bluuebunny/crossref_metadata_2025 huggingface dataset:
IGXSS: XSS payload detection model based on inductive GCN
Authors: Wang Qiuhua , Li Chuangchuang , Wang Dong , Yuan Lifeng , Pan Gaoning , Cheng Yanyu , Hu Mingde , Ren Yizhi
Published: February 2024

To facilitate the management, Internet of Things (IoT) vendors usually apply remote ways such as HTTP services to uniformly manage IoT devices, leading to traditional web application vulnerabilities that also endanger the cloud interfaces of IoT, such as cross‐site scripting (XSS), code injection, and Remote Command/Code Execute (RCE). XSS is one of the most common web application attacks, which allows the attacker to obtain private user information or attack IoT devices and IoT cloud platforms. Most of the existing XSS payload detection models are based on machine learning or deep learning, which usually require a lot of external resources, such as pretrained word vectors, to achieve a better performance on unknown samples. But in the field of XSS payload detection, high‐quality vector representations of samples are often difficult to obtain. In addition, existing models all perform substantially worse when the distribution of XSS payloads and benign samples in the test dataset is extremely unbalanced (e.g., XSS payloads: benign samples = 1: 20). While in the real XSS attack scenario against IoT, an XSS payload is often hidden in a massive amount of normal user requests, indicating that these models are not practical. In response to the above issues, we propose an XSS payload detection model based on inductive graph neural networks, IGXSS (XSS payload detection model based on inductive GCN), to detect XSS payloads targeting IoT. Firstly, we treat the samples and words obtained from segmenting the samples as nodes and attach lines between them in order to form a graph. Then, we obtain the feature matrix of nodes and edges utilizing information between nodes only (instead of external resources such as pretrained word vectors). Finally, we feed the obtained feature matrix into a two‐layer GCN for training and validate the performance of models in several datasets with different sample distributions. Extensive experiments on the real datasets show that IGXSS performs better compared to other models under various sample distributions. In particular, when the sample distribution is extremely unbalanced, the recall and F1 score of IGXSS still reach 1.000 and 0.846, demonstrating that IGXSS is more robust and more suitable for practical scenarios.
Survival Outcomes of Temporal Bone Squamous Cell Carcinoma: A Systematic Review and Meta‐Analysis
Authors: Sioufi Krystelle , Haynes Aaron David , Gidley Paul W. , Maniakas Anastasios , Roberts Dianna , Nader Marc‐Elie
Published: February 2024

Objective

Temporal bone squamous cell carcinoma (TBSCC) is a rare malignancy with poor prognosis, and optimal treatment for advanced cases is uncertain. Our systematic literature review aimed to assess 5‐year survival outcomes for advanced TBSCC across different treatment modalities.

Data Sources

EMBASE, Medline, PubMed, and Web of Science.

Review Methods

A systematic literature review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses guidelines for articles published between January 1989 and June 2023.

Results

The review yielded 1229 citations of which 31 provided 5‐year survival data for TBSCC. The final analysis included 1289 patients. T classification data was available for 1269 patients and overall stage for 1033 patients. Data for 5‐year overall survival (OS) was 59.6%. Five‐year OS was 81.9% for T1/2 and 47.5% for T3/4 (P < .0001). OS for T1/T2 cancers did not significantly differ between surgery and radiation (100% vs 81.3%, P  = .103). For advanced‐stage disease (T3/T4), there was no statistical difference in OS when comparing surgery with postoperative chemoradiotherapy (CRT) (OS 50.0%) versus surgery with postoperative radiotherapy (XRT) (OS 53.3%) versus definitive CRT (OS 58.1%, P  = .767‐1.000). There was not enough data to assess the role of neoadjuvant CRT.

Conclusion

Most patients will present with advanced‐stage disease, and nodal metastasis is seen in nearly 22% of patients. This study confirms the prognostic correlation of the current T classification system. Our results suggest that OS did not differ significantly between surgery and XRT for early stage disease, and combined treatment modalities yield similar 5‐year OS for advanced cancers.
Effect of carbon nanotubes on thermoset curing and mechanical properties of carbon fiber reinforced epoxy resin laminates fabricated by self‐resistance electric heating
Authors: Zhang Hongming , Zhao Gaoyin , Li Xin , Hao Zhiwei , Zhong Zhiwen
Published: February 2024

Self‐resistance electric (SRE) heating for the curing of carbon fiber reinforced plastic (CFRP) offers the benefits of saving energy consumption and reducing investment in equipment. In this work, the investigation was carried out to illustrate the effect of carbon nanotubes (CNTs) addition (0.5, 1.0, and 1.5 wt%) on the thermoset curing and mechanical properties of carbon fiber‐reinforced epoxy laminates fabricated by SRE heating method. The results show that adding CNTs can improve the temperature uniformity and interlayer‐resin flow during the SRE heating process and have a limited influence on the curing degree of CFRP composites. The tensile strength in the longitudinal direction of the composites increased with the increase of CNT addition. Meanwhile, the flexural strength and interlaminar shear strength had the maximum value with the CNTs content of 0.5 wt% and decreased significantly at the CNTs content of 1.5 wt%. It concludes that the appropriate content of CNTs addition has the potential to improve the thermoset curing performance and mechanical properties of the CFRP laminate composites fabricated by SRE heating.

