bluuebunny/crossref_metadata_2025 huggingface dataset:
Vaginal Microbiome and Pregnancy Complications: A Review
Authors: Gerede Angeliki , Nikolettos Konstantinos , Vavoulidis Eleftherios , Margioula-Siarkou Chrysoula , Petousis Stamatios , Giourga Maria , Fotinopoulos Panagiotis , Salagianni Maria , Stavros Sofoklis , Dinas Konstantinos , Nikolettos Nikolaos , Domali Ekaterini
Published: July 2024

Background/Objectives: There are indications that the microbial composition of the maternal mucosal surfaces is associated with adverse events during pregnancy. The aim of this review is to investigate the link between vaginal microbiome alterations and gestational complication risk. Methods: This comprehensive literature review was performed using Medline and Scopus databases. The following search algorithm was used, “Pregnancy Complications” [Mesh] AND (Vagin*), and after the literature screening, 44 studies were included in the final review. Results: The studies that were included investigated the association between vaginal microbial composition and preterm birth, miscarriage, preeclampsia, ectopic pregnancy, gestational diabetes mellitus, chorioamnionitis, and preterm premature rupture of membranes. In most of the studies, it was well established that increased microbial diversity is associated with these conditions. Also, the depletion of Lactobacillus species is linked to most of the gestational complications, while the increased relative abundance and especially Lactobacillus crispatus may exert a protective effect in favor of the pregnant woman. Several pathogenic taxa including Gardnerella, Prevotella, Sneathia, Bacterial Vaginosis-Associated Bacteria-2, Atopobium, and Megasphera seem to be correlated to higher maternal morbidity. Conclusions: Vaginal microbiome aberrations seem to have an association with pregnancy-related adverse events, but more high-quality homogenous studies are necessary to reliably verify this link.
Investigating Microstructural and Mechanical Behavior of DLP-Printed Nickel Microparticle Composites
Authors: Susanto Benny , Kumar Vishnu Vijay , Sean Leonard , Handayani Murni , Triawan Farid , Rahmayanti Yosephin Dewiani , Ardianto Haris , Muflikhun Muhammad Akhsin
Published: July 2024

The study investigates the fabrication and analysis of nickel microparticle-reinforced composites fabricated using the digital light processing (DLP) technique. A slurry is prepared by incorporating Ni-micro particles into a resin vat; it is thoroughly mixed to achieve homogeneity. Turbidity fluctuations are observed, initially peaking at 50% within the first two minutes of mixing and then stabilizing at 30% after 15–60 min. FTIR spectroscopy with varying Ni wt.% is performed to study the alterations in the composite material’s molecular structure and bonding environment. Spectrophotometric analysis revealed distinctive transmittance signatures at specific wavelengths, particularly within the visible light spectrum, with a notable peak at 532 nm. The effects of printing orientation in the X, Y, and Z axes were also studied. Mechanical properties were computed using tensile strength, surface roughness, and hardness. The results indicate substantial enhancements in the tensile properties, with notable increases of 75.5% in the ultimate tensile strength and 160% in the maximum strain. Minimal alterations in surface roughness and hardness suggest favorable printability. Microscopic examination revealed characteristic fracture patterns in the particulate composite at different values for the wt.% of nickel. The findings demonstrate the potential of DLP-fabricated Ni-reinforced composites for applications demanding enhanced mechanical performance while maintaining favorable printability, paving the way for further exploration in this domain.
The Incorporation of Zinc into Hydroxyapatite and Its Influence on the Cellular Response to Biomaterials: A Systematic Review
Authors: Dornelas Jessica , Dornelas Giselle , Rossi Alexandre , Piattelli Adriano , Di Pietro Natalia , Romasco Tea , Mourão Carlos Fernando , Alves Gutemberg Gomes
Published: July 2024

Zinc is known for its role in enhancing bone metabolism, cell proliferation, and tissue regeneration. Several studies proposed the incorporation of zinc into hydroxyapatite (HA) to produce biomaterials (ZnHA) that stimulate and accelerate bone healing. This systematic review aimed to understand the physicochemical characteristics of zinc-doped HA-based biomaterials and the evidence of their biological effects on osteoblastic cells. A comprehensive literature search was conducted from 2022 to 2024, covering all years of publications, in three databases (Web of Science, PUBMED, Scopus), retrieving 609 entries, with 36 articles included in the analysis according to the selection criteria. The selected studies provided data on the material’s physicochemical properties, the methods of zinc incorporation, and the biological effects of ZnHA on bone cells. The production of ZnHA typically involves the wet chemical synthesis of HA and ZnHA precursors, followed by deposition on substrates using processes such as liquid precursor plasma spraying (LPPS). Characterization techniques confirmed the successful incorporation of zinc into the HA lattice. The findings indicated that zinc incorporation into HA at low concentrations is non-cytotoxic and beneficial for bone cells. ZnHA was found to stimulate cell proliferation, adhesion, and the production of osteogenic factors, thereby promoting in vitro mineralization. However, the optimal zinc concentration for the desired effects varied across studies, making it challenging to establish a standardized concentration. ZnHA materials are biocompatible and enhance osteoblast proliferation and differentiation. However, the mechanisms of zinc release and the ideal concentrations for optimal tissue regeneration require further investigation. Standardizing these parameters is essential for the effective clinical application of ZnHA.
A Ship Energy Consumption Prediction Method Based on TGMA Model and Feature Selection
Authors: Liu Yuhang , Wang Kai , Lu Yong , Zhang Yongfeng , Li Zhongwei , Ma Ranqi , Huang Lianzhong
Published: July 2024

