bluuebunny/crossref_metadata_2025 huggingface dataset:
Some Quantitative Analogies Between Large-Strain Plasticity and Rectilinear Fluid Flow
Authors: Gupta Deepika , Udupa Anirudh , Viswanathan Koushik
Published: January 2021

The mechanics of chip formation involves a complex interplay between surface plastic flow, material microstructure and tool-chip interface dynamics. At the continuum scale, this process has often been approximated as being one of pure shear along a very narrow zone — the shear plane. The primary assumption behind this approximation is that of steady or time-independent plastic flow. This approximation addresses the exception rather than the rule, since most metal cutting processes involve unsteady time-dependent plastic flows. In this work, we attempt to develop parallels with an analogous problem in fluid mechanics — flow past a rigid fixed body — to quantify the unsteady nature of plastic flow. Here the role of the body is played by the tool, and the flow field corresponds to the plastically deforming material. The prerequisite for fully exploiting this kinematic analogy is full-field material flow measurements. This is provided by digital image correlation (DIC), a family of techniques that use in situ imaging of the cutting process to obtain instantaneous full-field material displacements. Given this kinematic flow information, we show how one can describe the cutting process more accurately using the fluid flow analogy, and without having to resort to specific preconceived models. For steady flows, the analogy is more than merely cosmetic — the pathlines, streamlines and streaklines, all determined kinematically, coincide exactly. The analogy also allows consideration of time-dependent unsteady plastic flows that are usually beyond the purview of theoretical analyses. One can, for instance, ask the question of whether the transition from steady to unsteady plastic flow observed in metal cutting can be described by a dimensionless parameter, analogous to the Reynolds number for fluids. We show that in the case of unsteady flows, the actual deformation field is far removed from that described by conventional shear plane or slip line field models. Now the streaklines develop undulations or folds for the same boundary conditions as for the steady case (cutting velocity, depth of cut). Of the three flow lines, we attempt to extract information from streaklines, since they contain information about both spatial and temporal gradient. We present analyses of these streakline curvature features using simple geometric techniques that reflect both the spatial and temporal flow evolution. Our results shed light on the importance of considering unsteady flows in chip formation and machining. Borrowing ideas from fluids to describe these flows appears to hold significant promise for quantifying unsteady flows and their consequences for practical machining operations.
On the Formation of Spherical Particles in Surface Grinding
Authors: Dhami Harish Singh , Viswanathan Koushik
Published: January 2021

Grinding swarf is conventionally of secondary interest to the process engineer. However, it has long been recognized that it is a useful indicator of process performance — the exact particle morphologies occurring in the swarf contain a wealth of information about the abrasive-workpiece interaction mechanics. In this work, we study the generation of perfectly spherical particles when grinding two plain carbon steels and a grade of stainless steel with an alumina wheel. Similar particles have also been reported in the wear community and several possible formation mechanisms have been discussed including chip curl resulting from electronic charge distributions; melting due to local flash temperatures in the grinding zone; and repeated abrasive wear of the workpiece surface. We postulate that the particles are likely formed as a result of an oxidation-melting-solidification route with small grinding chips. We present spectroscopy and X-ray diffraction data in support of this hypothesis — significant oxygen content, in the form of Fe3O4 was detected on the surface of the spheres. Electron micrographs also show remarkably robust dendrite-like structures on the surface of the particles, indicative of rapid solidification from the melt. Motivated by these results, we present model calculations to support our hypothesis. We first evaluate the initial temperature of chips exiting the grinding zone using a three-way heat partition model for dry grinding. An upper bound for the chip temperature is ∼ 600°C, well-below the melting point for the metal. Next, we show that the oxidation kinetics at this elevated temperature are such that the formation of a thin oxide layer (∼ 2μm) on the surface of an initially curled up chip, with size ∼ 50 μm comparable to the observed spheres, is enough to melt the entire chip on a timescale of 10−6 seconds. Surface tension then brings the molten chip into a perfectly spherical shape, followed by rapid solidification. We present a preliminary calculation of this solidification process, using a coupled heat conduction model along with a moving interphase interface. By making suitable approximations, we derive an ordinary differential equation describing the temporal evolution of the interface location. Coupling the interface velocity with a Mullins-Sekerka type instability analysis, we argue that solidification of these drops likely starts from a nucleated core in the drop interior, resulting in dendrite-type patterns on the outer surface. Our work is a preliminary attempt to put decades old observations of grinding swarf on a firm quantitative footing. The experimental evidence and related analysis presented here make a strong case for the oxidation-melting-solidification hypothesis for the formation of spherical particles in grinding swarf.
Non-Contact, Continuous, Synchronized, Cosine Error-Free Thickness Profile Measurement by Surface Metrology Tool Path Planning
Authors: Guo Xiangyu , Lee Chabum
Published: January 2021

