GFRBMLSs). These innovative spaces can expand various topological spaces, including neutrosophic rectangular extended b-metric-like spaces, intuitionistic fuzzy rectangular extended b-metric-like spaces, and fuzzy rectangular extended b-metric-like spaces. Moreover, we establish Banach’s fixed point theorem and Ćirić’s quasi-contraction theorem with respect to these spaces, and we explore an application regarding the existence and uniqueness of solutions for fuzzy fractional delay integro-differential equations, as derived from our main results.
Some Evaluations About Coefficients Boundaries for Specific Classes of Bi-Univalent Functions
Authors: Sowileh Suliman M. , Murugusundaramoorthy Gangadharan , Halouani Borhen , Elshazly Ibrahim S. , Mamon Mohamed A. , El-Qadeem Alaa H.
Published: November 2024

New subclasses of bi-univalent functions with bounded boundary rotation are presented in this study. We acquired estimates for the initial coefficients a2, a3 and a4. Furthermore, we have verified the specific situations satisfying the famous hypothesis of Brannan and Clunie. Additionally, we have obtained the well-known Fekete–Szegö inequality for the newly identified bi-univalent function subclasses. Our results not only improve, but also extend several existing results as particular cases.
Estimating the Lifetime Parameters of the Odd-Generalized-Exponential–Inverse-Weibull Distribution Using Progressive First-Failure Censoring: A Methodology with an Application
Authors: Ramadan Mahmoud M. , EL-Sagheer Rashad M. , Abd-El-Monem Amel
Published: November 2024

This paper investigates statistical methods for estimating unknown lifetime parameters using a progressive first-failure censoring dataset. The failure mode’s lifetime distribution is modeled by the odd-generalized-exponential–inverse-Weibull distribution. Maximum-likelihood estimators for the model parameters, including the survival, hazard, and inverse hazard rate functions, are obtained, though they lack closed-form expressions. The Newton–Raphson method is used to compute these estimations. Confidence intervals for the parameters are approximated via the normal distribution of the maximum-likelihood estimation. The Fisher information matrix is derived using the missing information principle, and the delta method is applied to approximate the confidence intervals for the survival, hazard rate, and inverse hazard rate functions. Bayes estimators were calculated with the squared error, linear exponential, and general entropy loss functions, utilizing independent gamma distributions for informative priors. Markov-chain Monte Carlo sampling provides the highest-posterior-density credible intervals and Bayesian point estimates for the parameters and reliability characteristics. This study evaluates these methods through Monte Carlo simulations, comparing Bayes and maximum-likelihood estimates based on mean squared errors for point estimates, average interval widths, and coverage probabilities for interval estimators. A real dataset is also analyzed to illustrate the proposed methods.
Congruence Extensions in Congruence–Modular Varieties
Authors: Georgescu George , Kwuida Leonard , Mureşan Claudia
Published: November 2024

We investigate from an algebraic and topological point of view the minimal prime spectrum of a universal algebra, considering the prime congruences with respect to the term condition commutator. Then we use the topological structure of the minimal prime spectrum to study extensions of universal algebras that generalize certain types of ring extensions. Our results hold for semiprime members of semidegenerate congruence–modular varieties, as well as semiprime algebras whose term condition commutators are commutative and distributive with respect to arbitrary joins and satisfy certain conditions on compact congruences, even if those algebras do not generate congruence–modular varieties.
Extension of Chu–Vandermonde Identity and Quadratic Transformation Conditions
Authors: Atia Mohamed Jalel , Alkilayh Maged
Published: November 2024

In 1812, Gauss stated the following identity: F12(a,b;c;1)=Γ(c)Γ(c−a−b)Γ(c−a)Γ(c−b), where, in the real case, c−a−b>0 and as an immediat consequence the Chu–Vandermonde identity: F12(a,−n;c;1)=(c−a)n(c)n for any positive integer n. In this paper, we investigate the case when c−a−b<0 by taking c=2b=−2n, n and a are positive integers (c−a−b=−n−a<0). We give two significant applications stemming from these findings. The second part of the paper will be devoted to Kummer’s conditions concerning hypergeometric quadratic transformations, particularly focusing on the distinctions between the conditions provided by Gradshteyn and Ryzhik (GR) and those by Erdélyi, Magnus, Oberhettinger, and Tricomi (EMOI) are outlined. We establish that the conditions given by GR differ from those of EMOI, and we explore the methodologies employed by both groups in deriving their results. This leads us to conclude that the search for exact and unified conditions remains an open problem.
Electroencephalography-Based Motor Imagery Classification Using Multi-Scale Feature Fusion and Adaptive Lasso
Authors: Chen Shimiao , Li Nan , Kong Xiangzeng , Huang Dong , Zhang Tingting
Published: November 2024