Optimizing ship energy efficiency is a crucial measure for reducing fuel use and emissions in the shipping industry. Accurate prediction models of ship energy consumption are essential for achieving this optimization. However, external factors affecting ship fuel consumption have not been comprehensively investigated, and many existing studies still face efficiency and accuracy challenges. In this study, we propose a neural network model called TCN-GRU-MHSA (TGMA), which incorporates the temporal convolutional network (TCN), the gated recurrent unit (GRU), and multi-head self-attention mechanisms to predict ship energy consumption. Firstly, the characteristics of ship operation data are analyzed, and appropriate input features are selected. Then, the prediction model is established and validated through application analysis. Using the proposed model, the prediction accuracy of ship energy consumption can reach up to 96.04%. Comparative analysis results show that the TGMA model outperforms existing models, including those based on LSTM, GRU, SVR, TCN-GRU, and BP neural networks, in terms of accuracy. Therefore, the developed model can effectively predict ship fuel usage under various conditions, making it essential for optimizing and improving ship energy efficiency.
Hydrodynamic Performance Assessment of Emerged, Alternatively Submerged and Submerged Semicircular Breakwater: An Experimental and Computational Study
Authors: Al-Towayti Faris Ali Hamood , Teh Hee-Min , Ma Zhe , Jae Idris Ahmed , Syamsir Agusril , Al-Qadami Ebrahim Hamid Hussein
Published: July 2024

Coastal protection structures are essential defenses against wave energy, safeguarding coastal communities. This study aims to refine coastal protection strategies by employing a semicircular breakwater (SBW) model. Through a combination of physical and computational models, the hydrodynamic properties of the SBW under regular wave conditions were thoroughly examined. The primary objectives included delineating the hydrodynamic characteristics of SBWs, developing a computational model to validate experimental findings. Hydrodynamic characteristics of the SBW model were scrutinized across various wave conditions. Experimental testing in a wave flume covered a range of relative water depths (d/h) from 0.667 to 1.667, wave steepness (Hi/L) spanning 0.02 to 0.06 and wave periods ranging from 0.8 to 2.5 s. Notably, analysis of an emerged SBW with d/h = 0.667 revealed superior wave reflection, while an alternative submerged SBW with d/h = 1.000 showed the highest energy loss. These findings are further corroborated by the validation of computational models against experimental outcomes for d/h = 0.667, 1.000, 1.333 and 1.667. Moreover, the investigation of forces revealed an inverse correlation between horizontal forces and wave height, while vertical forces showed nuanced variations, including a slightly decreasing average vertical force with greater relative wave period (B/L) for different immersion scenarios.
What’s Wrong with Enterprise Risk Management?
Authors: Fraser John , Quail Rob , Simkins Betty
Published: July 2024

Enterprise risk management (ERM) was introduced in the 1990s and has since become expected by boards of directors and regulators as a sign of good management and good corporate governance. However, many organizations struggle to implement ERM, and still seek practical advice on ERM implementation. This article explains many of the reasons why organizations are unsuccessful in their efforts at implementation and provides practical solutions provided by an experienced risk manager and consultant, an ex-Chief Risk Officer, and an academic, all of whom have written extensively on the subject. This article should be of interest to practitioners involved in implementing ERM, to consultants in ERM, and to academics teaching courses on ERM, risk management, and related topics. This article also provides a base against which further future research can be performed as ERM best practices continue to evolve.
The Impact of Economic Growth on the Ecological Environment and Renewable Energy Production: Evidence from Azerbaijan and Hungary
Authors: Humbatova Sugra Ingilab , Hajiyeva Nargiz , Fodor Monika Garai , Sood Kiran , Grima Simon
Published: July 2024

This article reflects on the necessity of employing renewable energy sources in the modern era to mitigate the negative environmental impact caused by traditional energy sources and address environmental pollution. Through research conducted in Azerbaijan and Hungary, it analyses the influence of economic growth on the ecological environment and renewable energy production. Due to limitations in the general dataset, the study considers the period of 1997–2022 for CO2 emissions causing environmental pollution, 2007–2022 for renewable energy production in Azerbaijan, and 2000–2021 for the same in Hungary. Information regarding wind and solar energy in Azerbaijan has been available since 2013. Temporal sequences have been utilised in the research, employing Augmented Dickey–Fuller and Phillips–Perron (PP) unit root tests to examine the stationarity of the time series. An Autoregressive Distributed Lag (ARDL) model has been constructed, and the credibility of the model has been verified using Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Canonical Cointegrating Regression (CCR) models. The findings reveal that in Azerbaijan, the long-term impact of economic growth on hydro-energy has been negative, while dependence on biomass and waste has been insignificant but positive. The influence on wind and solar energy production has also been negative and insignificant, akin to hydro-energy production. However, energy supply from renewable sources has been positively affected by the aggregate indicator of economic growth, albeit insignificantly. The impact of economic growth on carbon dioxide has been significant in two magnitudes, whereas in other cases, it has been insignificant but positive. In Hungary, economic growth has positively affected renewable energy production. However, the impact on carbon dioxide has been negative, meaning that this indicator has decreased as economic growth has increased. The study concludes that the impact of economic growth on indicators of both countries has been more effective in Hungary, which can be attributed to economic development.
Calculation Method and Experimental Study on Circumferential Total Clearance of Cageless Bearings
Authors: Zhao Xiaofeng , Xu Shuidian , Xu Tao , Xu Qianqian , Huang Kai
Published: July 2024

