bluuebunny/crossref_metadata_2025 huggingface dataset:
Methodology for embedding mineral insulated cables into DIN 1.2311 tool steel for the manufacture of smart tooling
Authors: Ostolaza M , Arrizubieta J I , Muro M , Ruiz J E , Artola G , Lamikiz A
Published: October 2021

In the present climate led by industry and digital manufacturing, the implementation of intelligent tooling in manufacturing processes has become imperative. In the case of metal forming processes, this requirement is translated into controlling the material flow and the temperature in the tool-part contact interface. In this manner, not only the mechanical properties of the produced parts are predicted, but also the status of the tooling can be monitored. To that end, a methodology for embedding sensors close to key areas needs to be developed. Additive Manufacturing holds a great potential for enabling such integration. However, high process temperatures inherent to metal AM processes are a limiting factor in this matter. With the aim of taking a step forward in this field, in the present work a methodology for embedding mineral insulated cables into metal forming tooling has been developed. Furthermore, the minimum cable size integrable by means of this technology has been determined and the main limitations of this process exposed. It has been concluded that low energy inputs are necessary to avoid the destruction of the sensorial components and that adaptive process parameters are necessary if sound metal coatings over undamaged components are to be deposited.
Laser engraving of chip-breaker geometry on ceramic cutting tools
Authors: Ukar E , Arrizubieta J I , Ruiz J E , Ostolaza M , Lamikiz A
Published: October 2021

Laser texturing is a process that allows the selective removal of material by applying a high energy density over a small area during a very short time interval. Although it is generally common to use ultra-short pulse (ps or fs) lasers for tool engraving, in certain applications it is possible to use short pulse (ns) lasers. In this work, the material removal rate of an ns laser has been evaluated in chip-breaker milling on Al2O3 cutting inserts reinforced with SiC whiskers. The results obtained show that by milling chip-breaker geometries it is possible to reduce the cutting forces, however, the process parameters used are key to obtain an adequate surface finish without embrittlement of the tool. By means of an adequate design, a reduction in cutting forces of 20% was achieved; additionally, it has been proved that there is a high dependence between tool life and the milling strategy used.
Effect of laser heat treatments on the hardness of tool steels
Authors: Lagarinhos J N , Afonso D , Torcato R , Santos C , Oliveira M
Published: October 2021

The application of laser heat treatments (LHT) has been growing attention in the last years, due to the effectiveness of localized hardening that can improve the tribological properties of steels. AISI P20 mod. steel is commonly used for plastic injection moulds applications and can be heat-treated to achieve high hardness values. This work presents an experimental investigation on the laser local heat treatments effect on the hardness of AISI P20 mod. steel parts, using a high-power diode laser. Different heat treatments at 1060 °C and 1100 °C using a feed rate of 10 mm·s-1 and 15 mm·s-1 were applied on the steel. The LHT were assessed through the hardness mapping trough depth and width. The results showed that the hardness of as-received P20 mod. tool steel is approximately 300 HV, and after LHT occurred an increment to around 625 HV with a fair hardness distribution. LHT had a minimum of 0.8mm and a maximum of 1.0mm depth.
Fused Filament Fabrication over fabrics – experiments and applications
Authors: Legoinha C , Afonso D , Pires L
Published: October 2021

The focus of this paper is to explore the use of Fused Filament Fabrication technology, a material extrusion additive manufacturing technology, by depositing melted Polilactic Acid (PLA) over a substrate – fabric - instead of on an empty building tray. The textile’s composition, nozzle and building plate temperature, printed PLA thickness and printed geometry have been considered as variables that could influence the structural and adhesion properties on this study so, therefor, were took into consideration and tested throughout the printing process through specimens printed with different combined parameters. The aim of this exploration process was developing an experimental procedure to study the limitations and capabilities of this printing technology over textiles, and which different variables’ combination would contribute to a better overall result in the development of a self-supporting textile based structural model, that could be apply in different contexts without the need of any extra external support. Results showed that PLA adherence to the fabric is correlated with nozzle/building plate temperature and printing thickness: higher temperature and thickness provide higher adherence. The weave of the textile didn´t reflect on better results but the polyester felt fabric exhibit maximum adherence with printed PLA in all sets of temperatures. In addition, geometries with reinforcement lines along the fabric stress direction provided better structural results. These results enable new application possibilities for the FFF technology combined in fabrics such as in interior, fashion and shoe ware design.
Experimental measuring of printing speed in FDM
Authors: Dorado R , Pérez F J , Medina G , Guerrero F
Published: October 2021