Highlights

This study focuses on the effect of CNT addition on SRE heating for CFRP.

The addition of CNTs improved the temperature uniformity during SRE heating.

The addition of CNTs can reduce the voids of SRE‐cured CFRP composites.

Threshold value of CNTs affected the mechanical performance of SRE‐cured CFRP.
Coextruded polylactide/encapsulated cinnamon essential oil/graphene nanoplatelets trilayer films: Morphological, barrier, thermal, rheological and antimicrobial properties
Authors: Ahmed Jasim , Bher Anibal , Jacob Harsha , Al‐Zuwayed Sheikha A. , Auras Rafael
Published: February 2024

Polylactide (PLA)‐based biodegradable three‐layer packaging film was fabricated using PLA, PLA/cinnamon oil (CEO), and PLA/graphene nanoplatelets (GNP). The central layer allows control over the release of antimicrobes, and the outer layer adds mechanical strength to the films. A comparison has been made on barrier, thermal, rheological, microstructural, and microbiological properties between single‐layer and multilayer films (MLF). The water vapor and oxygen barrier properties of MLF showed little reduction compared with those of neat PLA. The tensile stress of the neat PLA increased significantly from 23.31 to 35.91 MPa for the MLF. Thermal analysis data showed improvements in the thermal stability of the MLF film, with onset and peak temperatures of 331.5 and 357.1°C, respectively. The dispersion of GNP in the PLA matrix and in MLF was assessed by XRD analysis and rheological measurement. The AFM roughness parameters Sa and Sq of those films varied widely, with the highest (13.9 and 20.9 μm) and the lowest (0.08 and 0.11 μm) magnitudes recorded for PLA/GNP and PLA/CEO films, respectively. Antibacterial assays of the film confirmed a strong bactericidal effect against Listeria monocytogenes and Salmonella typhimurium, maintaining this activity for 21 days.

Highlights

Polylactide/cinnamon oil/ graphene nanoplatelet multilayer films were coextruded.

X‐ray diffraction and rheology confirm the dispersion of graphene into PLA.

Tensile stress and thermal stability improved in the multilayer films.

AFM roughness parameters varied significantly between single‐ and multilayer films.

Antibacterial assays confirmed the strong bactericidal effect of films against pathogens.
Nonassociative Geometric and Quantum Information Flows and R‐Flux Deformations of Wormhole Solutions in String Gravity
Authors: Bubuianu Laurenţiu , Singleton Douglas , Vacaru Sergiu I. , Veliev Elşen Veli
Published: February 2024

This article consists of an introduction to the theory of nonassociative geometric classical and quantum information flows defined by star products with R‐flux deformations in string gravity. Corresponding nonassociative generalizations of the concepts of classical Shannon entropy, quantum von Neumann entropy, Rényi entropy are formulated. The fundamental geometric and quantum information objects are computed following the Grigori Perelman statistical thermodynamic approach to Ricci flows and gravity theories generalized for phase spaces modeled as (co) tangent Lorentz bundles. Nonassociative parametric deformations and nonholonomic thermo‐geometric versions of statistical generating functions, their quantum analogues as density matrices are considered for deriving the entropy, energy and fluctuation functionals. This allows us to define and compute respective classical and quantum relative and conditional entropies, mutual information and nonassociative entanglement and thermodynamic information variables. The principles of nonassociative quantum geometric and information flow theory, QGIF, and study the basic properties of such quasi‐stationary models related to modified gravity theories are formulated. Applications are considered for nonassociative deformed and entangled couples of four‐dimensional (4‐d), wormholes (defined by respective spacetime and/or momentum type coordinates) and nonassociative QGIFs of 8‐d phase space generalized wormholes configurations. Finally, phase space black holes and wormholes being transversable for nonassociative qubits, quantum channels and entanglement witness are speculated; thought and laboratory experiments are discussed; and perspectives for quantum computer modeling and tests of nonassociative geometric flow and gravity theories are considered.
de Sitter Versus Anti‐de Sitter in Horndeski‐Like Gravity
Authors: Santos Fabiano F. , Pourhassan Behnam , Saridakis Emmanuel N.
Published: February 2024

The general solutions of Horndeski‐like gravity that can interpolate between the de Sitter and anti‐de Sitter regimes are presented. In particular, the first‐order formalism with two scalar fields is developed, and considering a black hole ansatz with flat slicing, three different cases, namely exponential, vacuum, and smooth superpotential solutions, with no Minkowski extrema are investigated. Furthermore, these solutions show that a Renormalization Group flow is established, and a turnaround in the warp factor is obtained, where the transition is bounded by the area low. The ideal regimes to trap gravity, which are constructed using the holographic function, which provides stable and unstable regimes to localize gravity are discussed. Finally, it is shown that no ghost appear and that the matter sector that violates the ‐theorem is physical.
Nonequilibrium Dynamics of the Hubbard Dimer
Authors: Pavlyukh Yaroslav
Published: February 2024