This paper addresses the issue of the frequent collision and grinding of rolling elements in cageless bearings during operation by proposing a method to calculate the total circumferential clearance. The calculation is based on the maximum orbital speed difference in the bearing rolling elements to determine the minimum clearance needed to prevent collision. The study analyzes the impact of the rolling element diameter, bearing pitch diameter, contact angle, and number of rolling elements on the total circumferential clearance. The discussion then focuses on optimizing the number of rolling elements in cageless bearings. The optimization results demonstrate that the proposed calculation reduces collisions between rolling elements and bearing stress. Additionally, a total circumferential clearance test was conducted on a logarithmic spiral bearing, showing significant improvements in wear, average temperature, and temperature rise when designed according to the method presented in this article. These findings offer valuable insights into the design of cageless bearings.
Zinc/Magnesium Ferrite Nanoparticles Functionalized with Silver for Optimized Photocatalytic Removal of Malachite Green
Authors: Fernandes Ricardo J. C. , Cardoso Beatriz D. , Rodrigues Ana Rita O. , Pires Ana , Pereira André M. , Araújo João P. , Pereira Luciana , Coutinho Paulo J. G.
Published: June 2024

Water pollution is a major environmental challenge. Due to the inefficiency of conventional wastewater treatment plants in degrading many organic complex compounds, these recalcitrant pollutants end up in rivers, lakes, oceans and other bodies of water, affecting the environment and human health. Semiconductor photocatalysis is considered an efficient complement to conventional methods, and the use of various nanomaterials for this purpose has been widely explored, with a particular focus on improving their activity under visible light. This work focuses on developing magnetic and photoactive zinc/magnesium mixed ferrites (Zn0.5Mg0.5Fe2O4) by sol-gel and solvothermal synthesis methods, which are two of the most important and efficient methods used for the synthesis of ferrite nanoparticles. The nanoparticles (NPs) synthesized by the sol-gel method exhibited an average size of 14.7 nm, while those synthesized by the solvothermal method had an average size of 17.4 nm. Both types possessed a predominantly cubic structure and demonstrated superparamagnetic behavior, reaching a magnetization saturation value of 60.2 emu g−1. Due to the high recombination rate of electrons/holes, which is an intrinsic feature of ferrites, surface functionalization with silver was carried out to enhance charge separation. The results demonstrated a strong influence of adsorption and of the deposition of silver. Several optimization steps were performed during synthesis, allowing us to create efficient catalysts, as proved by the almost full removal of the dye malachite green attaining 95.0% (at a rate constant of 0.091 min−1) and 87.6% (at a rate constant of 0.017 min−1) using NPs obtained by the sol-gel and solvothermal methods, respectively. Adsorption in the dark accounted for 89.2% of the dye removal for nanoparticles prepared by sol-gel and 82.8% for the ones obtained by the solvothermal method. These results make mixed zinc/magnesium ferrites highly promising for potential industrial application in effluent photoremediation using visible light.
An Investigation into Sheet-Inconel 718 Forming with Flexible and Metal Tools—Simulation and Experiment
Authors: Balcerzak Maciej , Rusz Stanislav , Čada Radek , Pastrňák Martin , Hilšer Ondřej , Greger Miroslav
Published: June 2024

The article presents the results of numerical simulations and experimental tests of plastic forming sheets made from the difficult-to-deform nickel alloy Inconel 718 with a thickness of 1 mm, using punches made from elastomeric materials with hardness 50–90 Shore A and steel dies. Elastomeric stamps were created in the form of five layers with a diameter of 160 mm. The influence of the hardness of the elastomeric punches on the geometry of the elements obtained was determined. The dies were made from 90MnCrV8 steel with a hardness of over 60 HRC. Their task was to obtain the expected shape of the element while generating various stress states in specific areas of the semi-finished product. The research was carried out using an original device whose operating principle was based on the Guerin method. The shape and dimensions of the elements made from Inconel 718 nickel alloy were determined by optical 3D scanning. The geometry of the drawpiece showed a significant impact of the hardness of the layered elastomer matrices on the degree of shape reproduction. The results obtained from numerical modeling were confirmed by the results of experimental tests. It has been shown that the hardness of the elastomeric material used for punches for plastic forming Inconel 718 nickel alloy sheets should be adapted to the shape of the drawpiece. It was also found that one of the important aspects of plastic forming sheets using the Guerin method is the tendency to obtain a diversified shape of the final elements.
Multiscale Progressive Failure Analysis for Composite Stringers Subjected to Compressive Load
Authors: Shi Jian , Zeng Jianjiang , Zheng Jie , Shi Furui , Yang Guang , Tong Mingbo
Published: June 2024

