bluuebunny/crossref_metadata_2025 huggingface dataset:
Application of radial basis functions in strain analysis of digital image correlation
Authors: Müller-Lohse Lutz , Tröger Jendrik-Alexander , Hartmann Stefan
Published: May 2023

Digital image correlation systems provide the motion of material points on the surface of a specimen or a component. Commonly, local interpolation concepts are chosen to determine the in‐plane strains or principal stretches. However, this approach yields discontinuous fields. In this paper, a global interpolation concept, particular, radial basis functions is considered to determine the displacement and in‐plane strain field and to overcome the underlying problem of discontinuities. Since there might be boundary effects, i.e. there are larger errors in the approximation of the strains in comparison to analytical verification examples, multiquadric are applied as particular radial basis function. It turns out that the error becomes smaller at the edges of the domain of interest, although the condition number of the resulting systems of equations in the applied interpolation scheme, might be critical. However, the studies at additively manufactured parts lead to the conclusion that the approach is promising for real‐world applications.
Modelling transient stresses in dynamically loaded elastic solids using the Lattice Boltzmann Method
Authors: Faust Erik , Steinmetz Felix , Schlüter Alexander , Müller Henning , Müller Ralf
Published: May 2023

In solids subjected to transient loading, inertial effects and S‐ or P‐wave superposition can give rise to stresses which significantly exceed those predicted by quasi‐static models. It pays to accurately predict such stresses – and the failures induced by them – in fields from mining to automotive safety and biomechanics. This, however, requires costly simulations with fine spatial and temporal resolutions.

The Lattice Boltzmann Method (LBM) can be used as an explicit numerical solver for certain appropriately formulated conservation laws [1]. It encodes information about the field variables to be simulated in distribution functions, which are modified locally and propagated across a regular lattice. As the LBM lends itself to finely discretised simulations and is easy to parallelise [2, p.55], it is an intriguing candidate as a solver for dynamic continuum problems.

Recently, Murthy et al. [3] and Escande et al. [4] adopted LBM algorithms to model isotropic, linear elastic solids. We extended these algorithms using local boundary rules that allow us to model arbitrary‐valued Dirichlet and Neumann boundaries. Here, we illustrate applications of the LBM for solids and the proposed additions by way of a simple numerical example – a glass pane subject to a sudden impact load.
Influence of Mean Stress on Lifetime Prediction of Adhesive Bonds
Authors: Köster Christian , Matzenmiller Anton
Published: May 2023

The importance of adhesive bonds in the field of joining technology is increasing due to their advantageous properties. One of these attributes is the possibility to reduce the weight compared to welded joints in group of components. For a safe design, the knowledge of the lifetime of these components is essential. Various methods are used for the prediction of the lifetime under cyclic loading. On the one hand there are test‐based methods, on the other hand simulation‐based approaches. Test‐based ones are often time‐consuming and cost‐intensive. In addition, a change in boundary conditions requires new tests. Using a simulation‐based method, it is possible to analyse new boundary conditions rapidly. The following contribution shows a damage model approach that is able to predict the lifetime of an adhesive bond with high accuracy, by taking into account the main influencing factors. First, various lifetime influencing factors are presented. Afterwards, the model approach is extended in regard to the consideration of the important mean stress influence. Finally, the model approach is validated by the comparison of the model‐based lifetime prediction to the one from test data under multiaxial loading.
Continuum Mechanical Modeling of the Inelastic Response of Woven Textile Membranes
Authors: Makhool Lubna , Balzani Daniel
Published: May 2023

This work discusses the derivation and numerical implementation of an elastoplastic model of textile membranes at finite strains. The mechanical model accounts for the anisotropic hyperelastic response [1], reached in the saturation region. The plastic anisotropy is modeled by implementing the yield surface and the flow rule as a function of the structural tensor [2]. Furthermore, the capability of the model to simulate the behavior of textile membranes under non‐proportional cyclic loading is investigated. For this purpose, a fitting procedure to identify the elastic and plastic parameters is presented.
Adaptive mesh refinement using Octree for finite cell simulation and its application for tunneling in saturated soils
Authors: Zendaki Yaman , Meschke Günther
Published: May 2023

During simulations of complex engineering processes that include the domain evolution in time and space, it is often impossible to predict which regions should have finer numerical discretization in advance. In such cases, adaptive mesh refinement (AMR) can be used to achieve higher accuracy of the solution for as little computational cost as possible. This is achieved by locally refining the mesh only in areas of interest, which leads to a considerable saving in computational and storage requirements in comparison to global refinement [1]. Further, AMR reduces the effort needed by the user to tailor a high‐quality mesh for the specific problem at hand.

Tree‐based refinement methods use a recursive encoding scheme and a hierarchical refinement of non‐overlapping elements, making them efficient and simple. These methods also ensure that the quality of the elements will not degrade and provide fine scale adaptivity [2]. Moreover, these methods are highly scalable with low overhead (see, e.g., [3]). The P4est library manages the AMR topology and uses tree‐based refinement to create a forest of octrees. It is also designed to work in parallel and scale well to a high number of processor cores. Hanging nodes resulting from bisection refinement are handled using constraints with the master‐slave elimination method. Data storage and data transfer between meshes are also handled.