Electron dynamics in a two‐sites Hubbard model is studied using the nonequilibrium Green's function approach. The study is motivated by the empirical observation that a full solution of the integro‐differential Kadanoff–Baym equation (KBE) is more stable and often accompanied by artificial damping [Marc Puig von Friesen, C. Verdozzi, and C.‐O. Almbladh (2009)] than its time‐linear reformulations relying on the generalized Kadanoff–Baym ansatz (GKBA). Additionally, for conserving theories, numerical simulations suggest that KBE produces natural occupations bounded by one and zero in agreement with the Pauli exclusion principle, whereas, in some regimes, GKBA‐based theories violate this principle. As the first step for understanding these issues, the electron dynamics arising in the adiabatic switching scenario is studied. Many‐body approximations are classified according to the channel of the Bethe–Salpeter equation in which electronic correlations are explicitly treated. They give rise to the so‐called second Born, T‐matrix, and GW approximations. In each of these cases, the model is reduced to a system of ordinary differential equations, which resemble equations of motion for a driven harmonic oscillator with time‐dependent frequencies. A more complete treatment of electronic correlations is achieved by combining different correlation channels, with parquet theory serving as a starting point.
Asymmetric Electronic Transport in Porphine: Role of Atomically Precise Tip Electrode
Authors: Das Koushik R. , Dutta Sudipta
Published: February 2024

Electronic conductance through a single molecule is sensitive to its structural orientation between two electrodes, owing to the distribution of molecular orbitals and their coupling to the electrode levels, that are governed by quantum confinement effects. Herein, the contact geometry of the porphine molecule is varied by attaching two Au tip electrodes that resemble the mechanical break junction, via thiol anchoring groups, is varied. The current–voltage characteristics of all the contact geometries are investigated using nonequilibrium Green's function formalism along with density functional theory and tight‐binding framework. Varying current responses are observed with changing contact sites, originating from varied wave‐function delocalization and quantum interference effect. The calculations show asymmetric current–voltage characteristics under forward and reverse biases due to structural asymmetry of the tip electrodes on either side of the molecule. This phenomenon is established as a universal feature for any molecular electronic device, irrespective of the inherent structural symmetry of a molecule. These findings provide fundamental insights into electronic transport through single molecules in the real experimental setup. Furthermore, the observations of varying current response can further motivate the fabrication of sensor devices with porphine‐based biomolecules that control important physiological activities, in view of their applications in advanced diagnostics.
Unravelling the role of Silibinin in targeting CD44+ cancer stem cells: Therapeutic implications, effective strategies and approaches
Authors: Lotia Shreya , Patel Shanaya , Patel Aditi , Patel Vaishnavi , Shah Kanisha , Tanavde Vivek
Published: February 2024

CD44+ cancer stem cells (CSCs) are believed to account for drug resistance and tumour recurrence due to their potential to self‐renew and differentiate into heterogeneous lineages. Therefore, efficient treatment strategies targeting and eliminating these CSCs are required. The flavonolignan, Silibinin, has gained immense attention in targeting CD44+ CSCs as it alters functional properties like cell cycle arrest, apoptosis, inhibition of invasion and metastasis and also inhibits a range of molecular pathways. However, its limited bioavailability is a major hurdle in asserting Silibinin as a translational therapeutic agent. Combinatorial therapy of Silibinin with conventional chemotherapeutic drugs is an alternative approach in targeting CD44+ CSCs as it increases the efficacy and reduces the cytotoxicity of chemotherapeutic drugs, thus preventing drug resistance. Certain Silibinin‐conjugated nano‐formulations have also been successfully developed, through which there is improved absorptivity/bioavailability of Silibinin and a decrease in the concentration of therapeutic drugs leading to reduced cytotoxicity. In this review, we summarise the effectiveness of the synergistic therapeutic approach for Silibinin in targeting the molecular mechanisms of CD44+ CSCs and emphasise the potential role of Silibinin as a novel therapeutic agent.
Reproducible research practices: A tool for effective and efficient leadership in collaborative statistics
Authors: Hochheimer Camille J. , Bosma Grace N. , Gunn‐Sandell Lauren , Sammel Mary D.
Published: February 2024

With data and code sharing policies more common and version control more widely used in statistics, standards for reproducible research are higher than ever. Reproducible research practices must keep up with the fast pace of research. To do so, we propose combining modern practices of leadership with best practices for reproducible research in collaborative statistics as an effective tool for ensuring quality and accuracy while developing stewardship and autonomy in the people we lead. First, we establish a framework for expectations of reproducible statistical research. Then, we introduce Stephen M.R. Covey's theory of trusting and inspiring leadership. These two are combined as we show how stewardship agreements can be used to make reproducible coding a team norm. We provide an illustrative code example and highlight how this method creates a more collaborative rather than evaluative culture where team members hold themselves accountable. The goal of this manuscript is for statisticians to find this application of leadership theory useful and to inspire them to intentionally develop their personal approach to leadership.
Recruitment and baseline data of the Aging and Cognitive Health Evaluation in Elders (ACHIEVE) study: A randomized trial of a hearing loss intervention for reducing cognitive decline
Authors: Reed Nicholas S. , Gravens‐Mueller Lisa , Huang Alison R. , Goman Adele M. , Mitchell Christine M. , Arnold Michelle L. , Bolton Spencer , Burgard Sheila , Chisolm Theresa H. , Couper David , Deal Jennifer A. , Evans Joshua , Faucette Sarah , Glynn Nancy W. , Gmelin Theresa , Hayden Kathleen M. , Miller Elizabeth , Minotti Melissa , Mosley Thomas , Naylor Stacee , Pankow James S. , Pike James Russell , Sanchez Victoria A. , Schrack Jennifer A. , Coresh Josef , Lin Frank R. ,   for the ACHIEVE Collaborative Research Group
Published: February 2024

INTRODUCTION

Hearing loss is highly prevalent among older adults and independently associated with cognitive decline. The Aging and Cognitive Health Evaluation in Elders (ACHIEVE) study is a multicenter randomized control trial (partially nested within the infrastructure of an observational cohort study, the Atherosclerosis Risk in Communities [ARIC] study) to determine the efficacy of best‐practice hearing treatment to reduce cognitive decline over 3 years. The goal of this paper is to describe the recruitment process and baseline results.