Fused Deposition Modeling (FDM) technology, based on material extrusion, helps additively manufacture, using cheap printers, stable mechanical parts in different materials. The dimensional deviations and staircase effect are the main drawbacks of this approach and limit its use to prototypes. The linear interpolation used to define the hot-end movements is responsible for continuous speed changes along the tool-path, contributing to dimensional and surface errors. In that sense, the study of the speed profile can help to improve the process. This work explains two printing speed estimation approaches an out-process measurement method, which estimates the average speed as a function of the interpolation segment length and direction, and an in-process method based on encoder measurements. We applied these solutions and an analytical approximation based on a trapezoidal speed profile to a printed 3D Archimedean spiral. All approaches detect abrupt speed changes, potential candidates to produce extrusion-movement synchronization problems, and, therefore, part errors.
Research on desktop 3D Printing Multi-Material New Concepts
Authors: Fenollosa F , Uceda R , Tejo A , Calvo L , Poudelet L , Buj I
Published: October 2021

3D printing or Additive Manufacturing (AM) was originally born as a mono-material technology. And, nowadays, most of the applications are still using only one material. AM has a lot of potential but has not yet been fully explored, and access to the creation of multi-material products is an example of it. One of the most interesting areas is the introduction in the same part of materials with different rigidities, stiffer and softer areas, with differentiated values of mechanical strength and viscoelasticity. In the present work, a general vision of Additive Manufacturing under the vision of mono- and multi-material processes is given, and some existing 3D printing multi-material experiences related to Material Jetting (MJ) and Material Extrusion (ME) are briefly described. But it is in this latter field, linked to Desktop 3D printing (more accessible than typical proprietary industrial equipment), where on-going research could easily be spread: five research ME concepts are then presented, from a revolver print-head to silicone UV 3D printing, with their initial embodiment in the form of prototypes or/and testing, as a way to verify the difficulties that would be encountered in the transition from research to reality.
Supply chain production planning of a manufacturing project system 4.0: case study: Shipbuilding
Authors: Ramirez M , Pérez V , Gómez A , Montaño R , Batista M
Published: October 2021

Projects characterized by high difficulty in terms of planning and administrative control, require the strategies facilitated by Manufacturing Project Systems (MPS). Among them is an adequate management of the Supply Chain used as a competitive strategy. It could be said that in the case of shipbuilding, the Supply Chain is much more complicated due to the number of intervening parties and many shipyards have opted to include Concurrent Engineering with the implication of considering all the elements that make up the product life cycle. The objective of this article is based on the study of the existing applications for the integration of the companies’ management as well as the technological contributions that can collaborate to the integration of the Supply Chain production planning. Getting to identify the seven key technologies of Industry 4.0 that most contribute to the sustainability of shipbuilding.
Uncertainty determination of a microvolume characterized through confocal microscope technique
Authors: Berzal M , Barajas C , Christopher J M , Santamaría B , Munoz D
Published: October 2021

Standardized measurements protocols are widely used and necessary in order to ensure a relivable and repetitive data. This work introduces a new procedure to measure the volume of any irregular micro-hole on a rough surface. A filtering and fitting model is proposed for calculating the void volume of the cavity. Experimental point cloud is acquired by optically measuring the micro-hole with a confocal microscope. RANSAC algorithm is used to establish the reference plane, while the limits of the cavity and the volume are determined by a proposed algorithm. The mentioned model is validated by measuring six real samples. In addition, the corresponding uncertainty is estimated by using Monte Carlo method.
Environmental conditions compensation for a length measurement system based in laser interferometry for machine tool volumetric verification
Authors: Brosed F J , Aguilar J J , Acero R , Velázquez J , Santolaria J
Published: October 2021

Measurement systems based in laser interferometry have been usually used in industry for volumetric verification. The behaviour of these systems rely on the wavelength of the laser used and so the estimation of the refractive index of the ambient air is a fundamental step in the measurement process. The environmental conditions can be measured with an environmental compensation unit and several equations can be used to estimate the refractive index. When several measurement systems are needed to measure the position of the machine tool head simultaneously during a volumetric verification, the information of the environmental control unit has to be applied to all the measurements in order to compensate the measurement result with the ambience conditions. This can be done estimating an adequate compensation model from the environmental data. In this work the Ciddor equation has been used to adjust compensation models based in regression curves.
Development of a quality control system for the supply of silica refractory material from China
Authors: Álvarez D , García M
Published: October 2021

This document describes how to perform a quality control management of refractory silica material purchased in China. Silica refractories are key actors in the lifetime of the equipment and they are fundamental to ensure the adequate operation of the plant. The objective is to plan the sampling, minimising the number of tests to obtain an assessment of the quality of the consignment with the greatest precision. The types of destructive and non-destructive tests, the number of pieces to be inspected per batch and the acceptance criteria will be defined in this article. The quality control will be carried out at three levels, one to be performed by the manufacturer and the others by the buyer and the final client. The approval of the lots by the three parties ensures that the quality of the product is in accordance with the specifications. It will be achieved by dividing the order into different batches to treat them as independent units for acceptance or rejection. To avoid the loss of “see freight time” in case of rejection of any consignment, the customer’s quality control must be performed before shipping the batches.
A comparison of fitting criteria for circle arc measurement applications
Authors: Calvo R , Arteaga A , Domingo R
Published: October 2021

