bluuebunny/crossref_metadata_2025 huggingface dataset:
Combination of the Scanning and the Polar Measuring Method for the Defect Detection in Dry Fibre Layups Using an Eddy Current Sensor
Authors: Mimra Christopher , Eisenbart Boris , Carosella Stefan , Middendorf Peter
Published: June 2023

Gaps, fibre misalignment and foreign objects in dry fibre tape layups are detrimental towards the final mechanical properties of carbon fibre composite parts. Eddy current sensors can be used to inspect layups for the named defects. In comparison to optical inspection methods, eddy current measurements are capable of inspecting not only the top layer but multiple plies at once. In the literature, two different methods have been proposed for this inspection. One is the scanning method, where the sensor is moved over the specimen and creates a grey-scale image. The pixel brightness correlates with the layup’s local electrical conductivity. The other method for the local inspection is the polar method, where the sensor is rotated on a single spot to detect the fibre orientation. In this work, both methods were conducted with the same inspection system, which is based on a collaborative robotic arm. It has been shown that the scanning method can identify gaps and foreign objects out of metal. The fibre orientation can be identified by the rotational method with a precision of 0.16$$^{\circ }$$

∘

. The exact positioning of the probe remains the main challenge for this inspection system. However, a combination of both methods promises to provide a reliable inspection method for the most common defect in a dry fibre layup.
Detection of Gaps and Overlaps in Laser Line Triangulation Data of Dry Fibre Tape Layups Using Image Projection
Authors: Mimra Christopher , Krein Vincent , Radjef Racim , Fox Bronwyn , Middendorf Peter
Published: June 2023

A major cost driver in the production of carbon composite parts is the quality inspection, which to this day relies on manual investigation by a trained worker. Gaps and overlaps in the layups are to be detected because they are proven to be detrimental towards the mechanical properties of the final part. In recent works, laser line triangulation sensors have been applied to inspect layups of prepreg tapes and non-crimp fabric material. These sensors create a 3D point cloud of the specimens surface. This is then evaluated by conversion into a grey-scale image and a subsequent image processing algorithm. However, the most commonly used algorithms fail to differentiate between defects and small, acceptable irregularities, such as welding spots, slits and single fibres which stick out.

The aim of this research is to develop a reliable evaluation method for scans of dry fibre tape layups. An overview over the different groups of algorithms is provided, image projection is selected and compared to algorithms which have been proven to work best on pre-pregs. While the common algorithms fail to classify a test set of dry fibre specimen, image projection can reach a true positive rate of 100% and a false positive rate of 19%. The proposed setup can be a centrepiece of a future in-line quality inspection system for dry fibre layups which has potential for a significant decrease of the manufacturing costs.
Parameter Study and Optimization of Forming Simulations for Tape-Based Fiber Layups
Authors: Saeed Muhammad S. , Gugliuzza Jakob M. J. , Liebl Michael , Eisenbart Boris , Radjef Racim , Middendorf Peter , Kreimeyer Matthias
Published: June 2023

This work presents a model of a parametrized fiber-reinforced tapes layup for simulations of stamp forming. BETA CAE Systems’ ANSA v22.1.0 produced the forming model. The initial configurations of the forming process are simulated using LS-DYNA R12 from the Livermore Software Technology Corporation (LSTC) on the High-Performance Computing Center Stuttgart (HLRS). A doubledome geometry was used as a use case in the presented study. An optimal solution is found by predicting and analyzing the forming defects, both quantitatively and qualitatively. Typical defects induced by the forming process include wrinkles, bridging, waviness, misalignment of tapes, instabilities due to tape overlaps and gaps, etc. Adjustments to the forming process are made by varying model parameters such as stacking sequence, fiber angle, material properties, tape orientation, or the position of ultrasonic thermal bonds between tapes. In addition, process parameters such as tool velocity, temperature, and gripping force were considered. Different algorithms for the sample creation of the designed experiments are examined, and the influence of various parameters on the final part is discussed. The limitations and requirements of the employed software are examined for additional studies. Furthermore, the machine learning-based neural network algorithms discussed, such as particle swarm optimization (PSO), gradient-based optimization (GBO), response surface method (RSM), and genetic algorithms (GA), may be used in future research to determine an ideal tape arrangement for various geometries based on nodal locations and the parameters as mentioned above.
Analysis of New Concepts for the Consolidation Roller in Laser-Assisted Automated Tape Placement Processes
Authors: Widmaier Nils , Raps Lukas
Published: June 2023

The need for more sustainable production has led to an increased popularity of thermoplastic fibre reinforced composites over the last years. Typical production processes rely on autoclave and/or sequential processes, which lead to long cycle times, high energy consumption and high costs. One step in-situ production processes, like the thermoplastic laser assisted automated fibre placement, provide an ideal solution to these challenges while enabling the benefits of circular economy through improved recyclability. An essential part of the production process is to ensure full consolidation during layup. One of the main influences on consolidation is the applied pressure of the compaction roller. Increasingly complex part geometries with curved surfaces place special demands on the deformation and adaptability of these rollers. Here, current solutions quickly reach their limits. This paper investigates new concepts for the consolidation roller to enable successful use of in-situ placement technologies on complex part geometries. Different sheath thicknesses and materials were investigated in experiments, followed by simulative investigation of further compaction roller concepts.
Development, Implementation and Evaluation of a Prototype System for Data-Driven Optimization of a Preforming Process
Authors: Liebl Michael , Holder Jonas , Mohr Tobias , Dorneich Albert , Liebgott Florian , Middendorf Peter
Published: June 2023