METHODS

Multiple strategies were used to recruit community‐dwelling 70–84‐year‐old participants with adult‐onset hearing loss who were free of substantial cognitive impairment from the parent ARIC study and de novo from the surrounding communities into the trial. Participants completed telephone screening, an in‐person hearing, vision, and cognitive screening, and a comprehensive hearing assessment to determine eligibility.

RESULTS

Over a 24‐month period, 3004 telephone screenings resulted in 2344 in‐person hearing, vision, and cognition screenings and 1294 comprehensive hearing screenings. Among 1102 eligible, 977 were randomized into the trial (median age = 76.4 years; 53.5% female; 87.8% White; 53.3% held a Bachelor's degree or higher). Participants recruited through the ARIC study were recruited much earlier and were less likely to report hearing loss interfered with their quality of life relative to participants recruited de novo from the community. Minor differences in baseline hearing or health characteristics were found by recruitment route (i.e., ARIC study or de novo) and by study site.

DISCUSSION

The ACHIEVE study successfully completed enrollment over 2 years that met originally projected rates of recruitment. Substantial operational and scientific efficiencies during study startup were achieved through embedding this trial within the infrastructure of a longstanding and well‐established observational study.

Highlights

The ACHIEVE study tests the effect of hearing intervention on cognitive decline.

The study is partially nested within an existing cohort study.

Over 2 years, 977 participants recruited and enrolled.

Eligibility assessed by telephone and in‐person for hearing, vision, and cognitive screening.

The ACHIEVE study findings will have significant public health implications.
Characterization of annealed‐silane modified barley husk biosilica and garment waste cotton microfiber vinyl ester composite
Authors: G Suganya , Kandavalli Sumanth Ratna , Sahu Santosh Kumar , Chanakyan C.
Published: February 2024

This study investigates the effect of adding annealed‐silane modified biosilica and waste cotton microfiber into the vinyl‐based composite on load‐bearing properties. The primary objective of this study was to unveil the significance of annealing treatment on the biosilica and its effect on composite's properties. The biosilica was prepared from waste barely husk ash and the waste cotton microfiber was used as received. The composites were fabricated using mold casting method and their properties were assessed in accordance with ASTM standards. Among the composites examined, the VCB2 displays improved mechanical properties with a highest tensile strength of 120 MPa. In contrast, the VCB3 composite exhibited enhanced hardness with a low specific wear rate of 0.22 mm3/N m and a coefficient of friction of 0.19. Furthermore, the composite VCB3 demonstrated an elevated dielectric constant of 3.85 and a low dielectric loss of 0.136 with a high thermal stability up to 388°C. This study underscores the potential of annealing process on biosilica and its stress free grain structure in property improvement made as valuable reinforcement in waste cotton microfiber‐vinyl ester composites, opening up new avenues for diverse engineering applications with advanced material performance.

Highlights

Vinyl ester composites are prepared from waste biomass biosilica and cotton microfiber.

Addition of biosilica improved the void filling effect of matrix.

Addition of biosilica improved the mechanical properties.

Addition of biosilica up to 3 vol.% improved the wear properties.

Addition of biosilica up to 3 vol.% improved the thermal stability.
Effect of zero‐valent iron (ZVI) and biogas slurry reflux on methane production by anaerobic digestion of waste activated sludge
Authors: He Junguo , Cui Xinxin , Chu Zhaorui , Jiang Zhifeng , Pang Heliang , Xin Xiaodong , Duan Shengye , Zhong Yijie
Published: February 2024

This study aimed to improve anaerobic digestion (AD) efficiency through the addition of zero‐valent iron (ZVI) and biogas slurry. This paper demonstrated that methane production was most effectively promoted at a biogas slurry reflux ratio of 60%. The introduction of ZVI into anaerobic systems does not enhance its bioavailability. However, both biogas slurry reflux and the combination of ZVI with biogas slurry reflux increase the relative abundance of microorganisms involved in the direct interspecific electron transfer (DIET) process. Among them, the dominant microorganisms Methanosaeta, Methanobacterium, Methanobrevibacter, and Methanolinea accounted for over 60% of the total methanogenic archaea. The Tax4Fun function prediction results indicate that biogas slurry reflux and the combination of ZVI with biogas slurry reflux can increase the content of key enzymes in the acetotrophic and hydrotrophic methanogenesis pathways, thereby strengthening these pathways. The corrosion of ZVI promotes hydrogen production, and the biogas slurry reflux provided additional alkaline and anaerobic microorganisms for the anaerobic system. Their synergistic effect promoted the growth of hydrotrophic methanogens and improved the activities of various enzymes in the hydrolysis and acidification phases, enhanced the system's buffer capacity, and prevented secondary environmental pollution.