Measuring circular shape is a main task of dimensional metrology, characterized by circle diameter and its roundness, both for full circles and circle arcs. Point coordinates allows measuring both arcs and full circle, by fitting to substitution geometry, in many cases by least-squares criteria and fitting. Nevertheless, circle shape can be also characterized by the minimum zone, minimum circumscribed and maximum inscribed circles. This research presents a systematic experimental analysis of results of normal distributed points around the substitution circle through simulation, for different circle arc angles to the full circle and for the four mentioned fitting criteria. The results show the influence of arc angle in the variability of the results across criteria and the different behaviour depending on the arc amplitude. The results confirm the good stability and behaviour of least squares and minimum zone criteria, while warns the use of minimum circumscribed and maximum inscribed circles over half circumference. Experimental regression facilitates estimation of the minimum zone criteria from the least squares fitting that are independently verified with literature datasets with good results.
Effect of ambient temperature on machine tool compensation functions
Authors: Aguado S , Pérez P , Albajez J A , Velázquez J , Santolaria J
Published: October 2021

Volumetric verification is increasing daily its relevance. However, as it is based on mathematical compensation, it does not model only the influence of the machine tool’s geometric error to verify, but the total error of the data. Among all error sources, thermal variations due to changes in environmental conditions strongly affect MT position accuracy. This paper studies how verification changes affect compensation functions based on a modification of machine tool kinematic model and a generator of synthetic data. It takes into consideration the influence of the measurement noise on verification too. Moreover, the paper also studies how differences between verification and working conditions affect the accuracy of MT compensation functions. To do that, a brief explanation of the developed algorithm is presented.
Analysis of AZ31B – Ti6Al4V bimetallic extrusion by numerical simulation and Taguchi method
Authors: Fernández D , Rodríguez A , Camacho A M
Published: October 2021

This paper investigates the extrusion force and damage induced during an extrusion process to manufacture bimetallic cylinders combining a titanium alloy sleeve (Ti6Al4V) and a magnesium alloy core (AZ31B). A study has been carried out to determine the damage factor distribution through the extrusion process and how this factor together with the extrusion force are influenced by the manufacturing parameters (extrusion ratio, friction and die semi-angle) by means of finite element (FE) simulations. Also, a Taguchi Design of Experiments (DoE) and an Analysis of Variance (ANOVA) have been performed in order to study the influence of each parameter to minimize the extrusion force needed to perform the process and the damage in the extrudate. The results show that damage distribution in the sleeve does not follow any pattern, appearing in different region in a random way. However, in the core the damage always occurs in the region outside the contour of the sleeve, where it reaches the maximum value and afterwards remains stationary during the rest of the process. In the core, damage increases as friction factor does and it is independent of the cross-section reduction for low die semi-angles (15°) and reaches the maximum values for 60° die semi-angle. In both cases, damage and extrusion force, the more relevant factor to obtain minimum values is the die semi-angle.
Investigation of ball burnishing process using vibration and acoustic emission sensors
Authors: Fernandez I , Velazquez E , Marques J , Lluma J , Jerez R , Travieso J A
Published: October 2021

In this paper, a ball burnishing tool mounted in a CNC lathe is characterized. This tool may work as vibration assisted ball-burnishing tool and in conventional way. The characterization consists of acoustic emission measurements in both burnishing processes, and vibration measurements with tri-axial accelerometers. The acoustic emission measurements permit to investigate if any kind of damage is produced in the material by the burnishing process. An operational deflexion shape exercise has been performed with the vibration measurements. This permits to investigate the movement of the tool during the burnishing process and to evaluate the rigidity of the tool.
Investigation of defects in roll contacts of machine elements with Acoustic Emission and Unsupervised Machine Learning
Authors: Hillenbrand J , Detroy J , Fleischer J
Published: October 2021

In the age of Industry 4.0 and IIoT machines are becoming increasingly connected enabling continuous monitoring. A variety of information from machines and installed sensors is used to develop condition monitoring solutions. These systems are used to prevent premature failures and the follow-up costs due to machine downtime associated with them. Recent research in this area applies supervised machine learning, extracting features from captured signals and training classifiers. Supervised learning approaches require large amounts of labeled data, whose generation is time consuming and requires domain knowledge. For this reason, an unsupervised learning approach is being used in this work to distinguish between different defect and operation states of axial ball bearings. Within the scope of this work, acoustic emission (AE) measurements in the ultrasonic range are recorded and evaluated. Artificial defects are seeded in the rolling contact of axial bearings. From the AE signals a selection of state-of-the-art features is extracted. Then, the Laplacian Score, an unsupervised filter algorithm, is used to select the most significant features. Subsequently, the DBSCAN clustering algorithm is used to draw conclusions about the existing damage.
Superfinishing robotic cell to automate belt polishing process on critical aeronautical components
Authors: González M , Rodriguez A , Pereira O , López De Lacalle L N
Published: October 2021