This paper represents the development of a synchronous thickness profile measurement system that measures double-sided thin pipe wall surfaces in a non-contact, continuous, cosine error-free and fast manner (NCCCE-Fast double-side thickness profiles measurement). A pair of capacitive type sensors (CS) placed on the rotary and linear axes scan the inner and outer surfaces of the thin wall. Surface metrology tool path is developed to align the displacement sensors always normal to the double-sided surfaces simultaneously. Because the rotary axis’s rotational error can badly affect thin wall thickness profile measurement accuracy, such error is initially characterized by a reversal method and was compensated for along the rotational direction while measuring the sample. Two measurement target samples (round/oval metal pipe-type thin walls) are prepared. Not only inner/outer surface profiles but also thin wall thickness profiles are obtained. Based on the output data, the circularity and ovality can be calculated, and those results are compared with those obtained by a contact type micrometer at every 6 degrees interval. As a result, the developed thin wall thickness profilometer can provide high precision results, continuous and fast thickness profile scanning and data are acquired for visualization.
Hexamethylenetetramine Levels Effect Over the Young’s Modulus in Abrasive Materials
Authors: Amaral Emanuelle Machado , Bottairi Raphael Schweiger Freitas , Candioto Katia Cristiane Gandolpho
Published: January 2021

Abrasive composites are very important, since they are widely used in industrial machining processes, responsible for both fine and rough grinding of the work material. For this reason, there is great interest in the research of materials for abrasive wheels, since advances in this area are restricted to the industries, without disclosure to the academic community. This study aims to compare the Young’s modulus and the Impact strength of the produced materials, parameter that can be related to the material’s hardness, thus defining its applicability. The abrasive materials produced are defined by a structure containing 46% vol. of aluminum oxide grain (mesh #46), 22% vol. of phenolic resin binders with different levels of hexamethylenetetramine (14.55% and 8.97%), curing agent responsible for the crosslinking of the resins and 32% vol. of pores. The materials were mixed and pressed at room temperature, and the curing process happened at 60°C/6h, 80°C/8h and 160°C/4h. The Young’s modulus were determined by non-destructive testing using the impulse excitation technique and the results obtained were compared to those obtained by the dynamic mechanical analysis. The abrasive composite materials produced from the mixture with higher hexamethylenetetramine content presented greater Young’s modulus and greater rigidity as demonstrated by the impact strength too, which should be associated with the influence of its content in the composition. The use of a resin with a higher content of this agent for the production of abrasive wheels will result in a higher stiffness tool compared to tools that do not use excess hexamethylenetetramine.
A Broad Transfer Learning Algorithm for Classification of Bearing Faults
Authors: Liu Guokai , Gao Liang , Shen Weiming , Kusiak Andrew
Published: January 2021

Condition monitoring and fault diagnosis are of great interest to the manufacturing industry. Deep learning algorithms have shown promising results in equipment prognostics and health management. However, their success has been hindered by excessive training time. In addition, deep learning algorithms face the domain adaptation dilemma encountered in dynamic application environments. The emerging concept of broad learning addresses the training time and the domain adaptation issue. In this paper, a broad transfer learning algorithm is proposed for the classification of bearing faults. Data of the same frequency is used to construct one- and two-dimensional training data sets to analyze performance of the broad transfer and deep learning algorithms. A broad learning algorithm contains two main layers, an augmented feature layer and a classification layer. The broad learning algorithm with a sparse auto-encoder is employed to extract features. The optimal solution of a redefined cost function with a limited sample size to ten per class in the target domain offers the classifier of broad learning domain adaptation capability. The effectiveness of the proposed algorithm has been demonstrated on a benchmark dataset. Computational experiments have demonstrated superior efficiency and accuracy of the proposed algorithm over the deep learning algorithms tested.
An Exposition of Recently Standardized Classifications of Information for Organizing Model-Based Definitions
Authors: Hedberg Thomas , Barnard Feeney Allison , Srinivasan Vijay
Published: January 2021