Brain–computer interfaces, where motor imagery electroencephalography (EEG) signals are transformed into control commands, offer a promising solution for enhancing the standard of living for disabled individuals. However, the performance of EEG classification has been limited in most studies due to a lack of attention to the complementary information inherent at different temporal scales. Additionally, significant inter-subject variability in sensitivity to biological motion poses another critical challenge in achieving accurate EEG classification in a subject-dependent manner. To address these challenges, we propose a novel machine learning framework combining multi-scale feature fusion, which captures global and local spatial information from different-sized EEG segmentations, and adaptive Lasso-based feature selection, a mechanism for adaptively retaining informative subject-dependent features and discarding irrelevant ones. Experimental results on multiple public benchmark datasets revealed substantial improvements in EEG classification, achieving rates of 81.36%, 75.90%, and 68.30% for the BCIC-IV-2a, SMR-BCI, and OpenBMI datasets, respectively. These results not only surpassed existing methodologies but also underscored the effectiveness of our approach in overcoming specific challenges in EEG classification. Ablation studies further confirmed the efficacy of both the multi-scale feature analysis and adaptive selection mechanisms. This framework marks a significant advancement in the decoding of motor imagery EEG signals, positioning it for practical applications in real-world BCIs.
Investigation of Elemental Composition in White Wine Treated with Varying Doses of Bentonite
Authors: Mladenova Elisaveta , Bakardzhiyski Ivan , Dimitrova Eva
Published: November 2024

The mineral composition of wine is affected by numerous factors, including treatments with bentonite to control colloidal hazes. In this study, 10 parallel samples of white wine (Chardonnay, 2021 vintage year) were treated with pre-selected bentonite (activated calcium bentonite) at increasing doses, from 0.3 to 3.0 g/L. Following acid mineralization, the content of some important elements was determined. The elements Al, Ba, Cd, Cu, Cr, Fe, Mg, Mn, P, Pb, and Zn were measured by inductively coupled plasma with optical emission spectrometry (ICP-OES), while flame atomic absorption spectrometry (FAAS) was used for the determination of Ca, K, and Li. Depending on the applied dose, the bentonite changed the concentration of the determined elements in different ways. Results indicated that higher doses of bentonite led to an increase in Al, Ca, and Fe content, while Cu and Zn initially rose with low doses before declining to near-baseline levels with higher doses.
Low-Intensity Continuous Ultrasound Enhances the Therapeutic Efficacy of Curcumin-Encapsulated Exosomes Derived from Hypoxic Liver Cancer Cells via Homotropic Drug Delivery Systems
Authors: Kim MinSeok , Kim YounJoong , Hwang ChiYeon , Song MinHyeok , Kim SuKang , Yoon Kyung-Sik , Kang InSug , Baik HyungHwan , Yoon Yong-Jin
Published: November 2024

Exosomes are extracellular nanovesicles secreted by cells that efficiently deliver therapeutic cargo for cancer treatment. However, because exosomes are present in low quantities and have limited target specificity, internal and external stress stimulation has been studied to increase exosome efficiency. Inspired by these studies, the uptake efficiency of cobalt chloride-induced hypoxic cancer cell-secreted exosomes was evaluated. Western blotting and RT-PCR data revealed increased exosome secretion and different protein compositions exhibited by hypoxic exosomes (H-Exos) compared to natural normoxic exosomes (N-Exos). Furthermore, these H-Exos were continuously stimulated using low-intensity ultrasound (LICUS) at an intensity of 360 mW/cm2 and a frequency of 3 MHz in vitro and 1 MHz in vivo. Hyperthermic and mechanical stress caused by ultrasound successfully improved exosome uptake via clathrin-mediated pathways, and confocal laser microscopy showed strong internal localization near the target cell nuclei. Finally, LICUS-equipped H-Exos were loaded with hydrophobic curcumin (H-Exo-Cur) and used to treat parent HepG2 liver cancer cells. The UV–Vis spectrophotometer displayed enhanced stability, solubility, and concentration of the encapsulated drug molecules. In MTT and FACS studies, approximately 40 times higher cell death was induced, and in animal studies, approximately 10 times higher tumor sizes were suppressed by LICUS-assisted H-Exo-Cur compared to the control. In this study, the delivery platform constructed demonstrated enormous potential for liver cancer therapy.
Intraoperative Optical Coherence Tomography (OCT)-Guided Femtosecond Laser-Assisted Descemet Membrane Endothelial Keratoplasty (iFAD)
Authors: Lim Joshua , Abusayf Mohammed M. , Liu Yu-Chi , Mehta Jodhbir S.
Published: November 2024