Surface quality requirements on aeronautical components are critical. When components are manufactured via casting or forging processes, functional surfaces should be machined and, later on, these surfaces should be finished using polishing or other superfinishing techniques. These final processes are usually performed manually by experienced operators, mainly due to their complexity. Nowadays, new technologies provide a chance to automate these processes, but some aspects must be taken into account. On the one hand, it requires technological advances that allow process to be carried out in compliance with the required tolerances. Many of these technologies do not include in their scope the usual materials employed in aeronautical components, which are critical in terms of geometries and machinability. On the other hand, tests must be carried out with different tools and abrasive materials to establish optimum processing conditions in this type of automated process. In this line, the driver of the proposed work is to analyse the behaviour of different abrasive materials and their influence in material removal rate when process parameters increase. Test were performed using a robotic cell equipped with a pneumatic compensation system for pressure and cutting speed control. Obtained results may serve as a basis for defining operating conditions of this type of processes and help to understand their behaviour when dealing with different cutting conditions.
Design of a conceptual model for a maintenance object within a producer: impact on distribution network - a simulation case study
Authors: Gejo J , Gallego S , García M
Published: October 2021

Nowadays, logistics can be described as an interdisciplinary strategy to optimize the production system. Availability is, therefore, the link between logistics and industrial maintenance. To manage this paradigm, maintenance management for a production process plays a key role. Therefore, the purpose of this paper is to design a holistic process-oriented approach to assess the impact of maintenance management on the distribution network and end-customer. As a result, impacts and interrelationships between maintenance and distribution towards the end-customers are derived. Based on the conceptual model, a simulation case study in a supply chain with a producer and its distribution network is developed. Goal is to observe the results of a certain maintenance strategy and its related maintenance characteristics in the subsequent steps of the production process and in the end-customer through the distribution network. The analysis of the case study is performed by means of simulation. The simulation model is built using System Dynamics (SD). Thanks to the scenarios and their results the impact of the maintenance strategy of one object could be observed. The impact depends also on other factors than only maintenance of the object such as customer demand, stocks, supply chain steps and proximity to end-customers.
Methodology to estimate the modulus of elasticity of parts manufactured by FFF/FDM combining finite element simulations and experimental tests
Authors: Fernández V , García A , Camacho A M , Claver J , Rodríguez A , Sebastián M A
Published: October 2021

Due to the manufacturing characteristics “layer by layer” of Additive Manufacturing processes (AM) such as Fused Filament Fabrication (FFF) or Fused Deposition Modelling (FDM) techniques, the manufactured parts exhibit anisotropic behaviour, and therefore it is complex to estimate their mechanical response. Consequently, finite element (FE) modelling of the performance of this kind of additive parts can be time-consuming, especially for implicit algorithms. For this reason, in this work, a proposal of simplified FEM model is presented to reduce the computation time but keeping accurate results, when predicting the modulus of elasticity of FDM parts. The methodology is based in a combination of experimental and numerical simulation techniques. A FEM model is developed using the commercial finite element software Abaqus/Standard. The parameters considered in this study are the percentage of infill (25, 50 and 75%) and the construction orientation (XYZ). Tensile tests were performed following the guidelines specified in the standards UNE-EN ISO 17296-3 and UNE-EN ISO 527-2. The comparison of the elastic behaviour obtained by both experimental and simulation techniques allowed to adjust the simulation parameters, resulting in a simplified FE model. The methodology presented can be used as a prediction tool to analyse the tensile mechanical behaviour of this kind of samples.
3D printed surgical planning prototype manufactured by a hybrid multi-material 3D printer
Authors: Tejo A , Castellví A , Lustig P , Fenollosa F , Uceda R , Buj I , Krauel L , Valls A , Munuera J
Published: October 2021

Surgical planning is a preoperative method of pre-visualization that is carried out before or during a surgical intervention in order to achieve the best outcome. This can be done either image-based or hands-on. Regarding the first strategy, it is based on the use of medical images. However, it has a huge limitation, which is the difficulty of identifying anatomical structures (crucial for surgeons to make correct decisions) and distances between tissues without any physical support. This problem is overcome with the use of 3D models. Despite this important development, until nowadays most of the surgical planning prototypes were 3D printed either using the moulding technique, which might take several days, or high-cost technologies as is material jetting. That is why, the present manuscript seeks to solve the problems arose by the use of a hybrid-multi material 3D printer which can not only use several materials at the time, but also two 3D printing technologies. The prototype introduced in this study is a neuroblastoma, a common cancer among children.
Responding to rapidly changing product demand through a coordinated additive manufacturing production system: a COVID-19 case study
Authors: Goudswaard M , Gopsill J , Ma A , Nassehi A , Hicks B
Published: October 2021