The fiber-reinforced composite stringer is commonly used in large civil aircraft wing structures. Under compression loads, it exhibits complex failure modes, with matrix cracking being one of the most common. The quantitative analysis of matrix failure is important and difficult. To address this issue, a multiscale method combining the generalized method of cells (GMC) and macroscopic FEM models is employed to quantitatively predict matrix damage and failure. The extent of matrix damage in the composite structure is represented by the number of failed matrix subcells within the repeating unit cells. The 3D Tsai–Hill failure criterion is established for the matrix phase, and the maximum stress failure criterion is applied to the fiber subcell. Upon meeting the criterion, the stiffnesses of the failed subcells are immediately reduced to a nominal value. In the current study, the ultimate loads, failure modes and load–displacement curves of composite stringers subjected to compressive load are obtained by the experiment approach and the proposed multiscale model. The experimental and simulation results show good agreement, and the multiscale analysis method successfully predicts the extent of matrix damage in the composite stringer under compressive load. The number of failed matrix subcells quantitatively evaluates the damage extent within a 2 × 2 GMC model. The findings reveal that matrix subcell failures primarily occur in the 45° and −45° plies of the middle part of the stringer composite.
On the Use of Nanoparticles in Dental Implants
Authors: Bokobza Liliane
Published: July 2024

Results obtained in physics, chemistry and materials science on nanoparticles have drawn significant interest in the use of nanostructures on dental implants. The main focus concerns nanoscale surface modifications of titanium-based dental implants in order to increase the surface roughness and provide a better bone–implant interfacial area. Surface coatings via the sol–gel process ensure the deposition of a homogeneous layer of nanoparticles or mixtures of nanoparticles on the titanium substrate. Nanotubular structures created on the titanium surface by anodic oxidation yield an interesting nanotopography for drug release. Carbon-based nanomaterials hold great promise in the field of dentistry on account of their outstanding mechanical properties and their structural characteristics. Carbon nanomaterials that include carbon nanotubes, graphene and its derivatives (graphene oxide and graphene quantum dots) can be used as coatings of the implant surface. Their antibacterial properties as well as their ability to be functionalized with adequate chemical groups make them particularly useful for improving biocompatibility and promoting osseointegration. Nevertheless, an evaluation of their possible toxicity is required before being exploited in clinical trials.
Graph Convolutional Network for Image Restoration: A Survey
Authors: Cheng Tongtong , Bi Tingting , Ji Wen , Tian Chunwei
Published: July 2024

Image restoration technology is a crucial field in image processing and is extensively utilized across various domains. Recently, with advancements in graph convolutional network (GCN) technology, methods based on GCNs have increasingly been applied to image restoration, yielding impressive results. Despite these advancements, there is a gap in comprehensive research that consolidates various image denoising techniques. In this paper, we conduct a comparative study of image restoration techniques using GCNs. We begin by categorizing GCN methods into three primary application areas: image denoising, image super-resolution, and image deblurring. We then delve into the motivations and principles underlying various deep learning approaches. Subsequently, we provide both quantitative and qualitative comparisons of state-of-the-art methods using public denoising datasets. Finally, we discuss potential challenges and future directions, aiming to pave the way for further advancements in this domain. Our key findings include the identification of superior performance of GCN-based methods in capturing long-range dependencies and improving image quality across different restoration tasks, highlighting their potential for future research and applications.
Geometry Interaction Embeddings for Interpolation Temporal Knowledge Graph Completion
Authors: Zhao Xuechen , Miao Jinfeng , Yang Fuqiang , Pang Shengnan
Published: July 2024

Knowledge graphs (KGs) have become a cornerstone for structuring vast amounts of information, enabling sophisticated AI applications across domains. The progression to temporal knowledge graphs (TKGs) introduces time as an essential dimension, allowing for a dynamic representation of entity relationships. Despite their potential, TKGs often suffer from incompleteness, necessitating the development of temporal knowledge graph completion (TKGC) techniques. These methods, particularly focusing on interpolation within the known timeframe, aim to infer missing temporal facts and enhance the predictive capabilities of TKGs. The prevalent reliance on Euclidean space modeling in TKGC methods presents challenges in capturing the complex, hierarchical, and time-varying nature of TKGs. To overcome these limitations, we introduced the attention-based geometry interaction embedding (ATGIE) method, a novel approach that leverages the strengths of multiple geometric spaces, i.e., Euclidean, hyperbolic, and hypersphere, to model the intricacies of TKGs more effectively. ATGIE employs an attention mechanism to dynamically weigh the contributions of different geometric spaces, allowing it to adaptively form reliable spatial structures based on interactive geometric information. This multi-space modeling not only captures the diverse relationships within TKGs but also facilitates a nuanced understanding of how entities and their relationships evolve over time. Through extensive experiments, we demonstrate ATGIE’s superiority in TKGC tasks, showcasing its improvement over existing methods, robustness to noise, and sensitivity to temporal dynamics. The results highlight ATGIE’s potential to advance the state-of-the-art in TKGC, offering a promising direction for research and application in the field.
Weighted Ranked Set Sampling for Skewed Distributions
Authors: Bhoj Dinesh S. , Chandra Girish
Published: July 2024