Practitioner Points

Optimal methane production was achieved at a biogas slurry reflux ratio of 60%.

Biogas slurry reflux in anaerobic digestion substantially reduced discharge.

ZVI addition in combination with biogas slurry reflux facilitates the DIET process.
Melting heat transmission of Maxwell nanofluid flow caused due to a stretchable cylindrical pipe through Finite Element Technique
Authors: Saif Rai Sajjad , Alhowaity Awatif , Afzaal Muhammad F. , Mahrous Yussri Mohammad , Muhammad Taseer
Published: February 2024

The objective of current investigation is to examine Maxwell fluid flow generated by cylindrical stretching pipe. Thermophoresis and Brownian moment phenomena will also incorporate on the said fluid. Melting heat shifting phenomenon incorporated at the surface of the elongating cylinder. Mathematical formulation is supported by boundary layer assumption. Suitable similarity transformations diminishes model of nonlinear partial differential equations  into a model of nonlinear ordinary differential equations  that ultimately solved via numerical technique named Finite Element Technique. The properties of numerous effective variables are graphically displayed and examined. Further the physical quantities like velocity gradient, heat and mass fluxes are tabulated numerically and analyzed. The dimensionless temperature distribution rises for rising values of curvature parameter and Brownian motion parameter however an opposite behavior is observed for melting parameter and Prandtl number. Moreover, a reduction occurs in heat and mass fluxes for sufficiently high values of curvature parameter.
Stability analysis of GO‐EG and GO‐blood base nanofluids by implementing of thermal radiation phenomena
Authors: Rehman Ali , Zeb Muhammad , Khun Ma Chau , Imran Ali , Ahmad Sohail , Ghazwani Hassan Ali
Published: February 2024

This work leaves to explore the stability of a 2‐D, time free, thermal boundary layer of graphene oxide ethylene glycol (GO‐EG,) where GO‐blood is taken as base nanofluids over a stretchable surface by executing a magnetic field (MHD), coupled stress effects, heat source/sink, and sun‐oriented radiations. This work is done due to the reason that nanofluids have a higher heat conductivity level rather than regular liquids. Nonlinear partial differential equations (N‐PDEs) are modeled utilizing the notable boundary layer equations. Dimensionless ordinary differential conditions (ODEs) are made from the created NPDEs by utilizing dimensional analysis and group theoretic approach. We examine the obtained ODEs through the notable homotopy analysis technique (HAM). The impacts of different parameters on temperature distribution and velocity profiles are shown graphically. However, some tables are constructed in support of the presented study to confirm the stability and convergence of the solutions. The main intentions in this work are to underline the enhancement of traditional heat transfer's thermal conductivity.
Numerical simulation of magneto thermal Marangoni convective flow of dusty Sutterby hybrid nanofluid with variable thermal conductivity
Authors: Abbas Munawar , Khan Nargis , Hashmi Muhammad Sadiq , Inc Mustafa
Published: February 2024

The current study concentrated on the 2‐D flow of a dusty, Magnetohydrodynamics (MHD) Sutterby hybrid nanofluid flowing across a surface in a Darcy–Forchheimer medium. The Cattaneo–Christov heat flux model and variable thermal conductivity properties are taken into description. Marangoni convective boundary conditions are taken into consideration while the thermal flow analysis is examined. Some of the applications of Marangoni convection include thin‐film diffusion, the formation of molten crystals, semiconductor fabrication, and the growth of vapor bubbles during nucleation. Hybrid nanofluid is made up of two nanoparticles ( and one base fluid . Determining the Marangoni convective flow of dusty hybrid nanofluid thermal mobility with ethylene glycol base fluids is the main objective of this investigation. The accepted nanoparticles and dust particles are assigned a spherical shape. The problem has been modeled using nonlinear partial differential equations. With the use of transformation, the partial differential equations (PDEs) system is reduced to a set of ordinary differential equation (ODEs). The problem is mathematically stated, and then using the RKF‐45th approach, it is numerically solved. Tables and graphs are used to assess the effects of the physical parameters of the current problem, such as the Deborah number, Eckert number and thermal relaxation parameter. The thickness of the momentum boundary layer decreases by growing the inverse Darcy number and the Forchheimer parameter for both phases. The velocity profiles of the dust and fluid phases are improved by greater estimates of the Deborah number.
Artificial neural network of thermal Buoyancy and Fourier flux impact on suction/injection‐based Darcy medium surface filled with hybrid and ternary nanoparticles
Authors: Dinesh Kumar Maddina , Siva Krishnam Raju Chakravarthula , El‐Zahar Essam R. , Shah Nehad Ali , Yook Se‐Jin
Published: February 2024