COVID-19’s lockdown policies saw Modern Manufacturing Practice (MMP) – batch/mass/just-in-time supply chains – severed and societal demands rapidly change from products such as vehicles and clothing to Personal Protection Equipment (PPE), ventilators and equipment for remote working. The critical and, in many cases, life preserving, need for responsive manufacturing resulted in government and frontline services turning to society’s Additive Manufacturing (AM) capability in homes, schools, universities, and industry to provide essential products and product replacements. While AM managed to respond and support some government and frontline services, the highly distributed and diverse nature of the nation’s AM resources resulted in potentially avoidable production inefficiencies and delays. This paper develops and evaluates a series of strategies for coordinating AM for rapidly changing product demand to further enhance the responsiveness and productivity of AM. The strategies presented in the paper employ a host-client agent-based architecture that enable local governance of production thereby enabling distributed AM resource to come together to tackle society’s production needs without the need for centralised coordination. To enable and support local governance, it is necessary to understand how the combination of production logics impact the overall performance of the production system. Correspondingly, the contribution of this paper lies in the characterisation and quantification of the impacts of production logic through the metrics of Time in System, Lateness and Jobs in Queue and the consequences for responsive AM production systems.
Design Learning: a methodology for the autonomous design and manufacture of customised toys based on Machine Learning
Authors: Pardo M-A , Rodríguez L , Pavon P
Published: October 2021

Society is increasingly demanding products with a higher degree of customization and shorter manufacturing phases. This demand is currently conditioned by a context of reduced mobility due to Covid-19. For these reasons, a new methodology called Design Learning is proposed, capable of designing personalized toys autonomously to improve the physical and mental development of children, including those with special needs. This method is based on the automated study of the user through their activity on audio-visual platforms and social networks, and on the application of Machine Learning techniques, Augmented Reality, Mixed Reality, parametric CAD and Additive Manufacturing. The results of the experiment show that children are able to use the proposed method and enjoy using it. It has also been obtained, thanks to the techniques used, in addition to designing and manufacturing toys autonomously and contributing to the development of children, that this tool also favours the competence of small companies and reduces the carbon footprint produced by traditional manufacturing processes.
Design and fabrication of prototype of extrusion equipment for research and teaching purposes
Authors: Camacho A M , De Agustina B , Pérez A , Marín M , Rubio E M
Published: October 2021

In Engineering Schools, metal forming teaching laboratories are not always equipped with all the suitable equipment to show the students how metal forming operations are performed in industrial facilities, due mainly to space and/or economical limitations. In this work, a proposal of design and fabrication of prototype of extrusion equipment is presented, mainly for teaching purposes, but also, for research activities in extrusion processes. To reach the aim, the components of the prototype are integrated in a universal testing machine Hoytom HM-100kN. This kind of equipment is available in any Engineering School, which makes the proposal accessible to any lecturer interested in metal forming teaching. The final design of the prototype was made taking into account the possibility of using standardized components to facilitate both installation and maintenance tasks. It is also important to emphasize the modular nature of the design to allow its adaptation to different applications and case studies. The prototype presented has demonstrated to be able to produce long profiles by cold extrusion, not only with plasticine (typically used in physical modelling) but with a metallic material, as tin. This prototype could be used as an example of extrusion equipment to be reproducible in metal forming laboratories of other universities.
A methodology for early detection of potentially low-achievement students by means of online testing and Item Response Theory
Authors: Blanco D , Sánchez F , Álvarez B J , Fernández P , Beltrán N
Published: October 2021

There is an increasing concern about the relevance of reducing university dropout, since the available information shows how dropout reaches surprisingly high values. Additionally, the particular dynamics of university courses makes it difficult to identify students that are prone to fail the course. Present work proposes a methodology to implement an early detection of students in risk of failure, based on the Item Response Theory (IRT) analysis of data collected from online tests. Questions are presented to the students according to knowledge campaigns within the frame of the course by means of an online knowledge management platform (ZAPIENS). Results from student´s performance are processed using IRT to obtain the value of ability for each individual. This information is later used to identify those students that, with high probability, would fail the subject. Students would be grouped according to a Homogeneous Cluster Strategy into different ability levels. Accordingly, faculty would be capable of implementing specific reinforcement strategies. Results indicate that the methodology allows for an appropriate segmentation of the students according to their capability at an early stage. This strategy could help in the development of differential learning itineraries and could also be easily adapted to different educational environments.
Effect of cold rolling and ageing treatment on the interface morphology and mechanical properties of maraging steel/medium-entropy alloy multilayer composite
Authors: Liu Baoxi , Li Zhuoyu , Chen Cuixin , Guo Weibing , Yang Bingchen , Yang Bo , Liu Kailun , Ge Yifei , Yin Fuxing
Published: October 2021