The effectiveness of the proposed framework is demonstrated by large scale simulations of the tunneling process in two‐phase soft soils [4]. A structured grid is used together with AMR to create meshes for arbitrary tunnel alignments which substantially reduces preprocessing time. The soil domain is modeled using the Finite Cell method (FCM) with a non‐boundary conforming mesh while the other tunneling components are modeled using a boundary fitted mesh.
Numerical Investigation of the Corrosion and Fatigue Behavior of Clinched Joints
Authors: Harzheim Sven , Hofmann Martin , Wallmersperger Thomas
Published: May 2023

The application area of clinched joints is steadily increasing. They are vastly used in the automotive industry to join car body parts. Clinched components are often exposed to different environmental conditions as well as cyclic mechanical loading. Those environments are common originators of multiple corrosion and material fatigue phenomena. It is thus important to include possible environmental factors into the design of the joining process, to ensure full functionality of the clinched joint during its service life. In order to estimate material failure in such joints, several experimental and numerical tools are available. However, the literature provides little knowledge about the combined influence of corrosion and high‐cycle fatigue on the service life of clinched joints. In this work, a modeling framework is given that combines the effects of corrosion products formation on the fatigue life of clinched EN AW‐6014/HCT590X+Z joints by means of numerical simulations.
Convergence study for composite gas flow in pipes
Authors: Nayak Ashwin S. , Grundel Sara
Published: May 2023

Utilizing hydrogen in energy sources plays a crucial step towards a complete transition to renewable energies since production at‐scale is possible. The study works towards developing monitoring and control strategies of proportionally induced hydrogen in existing pipeline infrastructure. With this aim, a scalable model is utilized to compute the flow of composite gas along a pipe. The transient model is solved using finite element discretization and error convergence is studied for a test case. Coupling of species transport to track mixture composition along the pipe is also studied for a test case and error behaviors are investigated. Finally, simulations performed for a practical testcase are compared with a recently available open‐source tool for studying flow dynamics. The study highlights the deployment and usage of state‐of‐the‐art simulation tools against existing industrial necessities while providing invaluable insights into dynamics of gas mixtures.
Reduced order fluid modeling with generative adversarial networks
Authors: Kemna Mirko , Heinlein Alexander , Vuik Cornelis
Published: May 2023

Surrogate models based on convolutional neural networks (CNNs) for computational fluid dynamics (CFD) simulations are investigated. In particular, the flow field inside two‐dimensional channels with a sudden expansion and an obstacle is predicted using an image representation of the geometry as the input. Generative adversarial neural networks (GANs) have been shown to excel at such image‐to‐image translation tasks. This motivates the focus of this work on investigating the specific effect of adversarial training on model performance. Numerical results show that the overall accuracy of the GANs is generally lower compared to an identical generator model trained directly on the ground truth using an L1 data loss. On the other hand, GAN predictions are often visually more convincing and exhibit a lower continuity residual.
Application of a microplane damage model for concrete to an isogeometric scaled boundary formulation for 3D solids
Authors: Kikis Georgia , Mester Leonie , Chudoba Rostislav , Klinkel Sven
Published: May 2023

Microplane models have the advantage of describing damage‐induced anisotropy, which is common in quasi‐brittle materials such as concrete, in a simple and straightforward way. Over the past decades, various microplane models have been formulated to describe different loading cases and phenomena in concrete structures. They include pure damage and pure plasticity based microplane models or a combination of these two approaches. In this work, as a first step, a microplane damage model, which is derived from the principle of energy equivalence, is applied in the framework of an isogeometric 3D solid in boundary representation. Isogeometric analysis has the advantage that it can represent exactly complex geometries, which can influence the correct description of damage evolution. In addition, the use of a boundary representation in combination with NURBS and B‐splines is in accordance with the modeling technique common in CAD and allows for a straightforward application of the design model to the analysis process. The boundary is described using bi‐variate NURBS while the interior of the solid is approximated using uni‐variate B‐splines. The combination of isogeometric analysis with a model that can capture the finely distributed cracking of the concrete matrix represents a modeling strategy that can effectively support the development of thin‐walled shell structures made of textile‐reinforced concrete. Several examples are studied in order to investigate the ability of the microplane damage model to correctly describe quasi‐brittle fracture in this kind of non‐standard discretization formulation. Furthermore, a comparison to the standard finite element method is conducted.
Internal prestressing of ultra‐high performance concrete using shape memory fibers
Authors: Descher Stefan , Krooß Philipp , Kuhl Detlef , Wetzel Alexander , Wolf Sebastian
Published: May 2023