Modern production of fiber reinforced composites via the preforming process is widely used in the industry. A common way to create dry, semi-finished fiber products is forming or draping a textile into a three-dimensional component geometry. The punch and die process is often used for resin transfer molding (RTM) composite manufacturing. Due to the major influence of the preforming step on the later mechanical performance of the component, a detailed knowledge of the fiber architecture is beneficial.

To enable in-situ monitoring of the specific deformation of a woven fabric, a novel kind of single-use two-dimensional strain sensors has already been developed and characterized. We show that by using industrial communication standards, data from various data sources can be consolidated in an edge computer and used to improve the process. To this end, we developed the hardware and firmware of a device that reads out the printed strain sensors and transfers the data to the edge device via IO-Link. In addition, the edge device collects data from a programmable logic controller and is capable of connecting further IO-Link sensors.

Our demonstrator is intended as a proof of concept for in-situ monitoring, data-driven analysis and improvement of the punch and die process and will be further developed. We propose a machine learning-based edge analytics approach for detecting defects and increasing the preforming quality during the draping process. Forming tests with the double-dome benchmark geometry and the carbon fabric which is suitable for industry have been carried out to validate our prototype system.
Resource Efficient Manufacturing of Complex Cooling Structures
Authors: John Leonard , Becker Dina , Reuter Steffen , Möhring Hans-Christian , Doppelbauer Martin , Berg Lars F.
Published: June 2023

The combination of additive manufacturing (LPBF) and plastic injection molding offers great benefits for functional integration and thereby the functionality of parts, components and systems. By manufacturing cooling channels as very thin-walled structures, short laser processing time is needed to produce these parts. The combination with plastic overmolding allows the mechanical loads to be absorbed, while at the same time utilizing the freedom of shape of the LPBF process. In order to prevent the structures from collapsing during overmolding or to ensure that they do not have to be very thick-walled in order to withstand the high injection pressures, the structures are closed, so that the base-powder is still contained in the structure during the overmolding. After opening the overmolded components, the powder can be extracted and reused. This technique offers great potential for high functional integration and new possibilities in terms of realizing internal cooling structures of electric traction machines. Other advantages that can be exploited are the thermally good connection due to the material bond and the possibility of local reinforcement due to the design freedom of the insert. Thanks to the injection-molded component, complex geometries can also be produced without additional unit costs.
Software-Defined Manufacturing for the Entire Life Cycle at Different Levels of Production
Authors: Behrendt Sebastian , Martin Michael , Puchta Alexander , Ströbel Robin , Fisel Johannes , May Marvin C. , Gönnheimer Philipp , Fleischer Jürgen , Lanza Gisela
Published: June 2023

Increasingly volatile markets, higher numbers of product variants and more sophisticated customer demands lead to a soaring complexity of productions themselves and their operations. An enabling technology that allows to cope with this increased complexity is digitization, as it enables data capturing and data driven analysis in production. Software-defined manufacturing (SDM) empowers to fully use the potential of digitization by decoupling physical production hardware and the associated control software. This enables an increase in the versatility of existing resources through automated generation of software for instantiations and interventions in production control. With the aim of enlarging the abstraction and decoupling capabilities of SDM, this paper presents a concept to use SDM at different abstraction levels of the production over the whole life cycle. The different abstraction levels, i.e. machine, production system and production network, are decoupled based on a service-oriented approach that defines interactions between these abstraction levels. The requirements to implement this approach are determined for the different levels where special notice is given to changing requirements over the life cycle of the production. With respect to the requirements, recommendations are given considering the integration of the concept in existing productions. Finally, potential benefits of this concept are discussed.
Asset Administration Shell for the Wiring Harness System
Authors: Schnauffer Georg , Görzig David , Kosel Christian , Diemer Johannes
Published: June 2023

The wiring harness is one of the most expensive components of the automobile. It is still a custom-made product despite the high-volume production in the automotive industry. However, various trends, such as increasing fragility of supply chains and functional safety demands for autonomous driving are demanding the automation of the value creation processes. But in mass customisation, automation needs the digitalisation of all information flows. Machines and processes must be able to automatically gather all required information. In the wiring harness industry, much of the information has been geared toward processing by humans and has hardly been digitised at all. One of the foundations for Industry 4.0-oriented automation is ergo the existence of complete digital information of each wiring harness. A digital twin of the wiring harness is required. The Asset Administration Shell (AAS) is the technical concept for transparently interoperating with the digital twin. The project “Asset Administration Shell for the Wiring Harness” or in German (Verwaltungsschale für den Leitungssatz - VWS4LS) creates the first complete digital description of the wiring harness based on the AAS. As a result, all actors in the value network can access complete and consistent data (“single point of truth”), enrich it, and control its application through authorisations. To achieve this goal, a consortium from all levels of the value network was assembled for VWS4LS starting with the OEM, through the suppliers at the various levels of the value chain, and to the software suppliers and machine manufacturers. This publication presents the project and its initial results.
Case Study on Localization for Robotic Wire Harness Installation
Authors: Wnuk Markus , Zürn Manuel , Paukner Matthias , Ulbrich Sascha , Lechler Armin , Verl Alexander
Published: June 2023