This study's main objective is to analyze the heat and velocity transfer rate with various effects such as the suction and buoyancy effects on a stretching sheet with ternary hybrid nanofluid flow via a porous medium. Ternary hybrid nanofluid is Case‐1 Ag‐TiO2 with base fluid H2O and Case‐2 CNT + Graphene + Al2O3 with base fluid H2O. Hybrid nanofluids have been used to speed up the heat transfer process, following Lie group transformations are used to transform non‐linear Partial Differential Equations (PDEs) into Ordinary Differential Equations (ODEs). The boundary value problem solver was used in conjunction with the ODE45 numerical approach to solve the resulting Ordinary differential equations. On a stretchy surface, the overall relationship between temperature, velocity, shear stress, and heat transfer rate are shown for a range of values of the significant factors. The temperature profiles have been rising with the impact of Da and fw. Utilizing streamlines and a machine learning technique to examine the flow pattern of a fluid. Artificial neurons or nodes make up a neural network, which is known as a neural network in the sense that the term is used today. A network or circuit of biological neurons is referred to as a neural network.
Numerical computation of joule heating and chemical reaction for the radiated Casson fluid on the slender parabolic surface
Authors: Salahuddin T. , Awais Muhammad
Published: February 2024

This work dealing to solve the numerical results of magnetohydrodynamic flow material (Casson fluid) moving over the slender parabolic surface with temperature dependent viscosity. To make the enhancement in the thermal and solutal fields, we have determined the impact of thermal radiation, viscous dissipation, joule heating, and chemical reaction on the considered flow material. Due to huge applications in coating processes and aerodynamic industries, the suction/Injection is assumed at the surface. With the help of assumed assumptions, the governing equations are obtained in partial differential equation forms, and these equations are translated into ordinary differential equations form by using the Levy‐Lee similarity transformations. The translated forms of ODE's are then numerically solved by using the Adams‐Milne (Predictor–Corrector) technique. The graphical and numerical findings are determined by producing the emerging parameters. The decrement in velocity is noted due to fluid parameter and suction coefficient whereas the enhancement happens due to natural convection. The numerical determination of physical quantities including, Nusselt number, Skin friction and Sherwood number are also examined here and compared the findings with two numerical techniques (Adam‐Milnes and Bvp4c method).
ANN model for magnetised Casson fluid flow under the influence of thermal radiation and temperature stratification: Comparative analysis
Authors: Tanveer Arooj , Ashraf Muhammad Bilal
Published: February 2024

The article compares the performance of multi‐layer back‐propagated neural networks using the Levenberg–Marquardt (LMS) method and Bayesian Regularization Scheme (BRS) for analysing heat transfer in magnetized Casson fluid over flat and cylindrical surfaces. Factors like mixed convection, Joule heating, thermal radiation and temperature stratification are considered. Both LMS and BRS prove effective in handling complex interactions in numerical studies. Non‐linear ODE systems are solved using a shooting technique to obtain Nusselt number datasets, which are then divided for training, testing and validation purposes. The accuracy of the artificial neural network (ANN) results is confirmed by the agreement between predicted and target Nusselt numbers. Analysis of mean square error (MSE), regression fitness and error histogram further validates ANN adeptness. Furthermore, heat transfer rate is increasing for the Casson parameter, Grashof number and radiation parameter, while, it declines for stratification parameter, Prandtl and Eckert number. The study explores the impact of various parameters on velocity and temperature profiles, revealing that ANN provides accurate Nusselt number results for both flat and cylindrical surfaces. The research contributes a novel perspective to understanding ANN behaviour in heat transfer analysis, particularly for magnetized Casson fluid flow over two stretching surfaces.
Polynomial stability of piezoelectric beams with magnetic effect and tip body
Authors: An Yanning , Liu Wenjun , Kong Aowen
Published: February 2024

In this paper, we consider a dissipative system of one‐dimensional piezoelectric beam with magnetic effect and a tip load at the free end of the beam, which is modeled as a special form of double boundary dissipation. Our main aim is to study the well‐posedness and asymptotic behavior of this system. By introducing two functions defined on the right boundary, we first transform the original problem into a new abstract form, so as to show the well‐posedness of the system by using Lumer–Phillips theorem. We then divide the original system into a conservative system and an auxiliary system, and show that the auxiliary problem generates a compact operator. With the help of Weyl's theorem, we obtain that the system is not exponentially stable. Moreover, we prove the polynomial stability of the system by using a result of Borichev and Tomilov (Math. Ann. 347 (2010), 455–478).
Thermal vibration of armchair, chiral, and zigzag types of single walled carbon nanotubes using a nonlocal elasticity theory: An analytical approach
Authors: Jena Subrat Kumar , Pradyumna S. , Chakraverty S.
Published: February 2024

This research delves into the study of thermal vibration characteristics exhibited by three distinct types of Single‐Walled Carbon Nanotubes (SWCNTs): armchair, chiral, and zigzag configurations. The investigation is carried out using Navier's technique, which integrates a non‐local elasticity theory and Euler‐Bernoulli beam theory, providing a comprehensive understanding of carbon nanotubes (CNT) behavior under varying temperature conditions. To explore these characteristics, governing equations for vibrations are derived based on Hamilton's principle, incorporating both non‐local stress resultants. These equations are instrumental in computing the natural frequencies of Hinged‐Hinged (HH) SWCNTs subjected to low (room) and high‐temperature conditions. A detailed exploration is conducted to evaluate the influence of several key scaling parameters. These parameters encompass small‐scale effects, temperature variations, the thermal environment, and the length‑to‑thickness ratio of the CNTs, scrutinizing their impact on the first and second mode natural frequencies. This comprehensive assessment sheds light on the multifaceted interplay between these factors and the resulting vibration behaviors in SWCNTs.
From Industry 4.0 to Industry 5.0: The Triple Transition Digital, Green and Social
Authors: Schröder Antonius Johannes , Cuypers Mathias , Götting Adrian
Published: February 2024