Using shape memory fibers to reinforce concrete is a novel concept in civil engineering. Pre‐stretched fibers are brought into concrete and after activating the shape memory effect, a compressive prestress state is introduced. The present work investigates this method numerically. A brief introduction to the relevant behavior of shape memory alloys is given. Fiber activation is modeled by an empirical phase transition model. Simulations are carried out by applying the Finite Element Method to solve the CAUCHY‐FOURIER equations. Results of studies are presented for single‐fiber, improved single‐fiber and multi‐fiber configurations. Special focus is put on the geometric type of strain release. Key findings are that compressive stresses can be introduced into the concrete, however, local tension will occur. By altering the fiber geometry and applying an elastomeric coating, these regions can be eliminated. Furthermore, when using multiple fibers, there are synergies between regions of compression.
A model order reduction technique for the linearised compressible flow equations
Authors: Toth Florian , Luo Likun
Published: May 2023

Viscous effects in acoustics are significant if the thickness of the oscillating viscous boundary layer (Stokes boundary layer) becomes comparable to characteristic problem dimensions. For air as an acoustic medium, this is frequently the case in small‐scale devices like micro‐electro‐mechanical systems or micro‐perforated panels for sound absorption. Accurate modelling of viscous effects can be done by the solution of the linearised compressible flow equations by the finite element method, which is computationally demanding due to the high number of unknowns arising in the problem: pressure, velocity and temperature. Furthermore, the discretisation must resolve the thin viscous boundary layers, creating a model with a high number of degrees of freedom. We suggest a projection‐based model order reduction procedure using the system eigenmodes as generalised coordinates. The procedure is tested based on a simple example problem in 2D. Here we show that the derived reduced order model is accurate and computationally highly efficient. The number of degrees of freedom can be reduced by several orders of magnitude, from around 30 000 to 100, thereby dramatically reducing the computation time for harmonic solutions.
Towards the evaluation of heat and mass transfer in pipe flows with cocurrent falling films using One‐Dimensional Turbulence
Authors: Medina Méndez Juan A. , Schmidt Heiko
Published: May 2023

Turbulent mixed convection in an air‐water system is evaluated with a novel numerical solver implementing the stochastic One‐Dimensional Turbulence (ODT) model in a turbulent air flow surrounded by a laminar cocurrent water falling film in a cylindrical geometry. The ODT model is used as a reduced order surrogate model for the effects of turbulent advection, turbulent heat flux, and turbulent mass‐flux within a one‐dimensional domain. An ad‐hoc temporal‐to‐spatial transformation relying on the bulk flow gas velocity is used to obtain streamwise‐dependent statistics of the flow. The ODT simulation results are compared to simulations obtained with the assumption of a quasi‐laminar one‐dimensional gas flow, and to Reynolds‐Averaged Navier‐Stokes (RANS) reference data for a cocurrent water falling film evaporator [1]. The results show that the turbulent transport plays a decisive role in the estimation of interface gradients of temperature and vapor mass fraction. Although ODT predicts global quantities such as the interface temperature in a reasonable way, the model falls short of successfully predicting streamwise‐dependent radial profiles. Despite the shortcomings, the framework presented here is the first stepping stone towards the evaluation of complex multiphase momentum, mass, and heat transfer couplings with full scale resolution on potential evaporative devices. The model, thus, provides valuable information with minimal empiricism on the dynamics of the small scales for pioneering engineering applications.
Application of back propagation neural networks and random forest algorithms in material research of hydrogels
Authors: Wang Yawen , Wallmersperger Thomas , Ehrenhofer Adrian
Published: May 2023

In the fourth paradigm of science, which is data‐driven discovery, the big data collected from the first three paradigms can be analyzed to gain information of the research object. Especially in the field of material science, various big data‐driven methods are applied in the tasks, such as material detection, material analysis and material design. In the current research, we focus on how data‐driven methods, e.g., machine learning algorithms, play a big role in deciphering processing‐properties‐performance (PPP) relationships in hydrogels. We present the procedure of (i) normalization of hydrogel properties, (ii) feature engineering of hydrogels, which is to summarize the decisive features in each PPP section of hydrogels, and (iii) database building by data extraction from scientific literature of hydrogels. Finally, we select the two most promising machine learning algorithms, back propagation neural network and random forest algorithm. The back propagation neural network can contribute to prediction of hydrogels properties and the random forest algorithm can be applied to obtain deeper understanding of hydrogels in the early stage of the research.
Computational model for the semi‐analytical assessment of the free‐edge effect in composite laminated shells
Authors: Kappel Andreas , Mittelstedt Christian
Published: May 2023

The development of efficient computational models for the accurate prediction of the state variables in general composite laminated shells undergoing uniform edge loadings is a major challenge, especially when stress concentration phenomena such as the free‐edge effect have to be considered. This paper addresses this issue by introducing a higher‐order semi‐analytical approach for the assessment of the three‐dimensional stress field in circular cylindrical composite shells with arbitrary layups subjected to a uniform bending moment. The presented semi‐analytical approach combines a closed‐form analytical plane‐strain solution with a higher‐order layerwise approach, and the governing equations are derived by virtue of the principle of minimum elastic potential. The resulting system of coupled ordinary differential equations is then solved by means of the state‐space approach and the free constants are determined by evaluating the boundary conditions at the traction‐free edges. A comparison of the numerical results of the presented semi‐analytical method with finite element simulations for various composite laminates indicates that the developed method works with high accuracy, although being extremely efficient in terms of computational resources.
Model order reduction via substructuring for a nonlinear, differential‐algebraic machine tool model with moving loads
Authors: Aumann Quirin , Benner Peter , Saak Jens , Vettermann Julia
Published: May 2023