Wire harness installation is one of the most challenging processing steps for automation in automotive production. Wire harnesses have an infinite number of degrees of freedom, such that they change their shape continuously during manipulation. As of today, the human’s ability to perceive the wire harness and deal with its shape changes, is unmatched by any technical solution. Therefore, wire harnesses are still installed manually. This paper proposes a concept for wire harness localization and applies it for robotic wire harness installation. The concept uses two stereo cameras, one to perceive the shape of the wire harness and obtain rough position estimates of wire harness components, and a second for accurate 6D pose estimation of the individual components. The concept is evaluated with a case study on localization in a car chassis, where the accuracy and limitations of the concept are investigated by practical experiments.
Traceability in Battery Production: Cell-Specific Marker-Free Identification of Electrode Segments
Authors: Riexinger Günther , Regina David J. , Haar Christoph , Schmid-Schirling Tobias , Landwehr Inga , Seib Michael , Lips Jonas , Fehrenbach Simon , Stübing Julian , Carl Daniel , Sauer Alexander
Published: June 2023

Digitalization in battery production, as well as the increase and stabilization of product quality of lithium-ion battery cells, require the elimination of information gaps between processes to enable the traceability of components and process steps to the finished product. In lithium-ion battery cell manufacturing, using a traceability system is considered a promising approach to reduce scrap rates and enable more efficient production. Today, traceability is possible from the assembled cell onwards. However, with a view to the new EU battery regulation, complete traceability down to the material needs to be ensured. One of the challenges in this context is to ensure both, traceability in continuous electrode production and cell-specific identification within the production chain. This paper presents an approach for identifying individual electrode segments without identification markers, using the individual microstructure of the electrode surface. The Fraunhofer Institute for Manufacturing Engineering and Automation IPA and the Fraunhofer Institute for Physical Measurement Techniques IPM are further developing and testing an identification technique known as Track & Trace Fingerprint. This technique is dedicated to serialization within battery production as part of the joint project DigiBattPro 4.0 and to be implemented at the Center for Digitalized Battery Cell Manufacturing (ZDB) of Fraunhofer IPA.
Multi-agent Interaction Structure for Enabling Subsidiary Planning and Control in Modular Production Systems
Authors: Komesker Simon , Bartels Jonathan , Wagner Achim , Ruskowski Martin
Published: June 2023

Modular production systems enable resilient production processes through decoupled production processes. On the way to implementing flexible and adaptable production systems, information support plays a decisive role. Only the use of intelligent and structured information processing across previous system boundaries and areas enables the coordination of requirements and capacities in dynamic production environments. The rigid communication structures in information systems of current production systems therefore need to be replaced by dynamic interaction, both horizontally between entities and vertically between different hierarchical levels. Multi-agent systems (MAS) are one way to meet the requirements for centralized and decentralized decision making in complex (cyber physical production) systems (CPPS). To prepare the instantiation of a MAS, it is necessary to structure and describe the information flows of a production system.

In this paper, the results of a simulation experiment for the implementation of collaborative, subsidiary decision making based on a model-based system structure are presented. Productivity potentials of more than 10% can be shown by using collaborative manufacturing strategies.
Requirements for a Process to Remanufacture EV Battery Packs Down to Cell Level and Necessary Design Modifications
Authors: Graner Melina , Heieck Frieder , Fill Alexander , Birke Peter , Hammami Woidy , Litty Katharina
Published: June 2023

In case of electric vehicles (EV) powered by lithium ion traction batteries (LIB), remanufacturing processes nbecome increasingly important due to their rising market share and valuable raw materials. LIB can account for up to 40% of the total EV cost. Often, only a small portion of the cells are significantly degraded when the usable battery capacity falls below 80%, which is currently considered the standard end-of-life criterion. However, in order to enable efficient remanufacturing, novel battery design principles are required. This paper discusses the requirements, opportunities and challenges of future remanufacturing processes of LIBs down to the cell level using a battery system of a commercial vehicle as an example. It gives an overview of the current state-of-the-art manufacturing processes of battery systems and shows the developed overall remanufacturing process including condition assessment, disassembly and reassembly. Subsequently, requirements on future designs are discussed. The state-of-the-art of EV batteries is evaluated based on these requirements to determine where incompatible connections such as welded contacts or adhesive joints conflict with remanufacturing design principles.
Improvement of the Scheduling of Automotive Testing Processes Based on Production Scheduling Methods
Authors: Stütz Leon , König Timo , Bader Roman , Kley Markus
Published: June 2023

Increasing challenges in the automotive industry are caused by shorter development times for products, greater diversity of variants and increasing cost pressure. Testing plays an elementary role within the product development process (PDP). There are already many publications that deal with the early phases of the PDP, but relatively few that address testing. Inefficient scheduling leads to suboptimal use of development and testing resources.