Ranked set sampling (RSS) is a useful technique for improving the estimator of a population mean when the sampling units in a study can be more easily ranked than the actual measurement. RSS performs better than simple random sampling (SRS) when the mean of units corresponding to each rank is used. The performance of RSS can be increased further by assigning weights to the ranked observations. In this paper, we propose weighted RSS procedures to estimate the population mean of positively skewed distributions. It is shown that the gains in the relative precisions of the population mean for chosen distributions are uniformly higher than those based on RSS. The gains in relative precisions are substantially high. Further, the relative precisions of our estimator are slightly higher than the ones based on Neyman’s optimal allocation model for small sample sizes. Moreover, it is shown that the performance of the proposed estimator increases as the skewness increases by using the example of the lognormal family of distributions.
Fractional Differential Operator Based on Quantum Calculus and Bi-Close-to-Convex Functions
Authors: Jia Zeya , Alb Lupaş Alina , Bin Jebreen Haifa , Oros Georgia Irina , Bulboacă Teodor , Ahmad Qazi Zahoor
Published: July 2024

In this article, we first consider the fractional q-differential operator and the λ,q-fractional differintegral operator Dqλ:A→A. Using the λ,q-fractional differintegral operator, we define two new subclasses of analytic functions: the subclass S*q,β,λ of starlike functions of order β and the class CΣλ,qα of bi-close-to-convex functions of order β. We explore the results on coefficient inequality and Fekete–Szegö problems for functions belonging to the class S*q,β,λ. Using the Faber polynomial technique, we derive upper bounds for the nth coefficient of functions in the class of bi-close-to-convex functions of order β. We also investigate the erratic behavior of the initial coefficients in the class CΣλ,qα of bi-close-to-convex functions. Furthermore, we address some known problems to demonstrate the connection between our new work and existing research.
Three-Dimensional Vehicle Detection and Pose Estimation in Monocular Images for Smart Infrastructures
Authors: Borau Bernad Javier , Ramajo-Ballester Álvaro , Armingol Moreno José María
Published: July 2024

Over the last decades, the idea of smart cities has evolved from a visionary concept of the future into a concrete reality. However, the vision of smart cities has not been fully realized within our society, partly due to the challenges encountered in contemporary data collection systems. Despite these obstacles, advancements in deep learning and computer vision have propelled the development of highly accurate detection algorithms capable of obtaining 3D data from image sources. Nevertheless, this approach has predominantly centered on data extraction from a vehicle’s perspective, bypassing the advantages of using infrastructure-mounted cameras for performing 3D pose estimation of vehicles in urban environments. This paper focuses on leveraging 3D pose estimation from this alternative perspective, benefiting from the enhanced field of view that infrastructure-based cameras provide, avoiding occlusions, and obtaining more information from the objects’ sizes, leading to better results and more accurate predictions compared to models trained on a vehicle’s viewpoint. Therefore, this research proposes a new path for exploration, supporting the integration of monocular infrastructure-based data collection systems into smart city development.
A (2 + 1)-Dimensional Integrable Breaking Soliton Equation and Its Algebro-Geometric Solutions
Authors: Chen Xiaohong , Xia Tiecheng , Zhu Liancheng
Published: July 2024

A new (2 + 1)-dimensional breaking soliton equation with the help of the nonisospectral Lax pair is presented. It is shown that the compatible solutions of the first two nontrivial equations in the (1 + 1)-dimensional Kaup–Newell soliton hierarchy provide solutions of the new breaking soliton equation. Then, the new breaking soliton equation is decomposed into the systems of solvable ordinary differential equations. Finally, a hyperelliptic Riemann surface and Abel–Jacobi coordinates are introduced to straighten the associated flow, from which the algebro-geometric solutions of the new (2 + 1)-dimensional integrable equation are constructed by means of the Riemann θ functions.
A Counterexample Concerning C0-Semigroups of Holomorphic Carathéodory Isometries
Authors: Stachó László L.
Published: July 2024

We give an example for a C0-semigroup of non-linear 0-preserving holomorphic Carathéodory isometries of the unit ball.
A Matrix Approach to Vertex-Degree-Based Topological Indices
Authors: Cruz Roberto , Espinal Carlos , Rada Juan
Published: July 2024

A VDB (vertex-degree-based) topological index over a set of digraphs H is a function φ:H→R, defined for each H∈H as φH=12∑uv∈Eφdu+dv−, where E is the arc set of H, du+ and dv− denote the out-degree and in-degree of vertices u and v respectively, and φij=f(i,j) for an appropriate real symmetric bivariate function f. It is our goal in this article to introduce a new approach where we base the concept of VDB topological index on the space of real matrices instead of the space of symmetric real functions of two variables. We represent a digraph H by the p×p matrix αH, where αHij is the number of arcs uv such that du+=i and dv−=j, and p is the maximum value of the in-degrees and out-degrees of H. By fixing a p×p matrix φ, a VDB topological index of H is defined as the trace of the matrix φTα(H). We show that this definition coincides with the previous one when φ is a symmetric matrix. This approach allows considering nonsymmetric matrices, which extends the concept of a VDB topological index to nonsymmetric bivariate functions.
Torricelli’s Law in Fractal Space–Time Continuum
Authors: Samayoa Didier , Alvarez-Romero Liliana , Jiménez-Bernal José Alfredo , Damián Adame Lucero , Kryvko Andriy , Gutiérrez-Torres Claudia del C.
Published: July 2024