Machine tools are permanently exposed to complex static, dynamic and thermic loads. This often results in an undesired displacement of the tool center point (TCP), causing errors in the production process and thus limiting the achievable workpiece quality. Recent research efforts try to counter these effects by process‐parallel solutions utilizing machine internal data. Therefore, fast simulation models are a fundamental requirement. Here, model order reduction (MOR) becomes crucial. The resulting low‐dimensional models are required for various applications, e.g., in digital twins, the correction of thermally induced errors at the TCP during the production process as well as for lifetime calculations in predictive maintenance. In this contribution, we present a strategy of MOR for a coupled thermo‐mechanical model with a nonlinear subsystem and moving loads, using the example of a feed axis with nonlinear machine components. Applying tailored substructuring techniques, we are able to separate the linear and nonlinear system components. This allows to apply classic linear MOR methods to the much larger linear part, whereas the small nonlinear part is kept, and thus enables drastically reduced computing times. The relative movement is considered by a switched system approach. Transient thermo‐mechanical interactions of the feed axis are calculated in a final investigation, comparing the performance of the resulting reduced‐order model and the original one.
Relaxed Incremental Formulations for Damage at Finite Strains Including Strain Softening
Authors: Köhler Maximilian , Neumeier Timo , Peterseim Daniel , Peter Malte A. , Balzani Daniel
Published: May 2023

Relaxation is a promosing technique to overcome mesh‐dependency in computational damage mechanics originating from the non‐convexity of an underlying incremental variational formulation. This technique does not require an internal length scale parameter. However, in case of damage formulations, for many years the decrease of stresses with an increase of strains, referred to as strain‐softening, could not be modeled in the relaxed regime. This contribution discusses several possibilities of relaxation that lead to suitable models for stress‐ and strain‐softening.
Stiffness pairing in soft‐hard active‐passive actuators
Authors: Ehrenhofer Adrian
Published: May 2023

Soft‐Hard Active‐Passive Embedded Structures (SHAPES) are composites that respond to the environments in which they are embedded. This reaction can be a mechanical actuation, but also an intrinsic computation that yields an adaptation as a result. The actuation capabilities primarily depend on the stiffness combination of the involved materials. Stiffness includes both material parameters (depending on the chosen material model, e.g., the Young's modulus) and geometry parameters (depending on the type of structure, e.g., the beam height). The active properties can be included using the Stimulus Expansion Model, which is based on the analogy of the active reponse to thermal expansion. SHAPES can be designed according to three different behaviors, Case Iconstrained, Case IIcombinedand Case IIIfree. In the current work, these cases, the modelling and design background, and various examples are presented.
Mechanical performance of carbon fiber‐reinforced polymer cellular structures manufactured via fused filament fabrication
Authors: Kepenekci Mehmet , Gharehpapagh Bahar , Yaman Ulas , Özerinç Sezer
Published: May 2023

This article investigates the mechanical behavior of polyamide and carbon fiber‐reinforced (CFR) polyamide structures produced by Fused Filament Fabrication. CFR improves solid polyamide's tensile strength and modulus by more than 200% and 800%, respectively. The enhancement is highest in the parallel raster due to the alignment of the fibers in the printing direction. The compression tests of gyroid, honeycomb, and Voronoi cellular structures revealed the effect of geometry and fiber reinforcement on energy absorption performance. CFR gyroid infill offers the best performance with a specific energy absorption capacity reaching 10 kJ/kg and an efficiency close to 50%. Fiber reinforcement improves energy absorption by a factor of four or higher while increasing the weight by only 10%. The energy absorption capacity of the reinforced polyamide offers enormous potential for developing new lightweight load‐bearing and impact‐absorbing structures.
Progress, challenges, and perspectives on polymer substrates for emerging flexible solar cells: A holistic panoramic review
Authors: Subudhi Poonam , Punetha Deepak
Published: May 2023