Automotive testing is characterized by high momentum and process complexity. The complexity of testing is determined, among other things, by the number of test rigs in a test field, the number and diversity of test objects, the type of testing and the preparatory setups. In addition, complex testing processes at the component and system level require a large number of human and material resources, whose time availability and sequence must be coordinated with the testing process. The sequence planning is subject to a high inherent dynamic because unexpected changes and disturbances of the process can occur during the testing. These changes require a rescheduling of the testing process. If done manually, the rescheduling results in high costs.

Based on known production planning methods, a solution approach is derived for improved utilization of test field resources for the automotive sector. The planning is optimized with a multitude of product - and process-related dependencies and restrictions using mixed-integer linear programming, a standardized method from operations research. The test field is simulated via a discrete event simulation. The proposed method considers the availability of essential resources.
A non-PMU-based WAN protection scheme for swing detection and stability enhancement in power systems
Authors: El-Metwally Ehab A. , Attia Mahmoud A. , El-Shimy Mohamed
Published: June 2023

This paper presents a scheme for power swing detection and stability assessment for multi-machine power systems in addition to a brief survey on that topic. The scheme adopts smart grid perception. It is an asynchronous scheme that uses the rate of change of the angle of the generator bus voltage instead of synchronously estimating the absolute rotor angle value for stability assessment. Therefore, it does not require phasor measurement units (PMUs). Instead, it uses commercially available intelligent electronic devices (IEDs). It introduces a new application of the multicast Generic Object Oriented Substation Event (GOOSE) protocol or its routable version (R-GOOSE) to reflect the disturbance in the power grid on the transmission pattern of data packets over the grid data network. In this scheme, the angle change information is transmitted in the form of GOOSE packets simultaneously from the IEDs that readily measure the angles of the affected generators. On the other hand, the detecting device identifies the stability status of each affected generator. The proposed scheme is validated by simulating disturbances on the IEEE 39-bus system. The results show that the scheme can discriminate between stable and unstable swings. In addition, the loss of synchronism of the unstable generator is predicted ahead of its occurrence by enough time to take an appropriate action.
Can coenzyme Q10 alleviate the toxic effect of fenofibrate on skeletal muscle?
Authors: El-Bassouny Dalia R. , Mansour Alyaa A. , Ellakkany Amany S. , Ayuob Nasra N. , AbdElfattah Amany A.
Published: June 2023

Fenofibrate (FEN) is an antilipidemic drug that increases the activity of the lipoprotein lipase enzyme, thus enhancing lipolysis; however, it may cause myopathy and rhabdomyolysis in humans. Coenzyme Q10 (CoQ10) is an endogenously synthesized compound that is found in most living cells and plays an important role in cellular metabolism. It acts as the electron carrier in the mitochondrial respiratory chain. This study aimed to elucidate FEN-induced skeletal muscle changes in rats and to evaluate CoQ10 efficacy in preventing or alleviating these changes. Forty adult male rats were divided equally into four groups: the negative control group that received saline, the positive control group that received CoQ10, the FEN-treated group that received FEN, and the FEN + CoQ10 group that received both FEN followed by CoQ10 daily for 4 weeks. Animals were sacrificed and blood samples were collected to assess creatine kinase (CK). Soleus muscle samples were taken and processed for light and electron microscopic studies. This study showed that FEN increased CK levels and induced inflammatory cellular infiltration and disorganization of muscular architecture with lost striations. FEN increased the percentage of degenerated collagen fibers and immune expression of caspase-3. Ultrastructurally, FEN caused degeneration of myofibrils with distorted cell organelles. Treatment with CoQ10 could markedly ameliorate these FEN-induced structural changes and mostly regain the normal architecture of muscle fibers due to its antifibrotic and antiapoptotic effects. In conclusion, treatment with CoQ10 improved muscular structure by suppressing oxidative stress, attenuating inflammation, and inhibiting apoptosis.
A high-quality feature selection method based on frequent and correlated items for text classification
Authors: Mamdouh Farghaly Heba , Abd El-Hafeez Tarek
Published: June 2023

The feature selection problem is a significant challenge in pattern recognition, especially for classification tasks. The quality of the selected features plays a critical role in building effective models, and poor-quality data can make this process more difficult. This work explores the use of association analysis in data mining to select meaningful features, addressing the issue of duplicated information in the selected features. A novel feature selection technique for text classification is proposed, based on frequent and correlated items. This method considers both relevance and feature interactions, using association as a metric to evaluate the relationship between the target and features. The technique was tested using the SMS spam collecting dataset from the UCI machine learning repository and compared with well-known feature selection methods. The results showed that the proposed technique effectively reduced redundant information while achieving high accuracy (95.155%) using only 6% of the features.
AWARE A novel web application to rapidly assess cardiovascular risk in type 2 diabetes mellitus
Authors: Berra Cesare , Manfrini Roberto , Mirani Marco , Bucciarelli Loredana , Zakaria Ahmed S. , Piccini Sara , Ghelardi Renata , Lunati Maria Elena , Rodovalho Sylka , Bifari Francesco , Fiorina Paolo , Folli Franco
Published: June 2023

Aim

To describe the development of the AWARE App, a novel web application for the rapid assessment of cardiovascular risk in Type 2 Diabetes Mellitus (T2DM) patients. We also tested the feasibility of using this App in clinical practice.