The cold rolling and subsequent ageing treatment of hot-rolled 18Ni300/CoCrNi multilayer composites were carried out to analyse the high work hardening ability of medium-entropy alloy (CoCrNi alloy) and the ageing precipitate strengthening effect of maraging steel (18Ni300). The results show that with the rise of cold rolling reduction, the ratio constitute layer and interface transition layer thicknesses are gradually decreased, and the interface shape changes from a flat to a wavy state, which is mainly due to the serious work hardening of the CoCrNi layer. Meanwhile, the tensile strength continuously increased. When the multilayer composite is cold-rolled to 0.5 mm, its tensile strength reaches more than 2 GPa, and the fracture elongation remains at approximately 7%. After ageing, the superior tensile strength is as high as 2825 MPa, which is attributed to the synergistic effect of work hardening, precipitation strengthening and strong interface bonding strengthening.
Chemical and biological studies of natural and synthetic products for the highly selective control of pest insect species
Authors: Matsuda Kazuhiko
Published: October 2021

Tanacetum cinerariifolium was known to produce pyrethrins, but the mechanism of pyrethrin biosynthesis was largely unclear. The author showed that the nonmevalonate and oxylipin pathways underlie biosynthesis of the acid and alcohol moieties, respectively, and a GDSL lipase joins the products of these pathways. A blend of the green leaf volatiles and (E)-β-farnesene mediates the induction of wounding responses to neighboring intact conspecies by enhancing pyrethrin biosynthesis. Plants fight against herbivores underground as well as aboveground, and, in soy pulps, some fungi produce compounds selectively modulating ion channels in insect nervous system. The author proposed that indirect defense of plants occurs where microorganisms produce defense substances in the rhizosphere. Broad-spectrum pesticides, including neonicotinoids, may affect nontarget organisms. The author discovered cofactors enabling functional expression of insect nicotinic acetylcholine receptors (nAChRs). This led to understanding the mechanism of insect nAChR–neonicotinoid interactions, thus paving new avenues for controlling crop pests and disease vectors.
Computational anti-COVID-19 drug design: progress and challenges
Authors: Wang Jinxian , Zhang Ying , Nie Wenjuan , Luo Yi , Deng Lei
Published: October 2021

Vaccines have made gratifying progress in preventing the 2019 coronavirus disease (COVID-19) pandemic. However, the emergence of variants, especially the latest delta variant, has brought considerable challenges to human health. Hence, the development of robust therapeutic approaches, such as anti-COVID-19 drug design, could aid in managing the pandemic more efficiently. Some drug design strategies have been successfully applied during the COVID-19 pandemic to create and validate related lead drugs. The computational drug design methods used for COVID-19 can be roughly divided into (i) structure-based approaches and (ii) artificial intelligence (AI)-based approaches. Structure-based approaches investigate different molecular fragments and functional groups through lead drugs and apply relevant tools to produce antiviral drugs. AI-based approaches usually use end-to-end learning to explore a larger biochemical space to design antiviral drugs. This review provides an overview of the two design strategies of anti-COVID-19 drugs, the advantages and disadvantages of these strategies and discussions of future developments.
Multiomics integration-based molecular characterizations of COVID-19
Authors: Li Chuan-Xing , Gao Jing , Zhang Zicheng , Chen Lu , Li Xun , Zhou Meng , Wheelock Åsa M
Published: October 2021

The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), rapidly became a global health challenge, leading to unprecedented social and economic consequences. The mechanisms behind the pathogenesis of SARS-CoV-2 are both unique and complex. Omics-scale studies are emerging rapidly and offer a tremendous potential to unravel the puzzle of SARS-CoV-2 pathobiology, as well as moving forward with diagnostics, potential drug targets, risk stratification, therapeutic responses, vaccine development and therapeutic innovation. This review summarizes various aspects of understanding multiomics integration-based molecular characterizations of COVID-19, which to date include the integration of transcriptomics, proteomics, genomics, lipidomics, immunomics and metabolomics to explore virus targets and developing suitable therapeutic solutions through systems biology tools. Furthermore, this review also covers an abridgment of omics investigations related to disease pathogenesis and virulence, the role of host genetic variation and a broad array of immune and inflammatory phenotypes contributing to understanding COVID-19 traits. Insights into this review, which combines existing strategies and multiomics integration profiling, may help further advance our knowledge of COVID-19.
Combining power of different methods to detect associations in large data sets
Authors: Li He , Zhang Hangxiao , Jiang Hangjin
Published: October 2021