A new formulation of Torricelli’s law in a fractal space–time continuum is developed to compute the water discharge in fractal reservoirs. Fractal Torricelli’s law is obtained by applying fractal continuum calculus concepts using local fractional differential operators. The model obtained can be used to describe the behavior of real flows, considering the losses in non-conventional reservoirs, taking into account two additional fractal parameters α and β in the spatial and temporal fractal continuum derivatives, respectively. This model is applied to the flows in reservoirs with structures of three-dimensional deterministic fractals, such as inverse Menger sponge, Sierpinski cube, and Cantor dust. The results of the level water discharge H(t) are presented as a curve series, showing the impact and influence of fluid flow in naturally fractured reservoirs that posses self-similar properties.
A Model for Developing a Mobile Payment Service Framework
Authors: Lee Amy H. I. , Kang He-Yau
Published: July 2024

The rise of wireless communication has spurred the global adoption of mobile payment services, a trend that is significantly reducing the use of cash. This shift, driven by new technologies and lifestyle changes, not only presents opportunities for businesses but also enhances consumers’ daily activities. Consumers’ and businesses’ willingness to adopt mobile payment services has increased due to factors such as easier access to new technologies, convenience, changing lifestyle choices, and economic conditions. Despite challenges such as limited access to technology, security concerns, and high transaction fees, the potential benefits of mobile payment services are promising. Therefore, this research aims to construct a suitable model for developing a mobile payment service framework that both consumers and businesses are willing to adopt. The proposed model integrates the Delphi method, interpretive structural modeling (ISM), quality function deployment (QFD), an analytic network process (ANP), and fuzzy set theory. To demonstrate the practical application of the model, a case study of developing a mobile payment service framework is presented, showcasing how the model can be used to address real-world challenges and enhance the adoption of mobile payment services. The case study results show that ease of use, system and service quality, and reliability are the most important customer requirements, and encryption, edge computing, authentication, and interoperability are the most important engineering characteristics.
Dual-Objective Reinforcement Learning-Based Adaptive Traffic Signal Control for Decarbonization and Efficiency Optimization
Authors: Zhang Gongquan , Chang Fangrong , Huang Helai , Zhou Zilong
Published: July 2024

To improve traffic efficiency, adaptive traffic signal control (ATSC) systems have been widely developed. However, few studies have proactively optimized the air environmental issues in the development of ATSC. To fill this research gap, this study proposes an optimized ATSC algorithm to take into consideration both traffic efficiency and decarbonization. The proposed algorithm is developed based on the deep reinforcement learning (DRL) framework with dual goals (DRL-DG) for traffic control system optimization. A novel network structure combining Convolutional Neural Networks and Long Short-Term Memory Networks is designed to map the intersection traffic state to a Q-value, accelerating the learning process. The reward mechanism involves a multi-objective optimization function, employing the entropy weight method to balance the weights among dual goals. Based on a representative intersection in Changsha, Hunan Province, China, a simulated intersection scenario is constructed to train and test the proposed algorithm. The result shows that the ATSC system optimized by the proposed DRL-DG results in a reduction of more than 71% in vehicle waiting time and 46% in carbon emissions compared to traditional traffic signal control systems. It converges faster and achieves a balanced dual-objective optimization compared to the prevailing DRL-based ATSC.
Identification of Axinellamines A and B as Anti-Tubercular Agents
Authors: Strong Emily J. , Tan Lendl , Hayes Sasha , Whyte Hayden , Davis Rohan A. , West Nicholas P.
Published: June 2024

Tuberculosis remains a significant global health pandemic. There is an urgent need for new anti-tubercular agents to combat the rising incidence of drug resistance and to offer effective and additive therapeutic options. High-throughput screening of a subset of the NatureBank marine fraction library (n = 2000) identified a sample derived from an Australian marine sponge belonging to the order Haplosclerida that displayed promising anti-mycobacterial activity. Bioassay-guided fractionation of the organic extract from this Haplosclerida sponge led to the purification of previously identified antimicrobial pyrrole alkaloids, axinellamines A (1) and B (2). The axinellamine compounds were found to have a 90% minimum inhibitory concentration (MIC90) of 18 µM and 15 µM, respectively. The removal of protein and complex carbon sources reduced the MIC90 of 1 and 2 to 0.6 and 0.8 µM, respectively. The axinellamines were not toxic to mammalian cells at 25 µM and significantly reduced the intracellular bacterial load by >5-fold. These data demonstrate that axinellamines A and B are effective anti-tubercular agents and promising targets for future medicinal chemistry efforts.
Does the Effect of Mental Fatigue Created by Motor Imagery on Upper Extremity Functions Change with Diaphragmatic Breathing Exercises? A Randomized, Controlled, Single-Blinded Trial
Authors: Türkmen Ozan Bahadır , Akçay Burçin , Demir Canan , Kurtoğlu Ahmet , Alotaibi Madawi H. , Elkholi Safaa M.
Published: July 2024