Methods

Based on 2019 European Society of Cardiology/European Association for the Study of Diabetes criteria for cardiovascular risk stratification in T2DM, the AWARE App classifies patients into very high (VHCVR), high (HCVR) and moderate (MCVR) cardiovascular risk categories. In this retrospective clinical study, we employed the App to assess the cardiovascular risk of T2DM patients, while also collecting data about current glycaemic control and pharmacological treatment.

Results

2243 T2DM consecutive patients were evaluated. 72.2% of the patients were VHCVR, 8.9% were HCVR, 0.8% were MCVR while 18.2% did not fit into any of the risk categories and were classified as “moderate-to-high” (MHCVR). Compared with the other groups, patients with VHCVD were more frequently ≥ 65 years old (68.9%), with a longer disease duration (≥ 10 years [56.8%]), a history of cardiovascular disease (41.4%), organ damage (35.5%) and a higher numbers of cardiovascular risk factors. Patients with MHCVD generally had disease duration < 10 years (96%), younger age (50–60 years [55%]), no history of cardiovascular disease, no organ damage, and 1–2 cardiovascular risk factors (89%). Novel drugs such as Glucagon Like Peptyde 1 Receptor Agonists or Sodium-Glucose Linked Transporter 2 inhibitors were prescribed only to 26.3% of the patients with VHCVR and to 24.7% of those with HCVR. Glycaemic control was unsatisfactory in this patients population (HbA1c 7.5 ± 3.4% [58.7 ± 13.4 mmol/mol]).

Conclusions

The AWARE App proved to be a practical tool for cardiovascular risk stratification of T2DM patients in real-world clinical practice.
Quantification of titanium and zirconium elements in oral mucosa around healthy dental implants: a case–control pilot study
Authors: Cionca Norbert , Meyer Julien , Michalet Sophie , Varesio Emmanuel , Hashim Dena
Published: June 2023

Objectives

Metallic particles are detected in different sites of the oral cavity, mainly in patients with peri-implantitis lesions. The aim of this pilot study was to analyze the levels of titanium and zirconium elements in the oral mucosa around healthy implants and to investigate the impact of titanium exogenous contamination on the measurements.

Materials and Methods

Forty-one participants were included in this three-phase study. Two groups of subjects were defined according to presence of titanium or zirconia implants (n: 20) or without any implants nor metallic restorations (n:21). Thirteen patients (n: 5 with zirconia implant; n: 3 with titanium implants; n: 5 control group) took part to the first part designed to optimize and validate the method of detecting titanium (Ti) and zirconium (Zr) elements in the oral mucosa and gingival tissues by the Inductively Coupled Plasma Mass Spectrometry (ICPMS). The second phase compared the levels of Ti and Zr concentrations in patients with implants (n: 12) and without implants (n: 6) who were controlled for their intake of titanium dioxide (TiO2). The last step included ten control subjects without any metallic devices to measure the concentration of Ti and Zr before and after having candies containing TiO2.

Results

In the first phase, concentrations of Ti and Zr were below the limit of detection (LOD) in most cases, 0.18 μg/L and 0.07 μg/L respectively. In the titanium group, two out of three subjects displayed concentrations above the LOD, 0.21 μg/L and 0.66 μg/L. Zr element was only found in patients with zirconia implants. After controlling the intake of TiO2, all concentrations of Ti and Zr were below the limit of quantification (LOQ). Moreover, in patients with no implants, the Ti concentration in gingiva cells was superior for 75% of the samples after having a TiO2 diet.

Conclusions

Zirconium was only found in patients with zirconia implants, whereas titanium was detected in all groups even in subjects with no titanium implants. Zirconium and titanium elements were not detected in patients who were controlled for their intake of food and their use of toothpaste irrespective of the presence of implants or not. For 70% of the patients, the titanium detection was directly influenced by the intake of TiO2 contained candies.