The paradigm Industry 5.0, to which the European Commission recently dedicated a conceptual report, focuses on both a sustainable and a human-centric and resilient industry: human-centric by using technology primarily for the benefit of people, sustainable by not harming the environment, and resilient by contributing to the security of supply and autonomous supply chains (Breque et al. in Industry 5.0: towards a sustainable, human-centric and resilient European industry. European Commission, Brussels: 14–16). This concept is no turn away from Industry 4.0 but is looking at the mainly technology-dominated approach of Industry 4.0 with a new lens and new priorities. Based on the approach of combining technological and social innovation within a common development process we will give some practical insights on how to coordinate change processes. The aim is to achieve solutions that are beneficial from several perspectives: e.g. social, economic and ecological. Grounded in our experience from industry-related multi-stakeholder projects this chapter discusses various concepts that can be applied within the Industry 5.0 approach. Particular attention is paid to the significance and importance of skills and human resources in the digital and green transformation. Additionally, the relevance of the social innovation approach is shown, leading to new practices to address societal challenges via the human-centred, sustainable and resilient Industry 5.0 perspective. The empirical background is given by the concepts and first results of our European projects for enhancing the digital and green transformation by a social transition.
Aiming for Industry 4.0: The Case of the Czech Republic
Authors: Ďurčo Roman , Pielesz Marcel , Sakařová Dana
Published: February 2024

Industry 4.0 (also Work 4.0 or the fourth industrial revolution) is the name for the current trend of digitization, the related automation of production and the changes in the labour market that it will bring. Industry 4.0 will be accompanied by a change in the labour market, which could cause a threat to the employment of people for whom computers with new management/decision-making systems or robotic systems controlled by these systems will replace human power (for example, production lines that will replace workers with lower qualifications). New jobs will be created, but they will require higher qualification of employees. This chapter is focused on Industry 4.0 in the Czech steel sector, it focuses on the steel industry in Ostrava, where the steel industry is mainly concentrated. It goes back to the beginnings of steelmaking in the middle of the eighteenth century and maps the gradual development and resulting changes not only for the steel sector itself, but for the entire Ostrava region. In the end, it deals with the possible future of the steel industry in the Czech Republic.
Disparities in prehospital and emergency surgical care among patients with perforated ulcers and a history of mental illness: a nationwide cohort study
Authors: Mackenhauer Julie , Christensen Erika Frischknecht , Mainz Jan , Valentin Jan Brink , Foss Nicolai Bang , Svenningsen Peter Olsen , Johnsen Søren Paaske
Published: February 2024

Purpose

To compare patients with and without a history of mental illness on process and outcome measures in relation to prehospital and emergency surgical care for patients with perforated ulcer.

Methods

A nationwide registry-based cohort study of patients undergoing emergency surgery for perforated ulcer. We used data from the Danish Prehospital Database 2016–2017 and the Danish Emergency Surgery Registry 2004–2018 combined with data from other Danish databases. Patients were categorized according to severity of mental health history.

Results

We identified 4.767 patients undergoing emergency surgery for perforated ulcer. Among patients calling the EMS with no history of mental illness, 51% were identified with abdominal pain when calling the EMS compared to 31% and 25% among patients with a history of moderate and major mental illness, respectively. Median time from hospital arrival to surgery was 6.0 h (IQR: 3.6;10.7). Adjusting for age, sex and comorbidity, patients with a history of major mental illness underwent surgery 46 min (95% CI: 4;88) later compared to patients with no history of mental illness. Median number of days-alive-and-out-of-hospital at 90-day follow-up was 67 days (IQR: 0;83). Adjusting for age, sex and comorbidity, patients with a history of major mental illness had 9 days (95% CI: 4;14) less alive and out-of-hospital at 90-day follow-up.

Conclusion

One-third of the population had a history of mental illness or vulnerability. Patients with a history of major mental illness were less likely to be identified with abdominal pain if calling the EMS prior to arrival. They had longer delays from hospital arrival to surgery and higher mortality.
Human umbilical cord mesenchymal stem cells improve uterine incision healing after cesarean delivery in rats by modulating the TGF-β/Smad signaling pathway
Authors: Sun Qing , Zhang Dan , Ai Qiuying , Yue Yang , Wang Haijiao , Tang Le , Yi Xiling , Wang Siyuan , Zheng Yang
Published: February 2024

Objective

Although human umbilical cord-derived mesenchymal stem cells (HU-MSCs) have attracted increasing attention because of their pivotal functions in the process of wound healing, the underlying molecular mechanisms have been poorly understood. It has been shown that the TGF-β/Smad signaling pathway plays an important role in the process of scar formation. The present study focused on exploring whether HU-MSCs improve uterine incision healing after cesarean delivery in rats via the TGF-β/Smad signaling pathway.

Study Design

Pregnant rats were randomly assigned to three groups, including the NP group, incision-injected group (HU-MSCs1 group), and tail vein-injected group (HU-MSCs2 group), and 30 days after cesarean section, sampling was carried out to further explore the specific mechanisms from tissue and protein levels.