In pursuit of a renewable, inexpensive, sustainable, and compact energy source to replace fossil fuels, solar photovoltaic devices have become an ideal alternative to meet human needs for environmentally friendly, affordable, and portable power sources. It is due to their excellent mechanical robustness and outstanding energy conversion efficiency. Concerning the increasing demand for flexible and wearable electronic devices with standalone power sources, much attention has been paid to photovoltaics' flexibility and lightweight developments. Along with high mechanical flexibility and lightweight, flexible photovoltaic devices have the advantages of conformability, bendability, wearability, moldability, and roll‐to‐roll processing into complex shapes that can produce niche products. Emerging solar cells, among other photovoltaic technologies, have been exalted for their high conversion efficiency, low cost, and ease of production, making them a viable new‐generation photovoltaic technology. The main commercialization choice for cutting‐edge solar cells is flexible dye‐sensitized and perovskite solar cells since they can be made using a roll‐to‐roll printing technique and are appropriate for mass manufacturing. More significantly, flexible evolving solar cells may be created on ultrathin and light substrates to fulfill the demands of the developing flexible electronics industry and discover uses that are not possible with traditional photovoltaic technology. In any flexible device, the substrate is a backbone on which further materials rely. A flexible substrate reduces the installation and transportation charges, thereby reducing the system price and increasing power conversion efficiency. In this review, we comprehensively assess relevant materials suitable for making flexible photovoltaic devices. Several flexible substrate materials, including ultra‐thin glass, metal foils, and various types of polymer materials, have been considered. For conducting materials, transparent conducting oxides, metal nanowires/grids, carbon nanomaterials, and conducting polymers have also been comprehended. Progress on various flexible foils, fabrication and stability issues, current challenges, and solutions to those challenges of using conductive polymer substrate is endorsed and reviewed in detail. The originality of this holistic study lies in its ability to offer a thorough overview of recent advancements in flexible dye‐sensitized and perovskite solar cells on polymer substrates, which is conceivable and worthy as a roadmap for future research work.
C‐Alkylated flavonoids from the whole plants of Desmodium caudatum and their anti‐TMV activity
Authors: Li Yin‐Ke , Xiong Rui‐Feng , Wu Qing‐Yang , Yao Sui , Qu Xing , Huang Zhi‐Hua , Su Yu‐Long , Wu Yu‐Ping , Dong Miao , Zhou Min , Hu Qiu‐Fen
Published: May 2023

Background

Natural products are important sources of biopesticides to control plant virus, and flavonoids are identified as promising anti‐tobacco mosaic virus (TMV) agents. Since Desmodium caudatum is a rich source of flavonoids, this study focuses on the discovery of the new anti‐TMV active flavonoids from D. caudatum and their possible mode of action.

Results

Three new (compounds 1–3) and nine known (compounds 4–12) C‐alkylated flavonoids were isolated from D. caudatum. To the best of our knowledge, the framework of 1–3 was reported in natural products for the first time. In addition, 1–3, 5, and 6 showed notable anti‐TMV activity with inhibition rates in the range of 35.8–64.3% at a concentration of 50 μg/mL, and these rates are higher than that of positive control (with inhibition rates of 34.6% ± 2.8). In addition, the structure–activity relationship study revealed that the (pyrrol‐2‐yl)methyl moiety on flavone can significantly increases the activity. This result is helpful to find new anti‐TMV inhibitors.

Conclusion

C‐Alkylated flavonoids showed potent activities against TMV with multiple modes of actions. The increase of defense‐related enzyme activities, up‐regulate the expression of defense related genes, down‐regulate the expression of Hsp70 protein by inhibiting the related Hsp genes that are involved in tobacco resistance to TMV. By the actions mentioned earlier, the infection of TMV was influenced, thereby achieving the effects of control of TMV. The successful isolation of the earlier‐mentioned flavonoids provide the new source of biopesticides to TMV proliferation, and also contribute to the utilization of D. caudatum. © 2023 Society of Chemical Industry.
A quantitative assessment of key drivers for environmental economic practices adoption for sustainable development
Authors: Oke Ayodeji Emmanuel , Aliu John , Odia Onoriode Austin , Aigbavboa Clinton O. , Jamir Singh Paramjit Singh , Awuzie Bankole O. , Samsurijan Mohamad Shaharudin
Published: May 2023

The purpose of this paper is to present the results of an assessment aimed at evaluating potential drivers for the adoption of environmental economic practices in the construction industry, with a view to enhancing sustainability of construction projects, using the Nigerian construction industry as a case study. This study utilized a post‐positivist philosophical approach and a quantitative research design to collect data from construction professionals in the Nigerian construction industry through a well‐structured questionnaire. The collected data was analyzed using various statistical tests, including the Kruskal–Wallis H test, Kendall's coefficient of concordance (W), Chi‐square (χ2), and exploratory factor analysis. Five major clusters of drivers for the adoption of environmental economic practices were derived in this study. These are (1) operational drivers, (2) stakeholder drivers, (3) market and financial drivers, (4) regulatory and policy drivers, and (5) technological drivers. The findings of this study offer valuable insights into the potential drivers for the adoption of environmental economic practices in the construction industry, particularly from the perspective of a developing country such as Nigeria. Overall, this study contributes to the promotion of environmental sustainability in the construction industry, particularly in developing countries, which can have significant implications for global sustainability efforts.
A Decade of Melt Electrowriting
Authors: O'Neill Kelly L. , Dalton Paul D.
Published: May 2023