Clinical relevance

When analyzing titanium particles, it is necessary to pay attention to the risk of contamination bias brought by external products. When this parameter was controlled, no titanium particles were detected around clinically healthy implants.
Scholarly recommendation systems: a literature survey
Authors: Zhang Zitong , Patra Braja Gopal , Yaseen Ashraf , Zhu Jie , Sabharwal Rachit , Roberts Kirk , Cao Tru , Wu Hulin
Published: June 2023

A scholarly recommendation system is an important tool for identifying prior and related resources such as literature, datasets, grants, and collaborators. A well-designed scholarly recommender significantly saves the time of researchers and can provide information that would not otherwise be considered. The usefulness of scholarly recommendations, especially literature recommendations, has been established by the widespread acceptance of web search engines such as CiteSeerX, Google Scholar, and Semantic Scholar. This article discusses different aspects and developments of scholarly recommendation systems. We searched the ACM Digital Library, DBLP, IEEE Explorer, and Scopus for publications in the domain of scholarly recommendations for literature, collaborators, reviewers, conferences and journals, datasets, and grant funding. In total, 225 publications were identified in these areas. We discuss methodologies used to develop scholarly recommender systems. Content-based filtering is the most commonly applied technique, whereas collaborative filtering is more popular among conference recommenders. The implementation of deep learning algorithms in scholarly recommendation systems is rare among the screened publications. We found fewer publications in the areas of the dataset and grant funding recommenders than in other areas. Furthermore, studies analyzing users’ feedback to improve scholarly recommendation systems are rare for recommenders. This survey provides background knowledge regarding existing research on scholarly recommenders and aids in developing future recommendation systems in this domain.
RETRACTED ARTICLE: ITGA3 acts as a purity-independent biomarker of both immunotherapy and chemotherapy resistance in pancreatic cancer: bioinformatics and experimental analysis
Authors: Zheng Xiaohao , Du Yongxing , Liu Mingyang , Wang Chengfeng
Published: June 2023

Contribution of integrin superfamily genes to treatment resistance remains uncertain. Genome patterns of thirty integrin superfamily genes were analyzed of using bulk and single-cell RNA sequencing, mutation, copy number, methylation, clinical information, immune cell infiltration, and drug sensitivity data. To select the integrins that are most strongly associated with treatment resistance in pancreatic cancer, a purity-independent RNA regulation network including integrins were constructed using machine learning. The integrin superfamily genes exhibit extensive dysregulated expression, genome alterations, epigenetic modifications, immune cell infiltration, and drug sensitivity, as evidenced by multi-omics data. However, their heterogeneity varies among different cancers. After constructing a three-gene (TMEM80, EIF4EBP1, and ITGA3) purity-independent Cox regression model using machine learning, ITGA3 was identified as a critical integrin subunit gene in pancreatic cancer. ITGA3 is involved in the molecular transformation from the classical to the basal subtype in pancreatic cancer. Elevated ITGA3 expression correlated with a malignant phenotype characterized by higher PD-L1 expression and reduced CD8+ T cell infiltration, resulting in unfavorable outcomes in patients receiving either chemotherapy or immunotherapy. Our findings suggest that ITGA3 is an important integrin in pancreatic cancer, contributing to chemotherapy resistance and immune checkpoint blockade therapy resistance.

Graphical abstract
Multi-GNSS PPP solutions with different handling of system-specific receiver clock parameters and inter-system biases
Authors: Mikoś Marcin , Kazmierski Kamil , Hadas Tomasz , Sośnica Krzysztof
Published: June 2023

In the multi-GNSS solutions integrating GPS, GLONASS, Galileo, and BeiDou, the receiver clock may be treated twofold; the clock parameter may be estimated for each GNSS separately or the common clock can be estimated, e.g., for GPS, with inter-system biases (ISBs) for other systems. The latter strategy reduces the number of estimated independent clock parameters per epoch almost by a factor of four because the clock parameters are estimated epoch-wise, whereas ISBs are estimated as constant values for the entire day or month. Due to the discontinuities in reference satellite clocks, the estimated ISBs and receiver clock parameters have also to be reinitialized at day boundaries. This raises questions about whether only the common clock has to be reset or all ISB values and what is the impact of the reinitialization of clock parameters with covariance values when estimating system-specific clock parameters. We analyze the effects of different types of stochastic modeling applied to the parameters of clocks and ISBs. In this study, we test five different strategies to clock handling in multi-GNSS kinematic Precise Point Positioning derived continuously for one month. We found that two solutions can be considered equivalent: (1) estimating system-specific clocks and (2) estimating the common clock with ISB and resetting at day boundaries the common clock parameter and ISBs. Oppositely, resetting only the common clock parameter or assuming that the ISB keep their stabilities over long periods is insufficient to obtain superior results of station coordinates and reliable time transfer results.
Geometric deep learning and equivariant neural networks
Authors: Gerken Jan E. , Aronsson Jimmy , Carlsson Oscar , Linander Hampus , Ohlsson Fredrik , Petersson Christoffer , Persson Daniel
Published: June 2023

We survey the mathematical foundations of geometric deep learning, focusing on group equivariant and gauge equivariant neural networks. We develop gauge equivariant convolutional neural networks on arbitrary manifolds $$\mathcal {M}$$
M
using principal bundles with structure group K and equivariant maps between sections of associated vector bundles. We also discuss group equivariant neural networks for homogeneous spaces $$\mathcal {M}=G/K$$