We describe retrospectively the indications and outcomes of nine patients who present with varying degrees of deep posterior stromal scarring or endothelial failure following deep anterior lamellar keratoplasty (DALK). These patients underwent a surgical strategy coined Intraoperative Optical Coherence Tomography Guided Femtosecond Laser-Assisted Descemet Membrane Endothelial Keratoplasty (iFAD). This strategy can be used to address suboptimal visual outcomes following primary DALK. Patients undergoing iFAD first had femtosecond laser-assisted trephination of the underlying posterior lamella using the liquid keratoplasty system on the Femto LDV Z8 platform (Zeimer Ophthalmic Systems AG, Port, Switzerland). A Descemet Membrane Endothelial Keratoplasty (DMEK) graft was subsequently transplanted in place of the removed lamella. Out of nine cases, major indications for seven included post-infective, blepharokeratoconjunctivitis (BKC) and deep stromal scarring related to stromal dystrophy. The remaining two had endothelial failure following primary DALK. The main benefits of this surgical approach are (1) Utilization of integrated real-time iOCT on the femtosecond laser platform allows for precise calibration of a wide range of vertical posterior trephination depths (96–329 microns) from the endothelial surface. (2) Femtosecond laser trephination utilizing a non-applanation liquid interface preserves trephination geometries and maximises precision-based surgical outcomes. (3) iFAD is a viable and straightforward technique for surgeons addressing patients who might otherwise require complex surgery to address residual deep stromal scars post-DALK.
Morphological and Redox/Glycative Alterations in the PCOS Oviducts: Modulating Effects of Carnitines in PCOS Mice
Authors: De Rubeis Mariacarla , Mascitti Ilaria Antenisca , Cocciolone Domenica , Placidi Martina , Vergara Teresa , Di Emidio Giovanna , Macchiarelli Guido , Tatone Carla , Nottola Stefania Annarita , Palmerini Maria Grazia
Published: November 2024

Polycystic ovarian syndrome (PCOS) is a heterogeneous condition characterized by hyperandrogenism (HA), polycystic ovaries, and dysfunctional ovulation, and it is associated with metabolic problems such as insulin resistance (IR) and obesity. After having investigated the morphological and antioxidant/antiglycative alterations on mouse ovaries and uteri, we here focus on PCOS oviducts, a tract of the reproductive system essential for the nourishment and transport of gametes and embryos. The modulating effects of L-carnitine (LC) and acetyl-L-carnitine (ALC) were also assessed. CD1 mice were administered or not with dehydroepiandrosterone (DHEA, 6 mg/100 g body weight) for 20 days, alone or with 0.40 mg of L-carnitine (LC) and 0.20 mg of acetyl-L-carnitine (ALC). Oviducts were then subjected to histology and immunohistochemistry to evaluate their morphology and collagen deposition, and steroidogenesis. Oxidative, mitochondrial, and methylglyoxal (MG)-dependent damage was also investigated. Transmission electron microscopy was used to detect ultrastructural alterations. The PCOS oviducts were affected by hyperfibrosis, hyperplasia, hypertrophy, and altered steroidogenesis, with oxidative alterations associated with MethylGlyoxal-Advanced Glycation End product (MG-AGE) accumulation. A reduced ciliary coverage and numerous dilated intercellular spaces were found in the epithelium. LC-ALC administration mitigated PCOS oviductal alterations. These results provide evidence for the detrimental action of oxidative and glycative stress in PCOS oviducts, confirming a protective role of carnitines on the PCOS phenotype.
Exosome-Mediated Transfer of X-Motif-Tagged Anti-MiR-33a-5p Antagomirs to the Medial Cells of Transduced Rabbit Carotid Arteries
Authors: Saenz-Pipaon Goren , Wacker Bradley K. , Bi Lianxiang , Stamatikos Alexis , Dichek David A.
Published: November 2024