Over the past decade, melt electrowriting (MEW) has established the fundamental understanding of processing (and printer) requirements. Iterative work on parametric development and dissemination of this recent additive manufacturing technology has been performed across many systems and polymers (mainly poly‐(ε‐caprolactone)), showing similarities and trends. However, the software and hardware ecosystems of MEW are not mature. Further, due to its multi‐parametric nature, MEW can be challenging for laboratories to master. This review intends to provide a unique perspective on the dynamic relationship between MEW processing parameters. Such parameters can be divided into 1) those that affect the polymer flow rate to or 2) from the nozzle, and 3) environmental conditions. The most influential parameters for high‐quality printing are applied voltage, applied pressure, collector speed, polymer temperature, nozzle diameter, and the conditions that lead to charge buildup (e.g., relative humidity). Other factors such as ambient temperature, nozzle size, and protrusion, collector temperature and conductivity, and collector distance can all affect the process. Success for MEW printing means fibers fall onto the collector according to their pre‐programmed path with predicted fiber diameter. Here, the authors elucidate how the dynamic relationship between these parameters can converge into ideal printing conditions to produce scaffolds.
Advances on the Application of Wide Band‐Gap Insulating Materials in Perovskite Solar Cells
Authors: Guo Yi , Huang Like , Wang Chaofeng , Liu Shuang , Huang Jiajia , Liu Xiaohui , Zhang Jing , Hu Ziyang , Zhu Yuejin
Published: May 2023

In recent years, the development of perovskite solar cells (PSCs) is advancing rapidly with their recorded photoelectric conversion efficiency reaching 25.8%. However, for the commercialization of PSCs, it is also necessary to solve their stability issue. In order to improve the device performance, various additives and interface modification strategies have been proposed. While, in many cases, they can guarantee a significant increase in efficiency, but not ensure improved stability. Therefore, materials that improve the device efficiency and stability simultaneously are urgently needed. Some wide band‐gap insulating materials with stable physical and chemical properties are promising alternative materials. In this review, the application of wide band‐gap insulating materials in PSCs, including their preparation methods, working roles, and mechanisms are described, which will promote the commercial application of PSCs.
Insulin therapy in a dog diagnosed with a metastatic insulin‐secreting neuroendocrine tumour
Authors: Kane Briannan‐Kym , Thompson Ann
Published: May 2023

A 10‐year‐old, male, neutered Jack Russell terrier cross presented for a 24‐hour history of ataxia and collapse, progressing to generalised seizures in hospital at which a severe hypoglycaemia (2.9 mmol/L; 3.5–6.7) and hyperinsulinaemia (122 mU/L; 5–40 mU/L) were documented. Fine‐needle aspirates taken from multiple hepatic masses confirmed the diagnosis of a neuroendocrine neoplasm and probable metastatic insulinoma. Initial medical treatment consisted of intravenous dextrose 5%, glucagon continuous‐rate infusion, prednisolone, diazoxide, S‐adenosylmethionine and silybin, and toceranib phosphate. Hyperglycaemia (16.9 mmol/L; 3.5–6.7 mmol/L) was documented 157 days after commencing therapy with consistent clinical signs of diabetes mellitus. All medical treatments for insulinoma were discontinued; however, the dog's hyperglycaemia persisted. Therefore, caninsulin therapy commenced at a starting dose of 0.25 IU/kg, and was gradually increased to 0.6 IU/kg in the morning and 0.5 IU/kg in the evening. The dog was treated with insulin for 140 days, before relapsing hypoglycaemia and hyperinsulinaemia, with subsequent euthanasia 320 days after the initial diagnosis.
The Hitchhiker’s Guide to the Social Media Data Research Galaxy - A Primer
Authors: Rossi Arianna
Published: May 2023

This short paper is a primer for early career researchers that collect and analyze social media data. It provides concise, practical instructions on how to address personal data protection concerns and implement research ethics principles.
Zivile Konfliktbearbeitung und Ziviler Friedensdienst
Authors: Ruppel Samantha
Published: May 2023

In diesem Kapitel erfolgt zunächst eine allgemeine Einführung und Begriffsklärung zur Friedenskonsolidierung und für Zivile Konfliktbearbeitung im Speziellen. Daran anschließend wird die besondere Rolle von zivilgesellschaftlichen Organisationen in der Friedensarbeit betrachtet. Dies ist eine erste Darstellung, welche dazu dient, den ZFD, der von zivilgesellschaftlichen Organisationen durchgeführt wird, besser verorten zu können. Darauf folgt eine Vorstellung des ZFD im Detail. Diese ausführliche Darstellung ist hilfreich, um den empirischen Teil, welcher Fallstudien des ZFD beinhaltet, besser einordnen und verstehen zu können. Generell findet in allen Kapiteln auch eine machtkritische Betrachtung von ZKB, der Arbeit von zivilgesellschaftlichen Organisationen und des ZFD statt.
Analytical Solution to Unsaturated Infiltration
Authors: Wu Lizhou , Zhou Jianting
Published: May 2023

Rainfall infiltration in unsaturated soil slopes is a classic issue in geotechnical engineering (Conte and Troncone in Géotechnique 62:87–91, 2012; Morbidelli et al. in J Hydrol 557:878–886, 2018). Factors influencing the soil slope stability due to rainwater infiltration comprise the rainfall characteristics, the saturated permeability coefficient, the geometry of the slope, and the boundary and initial soil moisture conditions (Ali et al. in Comput Geotech 61:341–354, 2014; Wu et al. in Hydro-mechanical analysis of rainfall-induced landslides. Springer, 2020).
Improved Linear and Nonlinear Iterative Methods for Rainfall Infiltration Simulation
Authors: Wu Lizhou , Zhou Jianting
Published: May 2023