M
=
G
/
K

, which are instead equivariant with respect to the global symmetry G on $$\mathcal {M}$$
M
. Group equivariant layers can be interpreted as intertwiners between induced representations of G, and we show their relation to gauge equivariant convolutional layers. We analyze several applications of this formalism, including semantic segmentation and object detection networks. We also discuss the case of spherical networks in great detail, corresponding to the case $$\mathcal {M}=S^2=\textrm{SO}(3)/\textrm{SO}(2)$$

M
=

S
2

=
SO

(
3
)

/
SO

(
2
)

. Here we emphasize the use of Fourier analysis involving Wigner matrices, spherical harmonics and Clebsch–Gordan coefficients for $$G=\textrm{SO}(3)$$

G
=
SO
(
3
)

, illustrating the power of representation theory for deep learning.
The Criminal Selfie: Conveying Grievance While Recording and Live Streaming Antisocial Behavior
Authors: Sandhu Ajay , Trottier Daniel
Published: June 2023

Despite attempts to regulate content, social media platforms continue to host images of antisocial behavior and crime. These images include dashboard videos of road rage and CCTV footage of shoplifting, as well as more extreme recordings of torture, sexual assault, suicide, and mass shootings. These images are often produced by offenders of their own volition using smartphone cameras and wearable recording devices. We understand criminal selfies as media content of antisocial behavior or crime produced by or with the awareness of an offender. By producing a criminal selfie, an offender renders themselves vulnerable to public scrutiny, legal punishment, and other negative outcomes. Yet criminal selfies remain a popular form of toxic online communication. This manuscript theorizes that one of the previously underappreciated explanations for criminal selfies is a desire to broadcast personal grievances. In such cases, they allow an offender to publicize their motivating politics and to offer them to an online audience for consideration and discussion. Antisocial content often evokes an unfavorable ratio of denunciation versus supportive responses. We claim that some offenders wager that a criminal selfie nonetheless earns their grievances a degree of awareness and, potentially, consequence. Some criminal selfies reflect a willingness to self-incriminate by documenting antisocial behavior in hopes that their images will contribute to public discourse. This article contributes to studies of criminal visibility by addressing how it can be intended as political expression. We first outline the concept of the criminal selfie and how it reflects a changing relationship between visibility and criminality in contemporary digital society. We then review literature on the motives of criminals who film themselves. We seek to compliment this literature by considering socially and politically aggrieved individuals producing antisocial content. This includes livestreams of white nationalist mass shootings (Christchurch, Halle) as well as a series of Reddit groups that solicit and (counter-)denounce antisocial grievances by digital media users (r/iamverybadass, r/publicfreakout, r/iamatotalpieceofshit).
Modeling the biological growth with a random logistic differential equation
Authors: Ornelas Arelly , Delgado-Vences Francisco , Morales-Bojórquez Enrique , Cruz-Escalona Victor Hugo , Marín-Enríquez Emigdio , Hernández-Camacho Claudia J.
Published: June 2023

We modeled biological growth using a random differential equation (RDE), where the initial condition is a random variable, and the growth rate is a suitable stochastic process. These assumptions let us obtain a model that represents well the random growth process observed in nature, where only a few individuals of the population reach the maximal size of the species, and the growth curve for every individual behaves randomly. Since we assumed that the initial condition is a random variable, we assigned a priori density, and we performed Bayesian inference to update the initial condition’s density of the RDE. The Karhunen–Loeve expansion was then used to approximate the random coefficient of the RDE. Then, using the RDE’s approximations, we estimated the density f(p, t). Finally, we fitted this model to the biological growth of the giant electric ray (or Cortez electric ray) Narcine entemedor. Simulations of the solution of the random logistic equation were performed to construct a curve that describes the solutions’ mean for each time. As a result, we estimated confidence intervals for the mean growth that described reasonably well the observed data. We fit the proposed model with a training dataset, and the model is tested with a different dataset. The model selection is performed with the square of the errors.
Neuropathic foot ulcers in the tallest patients with acromegalic gigantism: a common and significant problem. Historical overview
Authors: de Herder Wouter W. , Raymond Warren A.
Published: June 2023

Purpose

We present a historical overview on neuropathic ulcers in patients with acromegalic gigantism.

Materials and methods

The case histories of 6 famous patients with acromegalic gigantism and living in the twentieth century were analyzed. The combined final height and maximum weight of these giants were: 272 cm. & 215.9 kg., 218.4 cm. & 125 kg., 242 cm. & 165 kg., 220.5 cm. & 135 kg., 235 cm. & 136 kg. and 224.8 cm. & 174 kg.