Background and Objectives: This study focused on the impact of mental fatigue induced by motor imagery on upper limb function, an area with limited research compared to lower limb performance. It aimed to explore how diaphragmatic breathing exercises influence these effects. Materials and Methods: This study included 30 participants, and Group 1 participated in 12 sessions of diaphragmatic breathing exercises under the supervision of a physiotherapist; Group 2 did not receive any intervention. For all the participants, mental fatigue was induced with motor imagery before and after the intervention, and evaluations were performed before and after mental fatigue. Upper extremity functions were evaluated using isometric elbow flexion strength, hand grip strength, upper extremity reaction time and endurance, finger reaction time, the nine-hole peg test, shoulder position sense, light touch-pressure threshold, and two-point discrimination. Results: The study results showed that after mental fatigue, there was a decrease in isometric elbow flexion strength, nondominant hand grip strength, and nondominant upper extremity endurance, and an increase in nondominant tactile sensation (p < 0.05). No changes were found in two-point discrimination, nine-hole peg test time, and position sense on either side (p > 0.05). The effect of mental fatigue on isometric elbow flexion strength and nondominant grip strength showed significant improvement following diaphragmatic breathing exercises (p < 0.05). Conclusions: This study found that mental fatigue from motor imagery can impact elbow flexion, hand grip strength, upper extremity endurance, and tactile sensitivity. Breathing exercises may help improve strength parameters affected by mental fatigue. It is crucial to consider these effects on upper extremity functions in rehabilitation programs.
Endoscopic Resections for Barrett’s Neoplasia: A Long-Term, Single-Center Follow-Up Study
Authors: Löfdahl Per , Edebo Anders , Wolving Mats , Bratlie Svein Olav
Published: July 2024

Background and Objectives: Endoscopic mucosal resection (EMR) and endoscopic submucosal dissection (ESD) are both well-established and effective treatments for dysplasia and early cancer in Barrett’s esophagus (BE). This study aims to compare the short- and long-term outcomes associated with these procedures in treating Barrett’s neoplasia. Materials and Methods: This single-center retrospective cohort study included 95 patients, either EMR (n = 67) or ESD (n = 28), treated for Barrett’s neoplasia at Sahlgrenska University Hospital between 2004 and 2019. The primary outcome was the complete (en-bloc) R0 resection rate. Secondary outcomes included the curative resection rate, additional endoscopic resections, adverse events, and overall survival. Results: The complete R0 resection rate was 62.5% for ESD compared to 16% for EMR (p < 0.001). The curative resection rate for ESD was 54% versus 16% for EMR (p < 0.001). During the follow-up, 22 out of 50 patients in the EMR group required additional endoscopic resections (AERs) compared to 3 out of 21 patients in the ESD group (p = 0.028). There were few adverse events associated with both EMR and ESD. In both the stratified Kaplan–Meier survival analysis (Log-rank test, Chi-square = 2.190, df = 1, p = 0.139) and the multivariate Cox proportional hazards model (hazard ratio of 0.988; 95% CI: 0.459 to 2.127; p = 0.975), the treatment group (EMR vs. ESD) did not significantly impact the survival outcomes. Conclusions: Both EMR and ESD are effective and safe treatments for BE neoplasia with few adverse events. ESD resulted in higher curative resection rates with fewer AERs, indicating its potential as a primary treatment modality. However, the survival analysis showed no difference between the methods, highlighting their comparable long-term outcomes.
Tricuspid Annular Plane Systolic Excursion-to-Systolic Pulmonary Artery Pressure Ratio as a Prognostic Factor in Heart Transplant Patients
Authors: Huma Laurentiu , Suciu Horatiu , Avram Calin , Suteu Radu-Adrian , Danilesco Alina , Baba Dragos-Florin , Moldovan Diana-Andreea , Sin Anca-Ileana
Published: July 2024

Background and Objectives: Heart transplant is currently the final step in treating patients with heart failure. The success of this procedure is strongly connected to potential complications such as postoperative heart failure, infections, graft rejection, graft vasculopathy, and kidney failure. Thus, identifying potential prognostic factors for patients’ outcome is of utmost importance. We investigated the prognostic role of the postoperative ratio between the tricuspid annular plane systolic excursion (TAPSE) and systolic pulmonary artery pressure (sPAP) in patients who underwent heart transplantation in our center. Materials and Methods: The study included 46 adult patients from the Emergency Institute for Cardiovascular Diseases and Transplant of Târgu Mureș, who underwent heart transplant between January 2011 and April 2023. By the use of receiver operating characteristic (ROC) analysis, we determined an optimal cut-off value for TAPSE/sPAP with regard to survival at 6 months. Differences in central tendencies of baseline characteristics in those who had a value lower than the cut-off value of TAPSE/sPAP and those who presented a value above it were investigated using the corresponding parametric or nonparametric tests. Results: A value for TAPSE/sPAP above 0.47 mm/mmHg was associated with 6-month survival (OR: 59.5, CI: 5.7–616.0). No significant differences in central tendencies for baseline characteristics were found between the patients who had a TAPSE/sPAP ratio below the cut-off and those who had a ratio above it. Conclusions: The TAPSE/sPAP ratio might prove to be valuable in the early identification of at-risk heart transplant patients. Further prospective studies with larger cohorts are required for validation.
Perioperative Marinobufagenin (MBG) Measurement May Improve Acute Kidney Injury Risk Assessment in Patients Undergoing Major Cardiac Surgery: A Proof-of-Concept Study
Authors: Bolignano Davide , Serraino Giuseppe Filiberto , Pizzini Patrizia , Jiritano Federica , Zicarelli Mariateresa , Spoto Belinda , Mobrici Marco , Musolino Michela , Napolitano Désirée , Testa Alessandra , Andreucci Michele , Mastroroberto Pasquale , Coppolino Giuseppe
Published: July 2024