Exploring the relationship between factors of interest is a fundamental step for further analysis on various scientific problems such as understanding the genetic mechanism underlying specific disease, brain functional connectivity analysis. There are many methods proposed for association analysis and each has its own advantages, but none of them is suitable for all kinds of situations. This brings difficulties and confusions to practitioner on which one to use when facing a real problem. In this paper, we propose to combine power of different methods to detect associations in large data sets. It goes as combining the weaker to be stronger. Numerical results from simulation study and real data applications show that our new framework is powerful. Importantly, the framework can also be applied to other problems. Availability: The R script is available at https://jiangdata.github.io/resources/DM.zip
Historical controls in clinical trials: a note on linking Pocock’s model with the robust mixture priors
Authors: Callegaro Andrea , Galwey Nicholas , Abellan Juan J
Published: October 2021

Several Bayesian methods have been proposed to borrow information dynamically from historical controls in clinical trials. In this note, we identify key features of the relationship between the first method proposed, the bias–variance method, which is strongly related to the commensurate prior approach, and a more recent and widely used approach called robust mixture priors (RMP). We focus on the two key terms that need to be chosen to define the RMP, namely $w$, the prior probability that the new trial differs systematically from the historical trial, and $s_v^2$, the variance of the vague component of the RMP. The relationship with Pocock’s prior reveals that different combinations of these two terms can express similar prior beliefs about the amount of information provided by the historical data. This demonstrates the value of fixing $s_v^2$, e.g., so the vague component is “worth one subject.” Prior belief about the relevance of the historical data is then driven by a single value, the prespecified weight $w$.
Increased scale-free and aperiodic neural activity during sensorimotor integration—a novel facet in Tourette syndrome
Authors: Adelhöfer Nico , Paulus Theresa , Mückschel Moritz , Bäumer Tobias , Bluschke Annet , Takacs Adam , Tóth-Fáber Eszter , Tárnok Zsanett , Roessner Veit , Weissbach Anne , Münchau Alexander , Beste Christian
Published: October 2021

Tourette syndrome is a common neurodevelopmental disorder defined by multiple motor and phonic tics. Tics in Tourette syndrome resemble spontaneously occurring movements in healthy controls and are therefore sometimes difficult to distinguish from these. Tics may in fact be mis-interpreted as a meaningful action, i.e. a signal with social content, whereas they lack such information and could be conceived a surplus of action or ‘motor noise’. These and other considerations have led to a ‘neural noise account’ of Tourette syndrome suggesting that the processing of neural noise and adaptation of the signal-to-noise ratio during information processing is relevant for the understanding of Tourette syndrome. So far, there is no direct evidence for this. Here, we tested the ‘neural noise account’ examining 1/f noise, also called scale-free neural activity as well as aperiodic activity, in n = 74 children, adolescents and adults with Tourette syndrome and n = 74 healthy controls during task performance using EEG data recorded during a sensorimotor integration task. In keeping with results of a previous study in adults with Tourette syndrome, behavioural data confirmed that sensorimotor integration was also stronger in this larger Tourette syndrome cohort underscoring the relevance of perceptual-action processes in this disorder. More importantly, we show that 1/f noise and aperiodic activity during sensorimotor processing is increased in patients with Tourette syndrome supporting the ‘neural noise account’. This implies that asynchronous/aperiodic neural activity during sensorimotor integration is stronger in patients with Tourette syndrome compared to healthy controls, which is probably related to abnormalities of GABAergic and dopaminergic transmission in these patients. Differences in 1/f noise and aperiodic activity between patients with Tourette syndrome and healthy controls were driven by high-frequency oscillations and not lower-frequency activity currently discussed to be important in the pathophysiology of tics. This and the fact that Bayesian statistics showed that there is evidence for the absence of a correlation between neural noise and clinical measures of tics, suggest that increased 1/f noise and aperiodic activity are not directly related to tics but rather represents a novel facet of Tourette syndrome.
Aphid Species and Feeding Location on Canola Influences the Impact of Glucosinolates on a Native Lady Beetle Predator
Authors: Cibils-Stewart Ximena , Kliebenstein Daniel J , Li Baohua , Giles Kristopher , McCornack Brian P , Nechols James
Published: October 2021