Conclusions

Neuropathic foot ulcers leading to hospital admissions and surgical and medical interventions were reported in 6 patients with acromegalic gigantism. These ulcers significantly impaired the daily activities of these individuals. Neuropathies of the sural nerve in patients with acromegalic gigantism can lead to hypoesthesia and hypoalgesia of the lower legs and feet. Potential contributing factors for the development of neuropathic ulcers of the feet in patients with acromegalic gigantism and neuropathy might be leg and foot deformities, muscle weakness and poor quality footwear. Diabetes mellitus, or impaired glucose intolerance does not necessarily seem to play a role.
Toxicity Assessment of Urban Dust from Barranquilla, a Colombian Caribbean City, using Caenorhabditis elegans
Authors: Osorio-Martinez Jorge , Silva Luis F. , Flores Erico M. M. , Druzian Gabriel T. , Olivero-Verbel Jesus
Published: June 2023

Urban dust is a reservoir of potentially toxic elements (PTEs) that can be incorporated into aquatic ecosystems where they bioaccumulate and biomagnify causing toxic effects. The aim of this work was to assess the PTEs’ concentrations and toxicity to Caenorhabditis elegans of inorganic extracts from urban dust of Barranquilla, the largest Colombian Caribbean city. Trace elements were analyzed by inductively couple plasma-mass spectrometry. PTEs concentration decreased in the order Sr > Cu > Ba > Mo > Se > Cr > V > Ni > As > Zn > Rb > Mn > Sb > Co > Sn > Cd > La > Ce >Tl ≈ Bi > Ag ≈ Pb. Inorganic extracts from urban dust affected physiological parameters in the nematode, such as survival, growth and locomotion. Lethality showed a positive relation with Sr and negative with V. Growth displayed a negative association with Mo. Expression of mtl-2, sod-4, and unc-25 genes was induced by PTEs. The results suggest that C. elegans is a sensitive organism capable of responding to exposure to urban dust extracts, being a suitable sensor for the implementation of warning systems related to risks to biota associated with air pollution.
DNA methylation clocks for clawed frogs reveal evolutionary conservation of epigenetic aging
Authors: Zoller Joseph A. , Parasyraki Eleftheria , Lu Ake T. , Haghani Amin , Niehrs Christof , Horvath Steve
Published: June 2023

To address how conserved DNA methylation-based epigenetic aging is in diverse branches of the tree of life, we generated DNA methylation data from African clawed frogs (Xenopus laevis) and Western clawed frogs (Xenopus tropicalis) and built multiple epigenetic clocks. Dual species clocks were developed that apply to both humans and frogs (human-clawed frog clocks), supporting that epigenetic aging processes are evolutionary conserved outside mammals. Highly conserved positively age-related CpGs are located in neural-developmental genes such as uncx, tfap2d as well as nr4a2 implicated in age-associated disease. We conclude that signatures of epigenetic aging are evolutionary conserved between frogs and mammals and that the associated genes relate to neural processes, altogether opening opportunities to employ Xenopus as a model organism to study aging.
Combining seeded region growing and k-nearest neighbours for the segmentation of routinely acquired spatio-temporal image data
Authors: Zerweck Lukas , Wesarg Stefan , Kohlhammer Jörn , Köhm Michaela
Published: June 2023

Purpose

The acquisition conditions of medical imaging are often precisely defined, leading to a high homogeneity among different data sets. Nonetheless, outliers or artefacts still appear and need to be reliably detected to ensure a reliable diagnosis. Thus, the algorithms need to handle small sample sizes especially, when working with domain specific imaging modalities.

Methods

In this work, we suggest a pipeline for the detection and segmentation of light pollution in near-infrared fluorescence optical imaging (NIR-FOI), based on a small sample size. NIR-FOI produces spatio-temporal data with two spatial and one temporal dimension. To calculate a two-dimensional light pollution map for the entire image stack, we combine region growing and k-nearest neighbours (kNN), which classifies pixels into fore- and background by its entire temporal component. Thus, decision-making on reduced data is omitted.

Results

We achieved a $$F_1$$

F
1

score of 0.99 for classifying a data set as light polluted or pollution-free. Additionally, we reached a total $$F_1$$

F
1

score of 0.90 for detecting regions of interest within the polluted data sets. Finally, an average Dice’s coefficient measuring the segmentation performance over all polluted data sets of 0.80 was accomplished.

Conclusions

A Dice’s coefficient of 0.80 for the area segmentation does not seem perfect. However, there are two main factors, besides true prediction errors, lowering the score: Segmentation mistakes on small areas lead to a rapid decrease in the score and labelling errors due to complex data. However, in combination with the light-polluted data set and pollution area detection, these results can be considered successful and play a key role in our general goal: Exploiting NIR-FOI for the early detection of arthritis within hand joints.
The analysis of partisan differences in advanced democracies. The “independent variable problem” reconsidered
Authors: Zohlnhöfer Reimut
Published: June 2023

The paper challenges the idea that using governing parties’ policy positions is necessarily desirable in quantitative analyses of partisan differences in public policies. Rather, for some research questions parties’ affiliation with certain party families is the preferable solution. The paper shows that the use of policy positions instead of party family affiliation shifts the research question from asking whether parties make a difference in public policy to the question whether parties in government do what they promise. This shift can have considerable analytical costs and can potentially blindfold scholars for certain dynamics. Moreover, the use of party family affiliation has less drawbacks than is often claimed even under multidimensional party competition if the simple distinction between left, center and right parties is abandoned and more fine-grained data for various party families are used.