Background and Objectives: Acute kidney injury (AKI) remains a significant complication following major cardiac surgery. Marinobufagenin (MBG), a cardiotonic steroid involved in sodium balance and blood pressure regulation, has been linked to organ damage after ischemia–reperfusion events. This pilot, prospective study investigates the utility of circulating MBG to improve AKI risk assessment in cardiac surgery patients as a stand-alone biomarker and after inclusion in a validated risk model (STS-AKI score). Materials and Methods: We included 45 patients undergoing elective cardiac surgery. The MBG levels were measured preoperatively and at 4, 8, and 12 h post-surgery. The AKI was defined according to the KDIGO guidelines. Statistical analyses assessed the diagnostic and prognostic utility of MBG and its integration with the STS-AKI score. Results: An AKI occurred in 26.7% of the patients. The STS-AKI score performed well in this cohort (AUC: 0.736). The MBG levels displayed a decreasing trend in the whole population after surgery (p = 0.02). However, in the AKI patients, MBG increased at 4 and 8 h before decreasing at 12 h post-surgery. The MBG changes from the baseline to 8 h and from 8 to 12 h post-surgery showed a remarkable diagnostic accuracy for an AKI (AUCs: 0.917 and 0.843, respectively). Integrating these MBG changes with the STS-AKI score significantly improved the model performance, including discrimination, calibration, and risk reclassification. Conclusions: The MBG measurement, particularly any dynamic changes post-surgery, enhances AKI risk stratification in cardiac surgery patients. Integrating MBG with the STS-AKI score offers more accurate risk predictions, potentially leading to better patient management and outcomes.
Exploring Salivary Metabolic Alterations in Type 2 Diabetes: Implications for Dental Caries and Potential Influences of HbA1c and Vitamin D Levels
Authors: Alkahtani Ashwaq , Grootveld Martin , Bhogadia Mohammed , Baysan Aylin
Published: July 2024

Diabetes mellitus is considered to be the most common health issue affecting almost 1 in 11 adults globally. Oral health complications including xerostomia, periodontal disease, dental caries, and soft tissue lesions are prevalent among individuals with diabetes, and therefore an understanding of the potential association between salivary metabolites and dental caries progression would enable the early detection and prevention of this non-communicable disease. Therefore, the aim of this study was to compare salivary biomarkers between individuals with type 2 diabetes (T2DM) with those without this disorder (ND) using 1H NMR-based metabolomics strategies. The objectives were to identify T2DM-associated biomarker signatures and their potential impact on dental caries. In addition, HbA1c and vitamin D levels were also analysed for this purpose. Methods: Stimulated whole-mouth saliva (SWS) samples were collected from T2DM and ND (n = 30 in each case) participants randomly selected from a group of 128 participants recruited for this case–control study. All participants were advised to refrain from eating, drinking, and smoking for at least 1–2 h prior to sample collection. Following preparation, SWS supernatants underwent 1H NMR analysis at an operating frequency of 800 MHz, and the dataset acquired was analysed using a range of multivariate metabolomics techniques. Results: Metabolomics analysis of data acquired demonstrated that, together with up- and downregulated blood HbA1c and vitamin D levels, key salivary discriminators between these two classifications included lactate, taurine, creatinine, α-glucose, and formate to a lesser extent. The bacterial catabolites lactate and formate were both significantly upregulated in the T2DM group, and these have previously been implicated in the pathogenesis of dental caries. Significance analysis of metabolites (SAM)-facilitated AUROC analysis yielded an 83% accuracy for this distinction. Conclusion: In conclusion, this study highlights the significant differences in salivary metabolites between individuals with T2DM and healthy controls. Such differences appear to be related to the development and progression of dental caries in T2DM patients.
Clinically Defined Lymphogranuloma Venereum among US Veterans with Human Immunodeficiency Virus, 2016–2023
Authors: Oda Gina , Chung Joyce , Lucero-Obusan Cynthia , Holodniy Mark
Published: July 2024

We applied lymphogranuloma venereum (LGV) clinical case criteria to a cohort of 1381 Veterans positive for HIV and Chlamydia trachomatis (CT) from 2016 from 2023 and analyzed variables to ascertain risk factors for LGV and factors associated with the use of standard treatment regimens. In total, 284/1381 (20.6%) met the criteria for LGV. A total of 179/284 (63%) were probable cases, and 105/284 (37%) were possible cases (those meeting clinical criteria but with concurrent sexually transmitted infections (STI) associated with LGV-like symptoms). None had confirmatory CT L1–L3 testing. A total of 230 LGV cases (81%) presented with proctitis, 71 (25%) with ulcers, and 57 (20.1%) with lymphadenopathy. In total, 66 (23.2%) patients had >1 symptom of LGV. A total of 43 (15%) LGV cases were hospitalized. Primary risk factors for LGV were male birth sex (p = 0.004), men who have sex with men (p < 0.001), and the presence of STIs other than gonorrhea or syphilis (p = 0.011). In total, 124/284 (43.7%) LGV cases received standard recommended treatment regimens. Probable cases were more likely to receive standard treatment than possible cases (p = 0.003). We report that 20.6% of CT cases met clinical criteria for LGV among HIV-infected Veterans and that less than half of cases received recommended treatment regimens, indicating that LGV is likely underestimated and inadequately treated among this US population.