Results

HU-MSCs secretion could inhibit the fibrosis of scar tissue. We observed that the TGF-β induced expression of TGF-β1, Smad2, and Smad3 was attenuated upon HU-MSCs treatment in scar tissue, while the decrease in TGF-β3 expression was enhanced by HU-MSCs. Furthermore, HU-MSCs treatment accelerated wound healing and attenuated collagen deposition in a damaged uterine rat model, leading to the promoting of uterine incision scarring. In addition, the expression of alpha-smooth muscle actin (a-SMA) was enhanced by HU-MSCs treatment.

Conclusion

HU-MSCs transplantation promotes rat cesarean section uterine incision scar healing by modulating the TGF-β/Smad signaling pathway.
Prodromal multiple sclerosis: considerations and future utility
Authors: Harding Katharine E. , Kreft Karim L. , Ben-Shlomo Yoav , Robertson Neil P.
Published: February 2024

A multiple sclerosis (MS) prodrome has recently been described and is characterised by increased rates of healthcare utilisation and an excess frequency of fatigue, bladder problems, sensory symptoms and pain, in the years leading up to clinical onset of disease. This important observation may have several potential applications including in the identification of risk factors for disease, the potential to delay or prevent disease onset and early opportunities to alter disease course. It may also offer possibilities for the use of risk stratification algorithms and effective population screening. If standardised, clearly defined and disease specific, an MS prodrome is also likely to have a profound influence on research and clinical trials directed at the earliest stages of disease. In order to achieve these goals, it is essential to consider experience already gleaned from other disorders. More specifically, in some chronic neurological disorders the understanding of disease pro-drome is now well advanced and has been successfully applied. However, understanding of the MS prodrome remains at an early stage with key questions including the length of the prodrome, symptom specificity and potential benefits of early intervention as yet unanswered. In this review we will explore the evidence available to date and suggest future research strategies to address unanswered questions. In addition, whilst current understanding of the MS prodrome is not yet sufficient to justify changes in public health policy or MS management, we will consider the practical utility and future application of the MS prodrome in a wider health care setting.
Fractal dimensions and machine learning for detection of Parkinson’s disease in resting-state electroencephalography
Authors: Lal Utkarsh , Chikkankod Arjun Vinayak , Longo Luca
Published: February 2024

Parkinson’s disease (PD) is an incurable neurological disorder that degenerates the cerebrospinal nervous system and hinders motor functions. Electroencephalography (EEG) signal analysis can provide reliable information regarding PD conditions. However, EEG is a complex, multichannel, and nonlinear signal with noise that problematizes identifying PD symptoms. A few studies have employed fractal dimension (FD) to extract distinguishing PD features from EEG signals. However, no exploratory study exists, as per our knowledge, on the efficiency of the different FD measures. We aim to conduct a comparative analysis of the various FDs that, as feature extraction measures, can discriminate PD patients who are ON and OFF medication from healthy controls using ML architecture. This study has implemented and analyzed several techniques for segmentation, feature extraction, and ML models. The results show that k-nearest neighbors (KNN) classifier with Higuchi FD and 90% overlap for segmented window delivers the highest accuracies, yielding a mean accuracy of $$99.65\pm 0.15\%$$

99.65
±
0.15
%

for PD patients ON medication and $$99.45\pm 0.18\%$$

99.45
±
0.18
%

for PD patients OFF medication, respectively. The model accurately identifies the signs of the disease in resting-state EEG with almost equivalent accuracy in both OFF and ON medication patients. To enhance the interpretability in our study, we leveraged XGB’s feature importance to generate brain topographic plots. This integration of explainable AI (XAI) enhanced the transparency and comprehensibility of our model’s classifications. Additionally, a comparison between the performance of FD and a few entropy measures has also been drawn to validate the significance of FD as a superior feature extraction measure. This study contributes to the body of knowledge with an architectural pipeline for detecting PD in resting-state EEG while emphasizing fractal dimension as an effective way of extracting salient features from EEG signals.
A fast in silico model for preoperative risk assessment of paravalvular leakage
Authors: Spanjaards Michelle , Borowski Finja , Supp Laura , Ubachs René , Lavezzo Valentina , van der Sluis Olaf
Published: February 2024

In silico simulations can be used to evaluate and optimize the safety, quality, efficacy and applicability of medical devices. Furthermore, in silico modeling is a powerful tool in therapy planning to optimally tailor treatment for each patient. For this purpose, a workflow to perform fast preoperative risk assessment of paravalvular leakage (PVL) after transcatheter aortic valve replacement (TAVR) is presented in this paper. To this end, a novel, efficient method is introduced to calculate the regurgitant volume in a simplified, but sufficiently accurate manner. A proof of concept of the method is obtained by comparison of the calculated results with results obtained from in vitro experiments. Furthermore, computational fluid dynamics (CFD) simulations are used to validate more complex stenosis scenarios. Comparing the simplified leakage model to CFD simulations reveals its potential for procedure planning and qualitative preoperative risk assessment of PVL. Finally, a 3D device deployment model and the efficient leakage model are combined to showcase the application of the presented leakage model, by studying the effect of stent size and the degree of stenosis on the regurgitant volume. The presented leakage model is also used to visualize the leakage path. To generalize the leakage model to a wide range of clinical applications, further validation on a large cohort of patients is needed to validate the accuracy of the model’s prediction under various patient-specific conditions.