The linear infiltration equations obtained by discretizing Richards’ equation need to be solved iteratively, including two approaches of linear and nonlinear iterations. The first method is to use numerical methods to directly numerically discretize Richards’ equations to obtain nonlinear ordinary differential equations and then use nonlinear iterative methods to iteratively solve, such as Newton’s method (Radu et al. in On the convergence of the Newton method for the mixed finite element discretization of a class of degenerate parabolic equation. Numerical mathematics and advanced applications. Springer, pp 1194–1200, 2006), Picard method (Lehmann and Ackerer 1998), and the L-method (List and Radu 2016). The Picard method can be considered as a simplified Newton method, which linearly converges.
Pervasive Augmented Reality to support logistics operators in industrial scenarios: a shop floor user study on kit assembly
Authors: Maio Rafael , Santos André , Marques Bernardo , Ferreira Carlos , Almeida Duarte , Ramalho Pedro , Batista Joel , Dias Paulo , Santos Beatriz Sousa
Published: May 2023

Augmented Reality (AR) is a pillar of the transition to Industry 4.0 and smart manufacturing. It can facilitate training, maintenance, assembly, quality control, remote collaboration and other tasks. AR has the potential to revolutionize the way information is accessed, used and exchanged, extending user’s perception and improving their performance. This work proposes a Pervasive AR tool, created with partners from the industry sector, to support the training of logistics operators on industrial shop floors. A Human-Centered Design (HCD) methodology was used to identify operators difficulties, challenges, and define requirements. After initial meetings with stakeholders, two distinct methods were considered to configure and visualize AR content on the shop floor: Head-Mounted Display (HMD) and Handheld Device (HHD). A first (preliminary) user study with 26 participants was conducted to collect qualitative data regarding the use of AR in logistics, from individuals with different levels of expertise. The feedback obtained was used to improve the proposed AR application. A second user study was realized, in which 10 participants used different conditions to fulfill distinct logistics tasks: C1 — paper; C2 — HMD; C3 — HHD. Results emphasize the potential of Pervasive AR in the operators’ workspace, in particular for training of operators not familiar with the tasks. Condition C2 was preferred by all participants and considered more useful and efficient in supporting the operators activities on the shop floor.
On the Global Convergence of Particle Swarm Optimization Methods
Authors: Huang Hui , Qiu Jinniao , Riedl Konstantin
Published: May 2023

In this paper we provide a rigorous convergence analysis for the renowned particle swarm optimization method by using tools from stochastic calculus and the analysis of partial differential equations. Based on a continuous-time formulation of the particle dynamics as a system of stochastic differential equations, we establish convergence to a global minimizer of a possibly nonconvex and nonsmooth objective function in two steps. First, we prove consensus formation of an associated mean-field dynamics by analyzing the time-evolution of the variance of the particle distribution, which acts as Lyapunov function of the dynamics. We then show that this consensus is close to a global minimizer by employing the asymptotic Laplace principle and a tractability condition on the energy landscape of the objective function. These results allow for the usage of memory mechanisms, and hold for a rich class of objectives provided certain conditions of well-preparation of the hyperparameters and the initial datum. In a second step, at least for the case without memory effects, we provide a quantitative result about the mean-field approximation of particle swarm optimization, which specifies the convergence of the interacting particle system to the associated mean-field limit. Combining these two results allows for global convergence guarantees of the numerical particle swarm optimization method with provable polynomial complexity. To demonstrate the applicability of the method we propose an efficient and parallelizable implementation, which is tested in particular on a competitive and well-understood high-dimensional benchmark problem in machine learning.
Phenotypic and Genotypic Characterization of Antimicrobial Resistance in Streptococci Isolated from Human and Animal Clinical Specimens
Authors: Glajzner Paulina , Szewczyk Eligia M. , Szemraj Magdalena
Published: May 2023

Recently, the phenomenon of infection of humans as hosts by animal pathogens has been increasing. Streptococcus is an example of a genus in which bacteria overcome the species barrier. Therefore, monitoring infections caused by new species of human pathogens is critical to their spread. Seventy-five isolates belonging to streptococcal species that have recently been reported as a cause of human infections with varying frequency, were tested. The aim of the study was to determine the drug resistance profiles of the tested strains, the occurrence of resistance genes and genes encoding the most important streptococcal virulence factors. All tested isolates retained sensitivity to β-lactam antibiotics. Resistance to tetracyclines occurred in 56% of the tested strains. We have detected the MLSB type resistance (cross-resistance to macrolide, lincosamide, and streptogramin B) in 20% of the tested strains. 99% of the strains had tetracycline resistance genes. The erm class genes encoding MLSB resistance were present in 47% of strains. Among the strains with MLSB resistance, 92% had the streptokinase gene, 58% the streptolysin O gene and 33% the streptolysin S gene. The most extensive resistance concerned isolates that accumulated the most traits and genes, both resistance genes and virulence genes, increasing their pathogenic potential. Among the tested strains, the gene encoding streptokinase was the most common. The results of the prove that bacteria of the species S. uberis, S. dysgalactiae and S. gallolyticus are characterized by a high pathogenic potential and can pose a significant threat in case of infection of the human body.
Optimization of hydrophobic nonresponsive sol-ketal acrylate gel film to hydrophilic thermo-responsive gel by graft-polymerization
Authors: Abdelaty Momen S. A. , Abu-Zahra Nidal
Published: May 2023