Atherosclerosis is caused by the accumulation of cholesterol within intimal smooth muscle cells (SMCs) and macrophages. However, the transporter ATP-binding cassette subfamily A, member 1 (ABCA1), can remove cholesterol from these intimal, cells reducing atherosclerosis. Antagomir-mediated inhibition of miR-33a-5p, a microRNA that represses ABCA1 translation, promotes ABCA1-dependent cholesterol efflux and may impede atherosclerosis development. In our previous work, transducing cultured endothelial cells (ECs) with a helper-dependent adenoviral vector (HDAd) that expresses X-motif-tagged anti-miR-33a-5p enhanced antagomir packaging into EC-derived exosomes, which delivered the antagomir to cultured SMCs and macrophages. In this present study, we tested whether in vivo transduction of rabbit carotid artery endothelium can deliver an X-motif-tagged anti-miR-33a-5p to subendothelial cells. Rabbit carotid endothelial cells were transduced in vivo with an HDAd expressing anti-miR-33a-5p either with or without the X-motif (n = 11 arteries per vector). Contralateral carotids received HDAd that express scrambled oligonucleotides. Three days after transduction, the antagomir—without the X-motif—was detected in the intima but not in the media of transduced carotids (p = 0.062). The X-motif antagomir was detected in 82% of the intimal extracts (9 out of 11 carotids) and 27% of medial samples (3 out of 11 carotids, p = 0.031). However, the X-motif did not significantly enhance antagomir delivery to the media (p = 0.214 vs. non-X-motif antagomir). Expression of the antagomirs—with and without the X-motif—was sub-stoichiometric in ECs and SMCs. No antagomir-related changes in miR-33a-5p or ABCA1 expressions were detected. Despite its potential as a therapeutic strategy, our exosome-targeted gene transfer system requires further improvements to enhance antagomir expression and delivery to the subendothelial cells.
Internal Morphology and Phylogenetic Position of Mycetomorpha vancouverensis (Pancrustacea: Rhizocephala), an Enigmatic Parasitic Barnacle
Authors: Miroliubov Aleksei , Lianguzova Anastasia , Krupenko Darya , Poliushkevich Liudmila , Novokreshchennykh Semyon , Arbuzova Natalia , Kremnev Georgii
Published: November 2024

Mycetomorpha vancouverensis is an enigmatic parasitic barnacle from the family Mycetomorphidae, known for its unclear phylogenetic position within Rhizocephala. Specimens of M. vancouverensis were collected from infected Neocrangon communis shrimps near the South Kuril Islands. Detailed morphological studies were conducted using histological techniques and scanning electron microscopy, and 18S rDNA sequences were used to resolve the phylogenetic position of M. vancouverensis within Rhizocephala. Morphological analysis revealed a complex externa structure with spermatogenic bodies and the presence of a main trunk in the interna. Some of the side branches of the interna invade the host’s nerve tissue and are modified into specialized goblet-shaped organs. These invasive rootlets are morphologically similar to the goblet-shaped organs in the family Peltogastridae. Molecular analysis confirmed that the Mycetomorphidae is a sister group to the Peltogastridae. At the same time, peltogastrids were recovered as polyphyletic. Our findings contribute to the understanding of the evolution of parasitic barnacles and highlight the unique adaptations of Mycetomorphidae within the broader context of Rhizocephala.
Impact of Anthropogenic Factors on the Diversity of Microbial Communities of PM10 Air and PM100 of Tilia L. Phylloplane in an Urban Ecosystem
Authors: Sazonova Olesya I. , Ivanova Anastasia A. , Vetrova Anna A. , Zvonarev Anton N. , Streletskii Rostislav A. , Vasenev Viacheslav I. , Myazin Vladimir A. , Makhinya Ksenia I. , Kozlova Ekaterina V. , Korneykova Maria V.
Published: November 2024

Identifying the relationship between the microbiomes of urban dust particles from different biotopes is important because the state of microorganisms can be used to assess the quality of the environment. The aim of this work was to determine the distribution and interaction patterns of microorganisms of dust particles in the air and on leaf surfaces. Metabarcoding of bacterial and fungal communities, PAH, and metal content analyses and electron microscopy were used in this work. The results obtained allowed us to characterise the biological and chemical components of the dust particles. Some bacterial and fungal genera were correlated with benzanthracene, fluoranthene, and Cu, Ni, Co, Zn, and Mn contents. Bacterial communities were found to be more sensitive to all the pollutants studied. PM10 microbial communities circulated between biotopes and study areas due to air flows, as evidenced by the presence of similar ASVs in fungi and bacteria. The results could help to understand the effects of climate change and anthropogenic activities.
Estimating an Elephant Population Size Through Local Ecological Knowledge
Authors: Wenborn Michael , Svensson Magdalena S. , Nijman Vincent
Published: November 2024