ASME has published a new standard (ASME Y14.47) on model-based definition (MBD) organization practices. It is part of ASME’s series of standards on engineering product definition and related documentation practices. ASME Y14.47 introduces novel MBD-element classifications, which are based on industrial recommended practices in organizing and managing three-dimensional geometric models and related information of products. Such classifications form the technical basis for developing information models (e.g., as XML schema definitions) to enable interoperability among engineering information systems in model-based enterprises (MBEs). This paper provides an exposition of these classifications, while emphasizing the need and use of such standardized classifications in modern MBEs.
Laser-Induced Nanocarbon Formation for Tuning Surface Properties of Commercial Polymers
Authors: Abdulhafez Moataz , McComb Angela J. , Bedewy Mostafa
Published: January 2021

The growth of laser-induced nanocarbons, referred to here are LINC for short, directly on polymeric surfaces is a promising route toward surface engineering of commercial polymers. This paper aims to demonstrate how this new approach can enable achieving varied surface properties based on tuning the nanostructured morphology of the formed graphitic material on commercial polyimide (Kapton) films. We elucidate the effects of tuning laser processing parameters on the achieved nanoscale morphology and the resulting surface hydrophobicity or hydrophilicity. Our results show that by varying lasing power, rastering speed, laser spot size, and line-to-line gap sizes, a wide range of water contact angles are possible, i.e. from below 20° to above 110°. Combining water contact angle measurements from an optical tensiometer with LINC surface characterization using optical microscopy, electron microscopy, and Raman spectroscopy enables building the process-structure-property relationship. Our findings reveal that both the value of contact angle and the anisotropic wetting behavior of LINC on polyimide are dependent on their hierarchical surface nanostructure which ranges for isotropic nanoporous morphology to fibrous morphology. Results also show that increasing gap sizes lead to an increase in contact angles and thus an increase in the hydrophobicity of the surface. Hence, our work highlight the potential of this approach for manufacturing flexible devices with tailored surfaces.
Study of Mechanical Properties of Friction Stir Welded Armour Grade Aluminium Alloy Plates
Authors: Singh Umesh Kumar , Dubey Avanish Kumar
Published: January 2021

In present research work, friction stir welding of armour grade aluminium alloy, which is having excellent strength to weight ratio, has been done at low heat input rate (rotational speed of 600 rpm, travelling speed of 75 mm/min) and tool tilt angle of 2.5°. Tungsten carbide tool with a shoulder diameter of 15 mm was used to produce the joint. Tensile strength and microhardness of welded sample were measured at three different locations i.e. at the start, middle and end of the weld. The lowest value of tensile strength was obtained at the start of the weld while the maximum tensile strength was observed at middle of the weld and having the value of 378.672 MPa which is 82.32% of base metal along with 15.26% elongation. There is a large gap between the lower and the maximum value of tensile strength. The middle of the weld has less fluctuation in microhardness value as compared to the start and end of the weld. While the maximum value of microhardness was obtained on the advancing side at the start of the weld with the value of 187.4 Hv. Microstructural image shows the presence of craters and segregation in the weld surface. XRD result signify the presence of intermetallic compound Al12Mg17 in the welded zone.
Experimental Study of Micromachining on Reflective Surface Using CO2 Laser
Authors: Posa Vishnu Vardhan , Sundaram Murali
Published: January 2021