This work has been done in three steps. First, the preparation of acrylate monomers; they are [dimethyl-1,3-dioxoylan-4-yl-methylacrylate (sol-ketal acrylate) (SKA)], [4-acetylphenyl acrylate (APHA)], and [4-formyl-2-methoxyphenylacrylate (VA)]. All monomers were evaluated using 1H, 13C-NMR, and FT-IR. In the next step, two kinds of polymers were prepared. Two series of copolymers and terpolymers were carried out via the free-radical polymerization; SKA with the photo-cross-linker for poly (SKA-co-DMIAm) photo-cross-linker polymer and VA and APHA with N-isopropylacrylamide for poly (NIPA-co-VA-co-APHA) functional-thermo-responsive terpolymer. All fabricated polymers were investigated by (1H-NMR, FT-IR, UV, GPC, and DSC). The phase separation temperature of polymer solutions has been measured through the turbidity and the change in transmittance to the temperatures using UV–Vis spectroscopy. Eventually, the UV was used to form the gel layer after the deposition of the gold layer. The nonresponsive gel layer was grafted with poly (NIPA-co-VA-co-APHA) to optimize the upper layer to the thermo-responsive functional layer. SPR/OW measured the swelling properties of the gel layers. The active layer will immobilize biological molecules with the primary amine group.

Graphical abstract

The schematic diagram shows the steps of gel formation: The cross-linking initiated by UV; SPR/OW for film thickness; grafting for gel optimization.
Persistent Postural-Perceptual Dizziness (PPPD) and quality of life: a cross-sectional study
Authors: Steensnaes Malin Herwander , Knapstad Mari Kalland , Goplen Frederik Kragerud , Berge Jan Erik
Published: May 2023

Purpose

To determine if Persistent Postural-Perceptual Dizziness (PPPD) is associated with increased burden of dizziness and quality of life. Secondly, if this association is present, to determine if it can be explained by differences in anxiety and/or depression between patients with PPPD and dizzy patients without PPPD.

Methods

Cross-sectional study performed in an outpatient otolaryngology clinic, including patients 18–67 years referred from primary care for suspected vestibular disease with chronic dizziness. Patients underwent clinical examination and completed the following questionnaires: Dizziness Handicap Inventory (DHI), RAND-12 Health Status Inventory and Hospital Anxiety and Depression Scale (HADS). Scores in DHI and RAND-12 were compared between patients diagnosed with PPPD and patients without PPPD.

Results

202 patients were included. 150 (74%) were women and 37 (18%) were diagnosed with PPPD. Patients in the PPPD group had increased burden of dizziness and reduced quality of life (QoL) as shown by a higher mean DHI score (49.2 vs. 30.8; p < 0.001) and reduced mean RAND-12 physical score (39.0 vs. 44.6; p = 0.004). After adjusting for age, gender and HADS, PPPD was associated with a 15.3 (p < 0.001) points increase in DHI score, and a 4.0 (p = 0.020) points decrease in RAND-12 physical score.

Conclusion

Patients with PPPD have a higher burden of dizziness and a lower physical health-related quality of life (HRQoL) compared to other dizzy patients. The difference was evident also after adjusting for anxiety and depression, illustrating how PPPD is a different entity than these common psychiatric conditions.
A small RNA, microRNA as a potential biomolecular marker to estimate post mortem interval in forensic science: a systematic review
Authors: Pasaribu Roben Suhadi , Auerkari Elza Ibrahim , Suhartono Antonius Winoto , Auerkari Pertti
Published: May 2023

Background

Post-mortem interval (PMI) is the cornerstone of the forensic field to investigate. The examination technique by seeing the changes in the body such as algor mortis, rigor mortis, and livor mortis is a traditional technique in which accuracy is influenced by many factors. A biomolecular technique that uses microRNA (miRNA) biomarkers is developing because miRNA has good stability than other RNA, so it meets the requirements to be used for PMI estimation.

Method

Following the PRISMA guidelines, journals were taken from 5 databases: Scopus, Science Direct, PubMed, Embase, and Springer. The review was carried out by two people. Inclusion criteria in this review are original research, published in the last 10 years, discussing miRNA as a biomarker for PMI estimation, and free full access. While exclusion criteria are not original research and not using English.

Result

Eighteen journals were reviewed in this study. The study was conducted using test animals (rats) and human samples with tissue sources taken from the liver, skeletal muscle, blood, bone, heart, skin, saliva, semen, brain, lung, vitreous humor, spleen, and kidney. miRNA expression levels after death showed different results based on miRNA target, tissue source, and others.

Discussion

The results of each study are different due to the use of different types of miRNA targets and tissue sources. miRNA has great potential to estimate PMI in forensic science, but it is necessary to control the influencing factors to obtain an accurate conclusion.