In planning and monitoring measures to protect wildlife in an area, it is important to have a reliable baseline estimate of population size and trends. There has been minimal published information on a small population of elephants, a keystone and endangered species, in a large area west of Etosha National Park in Namibia, known locally as the Northern Highlands. It is a highly remote, mountainous area in which it is difficult to count elephants. It is semi-desert, where the protection of wildlife is at increasing risk from climate change events, and research on the elephant population is a priority. We interviewed 34 community game guards in the Northern Highlands, focusing on the number of elephants and distinguishing features in known groups. Based on the collated knowledge, and analysis to reduce double counting of known groups, we estimate that there are between 78 and 212 elephants in the Northern Highlands, with a best estimate of 128. The wide range is an indication of the current uncertainties in the method. However, we conclude that this low-cost method, if adapted based on lessons from this pilot study, would be applicable for longer-term ecological monitoring in areas that have a low population density.
Intermediate and Transitory Inflammation Mediate Proper Alveolar Bone Healing Outcome in Contrast to Extreme Low/High Responses: Evidence from Mice Strains Selected for Distinct Inflammatory Phenotypes
Authors: Colavite Priscila Maria , Azevedo Michelle de Campos Soriani , Francisconi Carolina Fávaro , Fonseca Angélica Cristina , Tabanez André Petenucci , Melchiades Jéssica Lima , Passadori Daniela Carignatto , Borrego Andrea , De Franco Marcelo , Trombone Ana Paula Favaro , Garlet Gustavo Pompermaier
Published: November 2024

Alveolar bone healing is influenced by various local and systemic factors, including the local inflammatory response. This study aimed to evaluate the role of inflammatory responsiveness in alveolar bone healing using 8-week-old male and female mice (N = 5/time/group) strains selected for maximum (AIRmax) or minimum (AIRmin) acute inflammatory response carrying distinct homozygous RR/SS Slc11a1 genotypes, namely AIRminRR, AIRminSS, AIRmaxRR, and AIRmaxSS mice. After upper right incisor extraction, bone healing was analyzed at 0, 3, 7, and 14 days using micro-computed tomography, histomorphometry, birefringence, immunohistochemistry, and PCRArray analysis. AIRmaxSS and AIRminRR presented the highest and lowest inflammatory readouts, respectively, associated with lowest repair levels in both strains, while intermediate inflammatory phenotypes observed in AIRminSS and AIRmaxRR were associated with higher repair levels in such strains. The better healing outcomes are associated with intermediate inflammatory cell counts, a balanced expression of pro- and anti-inflammatory cytokines and chemokines, increased expression of growth and osteogenic factors and MSCs markers. Our results demonstrate that extreme high and low inflammatory responses are not ideal for a proper bone repair outcome, while an intermediate and transitory inflammation is associated with a proper alveolar bone healing outcome.
Prediction of the Future Evolution Trends of Prunus sibirica in China Based on the Key Climate Factors Using MaxEnt Modeling
Authors: Wang Jiazhi , Cheng Jiming , Zhang Chao , Feng Yingqun , Jin Lang , Wei Shuhua , Yang Hui , Cao Ziyu , Peng Jiuhui , Luo Yonghong
Published: November 2024