Laser Beam Machining (LBM) is one of the versatile non-traditional manufacturing processes. Material removal in LBM is based on high heat flux generated by laser beam which melts and vaporizes the workpiece material in the focused point. Laser Beam Machining process can shape almost all range of engineering materials from metallic alloys to non-metallic alloys as well as composite materials. But one of the main limitations of laser beam machining is the machining of reflective materials. When laser beam is focused on the reflective surface, part of the energy is reflected by the surface and the remaining is absorbed. In this study, an attempt has been made to increase the absorptivity of the reflective material by coating anti-reflective coating on the surface of the material. Glass has been used as reflective material in this study because of its extensive applications in the micro-opto-electro-mechanical systems. The optimal machining depends on both laser parameters and properties of the workpiece material. There are number of laser parameters that can be varied in the laser machining process. It is difficult to find optimal laser parameters due to mutual interaction of laser parameters. A statistical study based on design of experiment (DoE) has been made to study the effect of anti-reflective coating and parameters like laser power, laser scanning speed, angle of inclination of the workpiece on depth of the slot, width of the slot, aspect ratio and material removal rate (MRR) in the laser machining process using 2k factorial design and ANOVA. On an average 4 times increase in depth of the slot, 2 times increase in width of the slot and 7 times increase in the MRR was observed in the glass work samples with anti-reflective coating when compared to glass work samples without anti-reflective coating.
Knowledge Graph-Based Manufacturing Capability Service Optimal Selection for Industrial Cloud Robotics
Authors: Ma Yanping , Xu Wenjun , Tian Sisi , Liu Jiayi , Yao Bitao , Hu Yang , Feng Hao
Published: January 2021

As an important part of Cloud Manufacturing (CMfg), Industrial Cloud Robotics (ICRs) encapsulates manufacturing capability of physical industrial robots as services for the users. However, a growing number of functionally equivalent services appear in CMfg platform due to the wide use of industrial robots in manufacturing field. It is important to carry out Manufacturing Capability Service (MCS) optimal selection for ICRs from various optional services under CMfg environment. But current service optimal selection method emphasizes on the non-function information of services, and it ignores the interactive relationships between different services and the basic function information of services, which make it difficult to satisfy the various personalized demands of users. Service optimal selection requires the integration and sharing of manufacturing knowledge. Knowledge graph provides an effective way to express and manage knowledge. And it can provide decision support for users to select appropriate ICRs service. Therefore, this paper proposes a method of knowledge graph-based manufacturing capability service optimal selection for ICRs. The function information, association information and non-function information of MCS are described based on knowledge graph. Based on this, the service optimal selection procedure is proposed to realize smart MCS optimal selection for ICRs, which includes feature selection, association selection and user custom weights of non-function indices selection. Finally, a case study based on robotic assembly is presented to demonstrate the effectiveness of proposed method.
Fundamental Process Mechanics Common to Machining and Grinding Operations
Authors: Lortz Wolfgang , Pavel Radu
Published: January 2021

All different production processes have one thing in common: in each case a workpiece with characteristic material behavior, stress, strain, self-hardening and temperature will be produced by a tool with special geometry and individual kinematic conditions, with a wide range of energy in a designed machine tool which is working along programmed lines. For the workpiece material, it is not important from which machine the energy is coming. To be able to predict more accurate values of the production process, it will be necessary to focus more on the complex and difficult process mechanics. The result must have a strong physical base and be in good agreement with practical results To solve these problems, we have to uncover all previous simplification assumptions for the existing models. This leads in a first step to a new fundament in process mechanics, which is only based on mathematics, physics and material behavior with friction conditions, and resulting temperatures during metal plastic flow. The new mathematical equations developed for yield shear stress and strain rate will be presented and discussed in this paper. The plastic deformation is the only parameter that will not disappear after completing the operation. Therefore, this will be the base to compare the developed theoretical deformation with the experimental results for two operations: cutting and grinding. In addition, it could be shown that yield shear stress and corresponding strain rate versus temperatures have an interdependent relationship, which creates the opportunity to determine the temperatures during metal plastic flow.
Intense Pulse Light Annealing for Perovskite Photovoltaics
Authors: Ghahremani Amir H. , Druffel Thad
Published: January 2021