Aphids that attack canola (Brassica napus L.) exhibit feeding preferences for different parts of canola plants, which may be associated with brassica-specific glucosinolates. However, this idea remains untested. Furthermore, canola aphid species employ different strategies for tolerating glucosinolates. While the green peach aphid, Myzus persicae (Sulzer) (Hemiptera: Aphididae), excretes glucosinolates, the cabbage aphid Brevicoryne brassicae (L.) (Hemiptera: Aphididae) sequesters them. Given the different detoxification mechanisms, we predicted that both aphid species and aphid feeding location would affect prey suitability for larvae of the predator, Hippodamia convergens (Guérin-Méneville) (Coleoptera: Coccinellidae). We hypothesized that aphids, specifically glucosinolate-sequestering cabbage aphid, reared on reproductive structures that harbor higher glucosinolates concentrations would have greater negative effects on predators than those reared on vegetative structures which have lower levels of glucosinolates, and that the impact of aphid feeding location would vary depending on the prey detoxification mechanism. To test these predictions, we conducted experiments to compare 1) glucosinolates profiles between B. brassicae and M. persicae reared on reproductive and vegetative canola structures, 2) aphid population growth on each structure, and 3) their subsequent impact on fitness traits of H. convergens. Results indicate that the population growth of both aphids was greater on reproductive structures, with B. brassicae having the highest population growth. B. brassicae reared on reproductive structures had the highest concentrations of glucosinolates, and the greatest adverse effects on H. convergens. These findings suggest that both aphid-prey species and feeding location on canola could influence populations of this predator and, thus, its potential for biological control of canola aphids.
Trends in aortic valve replacement for aortic stenosis: a French nationwide study
Authors: Nguyen Virginia , Willner Nadav , Eltchaninoff Helene , Burwash Ian G , Michel Morgane , Durand Eric , Gilard Martine , Dindorf Christel , Iung Bernard , Cribier Alain , Vahanian Alec , Chevreul Karine , Messika-Zeitoun David
Published: October 2021

Aims

Transcatheter aortic valve replacement (TAVR) as an alternative to surgical aortic valve replacement (SAVR) has profoundly changed the management of patients with aortic valve stenosis (AS). Large unbiased nationwide data regarding TAVR implementation, impact on SAVR and their respective outcomes are scarce.

Methods and results

Based on a French administrative hospital-discharge database, we collected data on all consecutive aortic valve replacements (AVRs) performed in France for AS between 2007 and 2019 [106 253 isolated SAVR (49%), 46 514 combined SAVR (21%), and 65 651 TAVR (30%)]. The number of AVR linearly increased between 2007 and 2019 (from 10 892 to 23 109, P for trend < 0.0001) due to a marked increase in TAVR (from 253 to 13 030, P for trend < 0.0001), while SAVR increased up to 2013 and then declined (10 892 in 2007, 12 699 in 2013, and 10 079 in 2019). The Charlson index decreased linearly for TAVR, but in two steps for SAVR (2011 and 2017). In-hospital mortality rates of both SAVR and TAVR declined (both P for trend < 0.0001) and were similar or lower for TAVR than for isolated SAVR in patients 75 years or above in the last 3 years (2017–19). Complication rates of TAVR also declined but permanent pacemaker rates remained high and length of stay substantial (16.7% and median 6 days, respectively, in 2017–19).

Conclusion

The number of AVR has doubled in a decade and TAVR has become the dominant form of AVR in 2018. The improvement in patient profiles seems to have anticipated the demonstrated benefit of TAVR in intermediate and low-risk patients. In patients 75 years or older, TAVR should be considered as the first option. We also highlight two important areas for improvement, the high permanent pacemaker rates, and the long length of stay even in the contemporary era. Our results may have major implications for clinical practice and policymakers.
Tracing the Evolution of Human Gene Regulation and Its Association with Shifts in Environment
Authors: Colbran Laura L , Johnson Maya R , Mathieson Iain , Capra John A
Published: October 2021

As humans populated the world, they adapted to many varying environmental factors, including climate, diet, and pathogens. Because many of these adaptations were mediated by multiple noncoding variants with small effects on gene regulation, it has been difficult to link genomic signals of selection to specific genes, and to describe the regulatory response to selection. To overcome this challenge, we adapted PrediXcan, a machine learning method for imputing gene regulation from genotype data, to analyze low-coverage ancient human DNA (aDNA). First, we used simulated genomes to benchmark strategies for adapting PrediXcan to increase robustness to incomplete data. Applying the resulting models to 490 ancient Eurasians, we found that genes with the strongest divergent regulation among ancient populations with hunter-gatherer, pastoralist, and agricultural lifestyles are enriched for metabolic and immune functions. Next, we explored the contribution of divergent gene regulation to two traits with strong evidence of recent adaptation: dietary metabolism and skin pigmentation. We found enrichment for divergent regulation among genes proposed to be involved in diet-related local adaptation, and the predicted effects on regulation often suggest explanations for known signals of selection, for example, at FADS1, GPX1, and LEPR. In contrast, skin pigmentation genes show little regulatory change over a 38,000-year time series of 2,999 ancient Europeans, suggesting that adaptation mainly involved large-effect coding variants. This work demonstrates that combining aDNA with present-day genomes is informative about the biological differences among ancient populations, the role of gene regulation in adaptation, and the relationship between genetic diversity and complex traits.