Mountain apricot (Prunus sibirica) is an important fruit tree variety, and has a wide range of planting and application value in China and even the world. However, the current research on the suitable distribution area of P. sibirica is still inconclusive. In this study, we retrieved distribution data for P. sibirica in China from the Global Biodiversity Information Facility (GBIF), and identified six key environmental factors influencing its distribution through cluster analysis. Using these six selected climate factors and P. sibirica distribution points in China, we applied the maximum entropy model (MaxEnt) to evaluate 1160 candidate models for parameter optimization. The final results predict the potential distribution of P. sibirica under the current climate as well as two future climate scenarios (SSPs126 and SSPs585). This study shows that the model optimized with six key climate factors (AUC = 0.897, TSS = 0.658) outperforms the full model using nineteen climate factors (AUC = 0.894, TSS = 0.592). Under the high-emission scenario (SSPs585), the highly suitable habitat for P. sibirica is expected to gradually shrink towards the southeast and northwest, while expanding in the northeast and southwest. After the 2050s, highly suitable habitats are projected to completely disappear in Shandong, while new suitable areas may emerge in Tibet. Additionally, the total area of suitable habitat is projected to increase in the future, with a more significant expansion under the high-emission scenario (SSPs585) compared to the low-emission scenario (SSPs126) (7.33% vs. 0.16%). Seasonal changes in precipitation are identified as the most influential factor in driving the distribution of P. sibirica.
Cellular and Humoral Response After Induction of Protection and After Finishing Hymenoptera Venom Immunotherapy
Authors: Demšar Luzar Ajda , Rijavec Matija , Košnik Mitja , Bidovec-Stojković Urška , Debeljak Jerneja , Zidarn Mihaela , Kopač Peter , Korošec Peter
Published: November 2024

Hymenoptera venom allergy (HVA) is an IgE-mediated hypersensitivity reaction caused by Hymenoptera species stings (honeybee, vespid, or ant). The only effective treatment is Hymenoptera venom immunotherapy (VIT). Our study aimed to evaluate whether humoral and cellular biomarkers measured before, during, and after honeybee VIT are associated with the success of VIT, which was assessed by the response to a sting challenge one year after finishing VIT. In this prospective study, blood biomarkers of 25 patients undergoing honeybee VIT at the referral center in Slovenia were evaluated. A controlled honeybee sting challenge confirmed successful VIT in 20 of 25 (80%) patients. Honeybee venom (HBV) recombinant allergen profiles, evaluated before the treatment, were comparable between responders and non-responders. Longitudinal follow-up, up to 1 year after finishing VIT, showed that the immune responses do not differ significantly between patients with successful VIT and treatment failure. Those responses were characterized by decreased sIgE, tIgE, and BST, whereas sIgG4 levels increased. The basophil sensitivity also significantly decreases after VIT in both groups of patients. The analyzed biomarker which correlated considerably with treatment failure was higher basophil sensitivity to allergen stimulation before VIT. Similarly, systemic adverse events (SAEs) during the build-up phase of VIT correlated with treatment failure. Our study demonstrated similar sensitization profiles, and humoral and basophil immune responses to immunotherapy, in two different well-characterized groups of patients, one with successful VIT and the other with treatment failure. Notably, only high basophil sensitivity measured before VIT and SAEs during VIT were significantly associated with VIT failure, and both have the potential to be predictors of VIT failure.
Insight into Antifungal Metabolites from Bacillus stercoris 92p Against Banana Cordana Leaf Spot Caused by Neocordana musae
Authors: Yu Qunfang , He Pengbo , Qi Yanxiang , He Pengfei , Ahmed Ayesha , Zhang Xin , Zhang He , Wu Yixin , Munir Shahzad , He Yueqiu
Published: November 2024

Banana crop ranks among the most crucial fruit and food crops in tropical and subtropical areas. Despite advancements in production technology, diseases such as cordana leaf spot, caused by Neocordana musae, remain a significant challenge, reducing productivity and quality. Traditional chemical controls are becoming less effective due to the development of resistance in target pathogens, which pose significant environmental and health concerns. Consequently, there is growing attention toward the development of biocontrol strategies. Here, we identified a new bacterial strain, Bacillus stercoris 92p, from the rhizosphere soil of banana. We evaluated its ability to suppress the growth of N. musae and other fungal pathogens that cause leaf spot disease in bananas. The inhibitory effect of B. stercoris 92p were checked using dual culture assays, microscopic observations, and pot experiments. Furthermore, the biocontrol mechanisms were investigated using whole-genome sequencing and biochemical analyses. The results showed that B. stercoris 92p exhibited significant antifungal activity against N. musae and other fungal pathogens, with inhibition rates exceeding 70%. Microscopic examination revealed significant morphological alterations in the hyphae and conidia of the tested pathogens. In pot experiments, B. stercoris 92p effectively reduced the severity of cordana leaf spot, achieving a biocontrol efficacy of 61.55%. Genomic analysis and biochemical tests indicated that B. stercoris 92p produces various antifungal compounds, including lipopeptides (fengycins and surfactins), hydrolytic enzymes (proteases and amylases), and phosphate-solubilizing metabolites. In conclusion, the study highlights that B. stercoris could potentially be used as a potential biological control agent against cordana leaf spot.