Rapid advancements within photovoltaics realm necessitates swift fabrication of the modules using cheap materials through cost effective manufacturing processes to achieve short cost payback time. Photovoltaics manufacturing includes chemical processing of the materials followed by thermal annealing. Yet, long-term annealing of the materials using high temperature furnaces have remained the prevalent post-processing approach in industry which necessitates alternative methods to achieve high performance modules through rapid and economical processes. Intense pulse light (IPL) has been successfully applied as a promising rapid post-process annealing for various thin film photovoltaics, particularly to process the organic-inorganic perovskite solar cell (PSC) layers. In this paper, several results pertinent to the application of IPL on perovskite and SnO2 electron transport thin films are presented and the role of IPL on rapid thermal annealing (RTA) is explained. We show that swift fabrication of PSCs through IPL can result in efficiencies exceeding 16% when the Perovskite film is annealed with aid of CH2I2 alkyl halide additive in the ambient with 60% relative humidity. In addition, the synergy of IPL-alkyl halide interaction for other perovskite chemistries is introduced. We show that achieving to PSCs exceeding 12% efficiency was possible when the perovskite and SnO2 ETL was annealed sequentially through IPL.
Review of Surface Finishing of Additively Manufactured Metal Implants
Authors: Fashanu Felicia F. , Marcellin-Little Denis J. , Linke Barbara S.
Published: January 2021

Metal additive manufacturing (AM) technologies, commonly referred to as 3D printing, provide a good prospect for medical applications because complex geometries and customized parts can be fabricated to meet individual patient needs. Orthopedic implants are a group of medical parts with high relevance for AM. This paper discusses relevant AM technologies, several orthopedic applications, materials and material properties, mechanical surface finishing techniques, and measurement techniques from the literature. Today, most metal 3D printed implants are manufactured through metal powder bed fusion technology which includes direct metal laser sintering (DMLS), selective laser melting (SLM), and electron beam melting (EBM). Common materials include titanium alloys, cobalt chromium (CoCr) and stainless steel, chosen because of their biocompatibility and mechanical properties. Surface finishing is most often required for 3D printed implants due to the relatively poor surface quality to meet the desired surface texture for the application. Typically, postprocessing is done mechanically, including manual and automated grinding, sandblasting, polishing, or chemically, including electrochemical polishing. This review also covers an overview of surface quality characterization of AM metal implants which includes surface texture and topography. The surface parameters used to characterize the surface of the implants: surface roughness (Ra), differences between the peak and valley (Rz), waviness, and micro-finish.
3D Printing of Flexible and Stretchable Parts Using Multiwall Carbon Nanotubes/Polyester-Based Thermoplastic Polyurethane
Authors: Stan Felicia , Stanciu Nicoleta-Violeta , Constantinescu Adriana-Madalina , Fetecau Catalin
Published: January 2021

This paper reports on the 3D printing of flexible and stretchable parts based on multiwall carbon nanotubes (MWCNTs)/polyester-based thermoplastic polyurethane (TPU) nanocomposites. The rheological properties of the MWCNT/TPU nanocomposites with different wt.% of MWCNTs (0.1–3) were determined and used as guidance for the extrusion and 3D printing processes. MWCNT/TPU filaments were extruded and used for 3D printing of different flexible and stretchable parts. The mechanical, electrical, and piezoresistive response of the MWCNT/TPU nanocomposite filaments and 3D printed parts under static and monotonic loading was studied.

The experimental results show that with increasing temperature and shear rate, respectively, the shear viscosity of the MWCNT/TPU nanocomposite decreases, whereas the viscosity increases with increasing wt.% of MWCNTs. With the addition of MWCNTs, the elastic modulus and tensile strength of the feedstock filament all increase, enhancing the printability of TPU by increasing the buckling resistance and the stability of the 3D printed layer. The electrical conductivity of the 3D printed MWCNT/TPU nanocomposites increases with increasing wt.% of MWCNTs and exceeds the conductivity of the filaments. The 3D printed MWCNT/TPU nanocomposites with 3 wt.% show an electrical conductivity about 10 S/m, irrespective of the printing direction. Moreover, the 3D printed MWCNT/TPU nanocomposites exhibit good mechanical properties and high piezoresistive sensitivity with gauge factor (50–600) dependent on both strain and printing direction.
Mechanical and Corrosion Assessment of Friction Self-Piercing Rivet Joint of Carbon Fiber-Reinforced Polymer and Magnesium Alloy AZ31B
Authors: Lim Yong Chae , Chen Jian , Jun Jiheon , Leonard Donovan N. , Brady Michael P. , Warren Charles David , Feng Zhili
Published: January 2021

In the present work, thermoset carbon fiber–reinforced polymer (CFRP) was spot joined to magnesium alloy AZ31B by a friction self-piercing riveting (F-SPR) process. Lap shear tensile and cross-tension testing were used to evaluate the mechanical joint performance. An average lap shear tensile load of 5.18 kN was achieved, while an average of 2.81 kN was found from cross-tension testing. All F-SPR samples showed pull-out of AZ31B after mechanical testing, indicating good mechanical interlocking between the steel rivet and AZ31B. Corrosion potential was measured for each material to establish the galvanic corrosion characteristics. As expected, AZ31B was found to be the most active, while thermoset CFRP was the most noble. The steel rivet fell between the AZ31B (active) and the thermoset CFRP (noble). Salt fog corrosion testing (ASTM B-117) was performed to evaluate the corrosion performance of the uncoated F-SPR joint. With up to 200 h of exposure, the post-corroded F-SPR joint integrity retained 81.2% of the pre-exposure F-SPR joint strength with AZ31B pull-out failure mode. From cross-sectional analysis of the F-SPR joint, extensive corrosion of AZ31B was observed at the joint and other exposure areas. However, steel rivet was not significantly corroded potentially due to sacrificial anode effect by which AZ31B corroded first in the galvanic couple.
Localized Acoustic-Event Measurement Probe: Connector Confirmation Utilizing Acoustic Signatures
Authors: Skoglind Brian , Roberts Travis , Karmakar Sourabh , Turner Cameron , Mears Laine
Published: January 2021

Electrical connections in consumer products are typically made manually rather than through automated assembly systems due to the high variety of connector types and connector positions, and the soft flexible nature of their structures. Manual connections are prone to failure through missed or improper connections in the assembly process and can lead to unexpected downtime and expensive rework. Past approaches for registering connection success such as vision verification or Augmented Reality have shown limited ability to verify correct connection state. However, the feasibility of an acoustic-based verification system for electrical connector confirmation has not been extensively researched. One of the major problems preventing acoustic based verification in a manufacturing or assembly environment is the typically low signal to noise ratio (SNR) between the sound of an electrical connection and the diverse soundscape of the plant. In this study, a physical means of background noise mitigation and signature amplification are investigated in order to increase the SNR between the electrical connection and the plant soundscape in order to improve detection. The concept is that an increase in the SNR will lead to an improvement in the accuracy and robustness of an acoustic event detection and classification system. Digital filtering has been used in the past to deal with low SNRs, however, it runs the risk of filtering out potential important features for classification. A sensor platform is designed to filter out and reduce background noise from the plant without effecting the raw acoustic signal of the electrical connection, and an automated detection algorithm is presented. The solution is over 75% effective at detecting and classifying connections.
Structural Nonlinearity of Robotic Machining Systems
Authors: Mohammadi Yaser , Ahmadi Keivan
Published: January 2021

Excessive and unstable vibrations that are caused by the machining forces are among the most critical problems that limit the use of industrial robots instead of CNC machine tools. Reduction and control of robot’s vibrations during machining require accurate models of the robot’s vibration response to the dynamic forces exerted at the Tool Centre Point (TCP) where the cutting tool interacts with the workpiece material. The existing models of vibrations in robotic machining have been formed by assuming the linearity of the dynamic response at the TCP. In this paper, the accuracy of this assumption is investigated experimentally, and the results show that the dynamic response at the TCP is strongly nonlinear. An experimental procedure is presented to identify the nonlinearities by employing the first-order Frequency Response Functions (FRFs) measured using various input force excitations. Nonlinear Complex Mode Analysis is then used to extract the modal parameters of the system when its dynamics is linearized around a harmonic response with a constant amplitude. The extracted modal parameters strongly depend on the amplitude of the applied force and the resulting vibrations. This study highlights the need for considering the nonlinearities of the structural dynamics of industrial robots in modelling machining vibrations.
Deep Learning-Based Data Fusion Method for In-Situ Porosity Detection in Laser-Based Additive Manufacturing
Authors: Tian Qi , Guo Shenghan , Guo Weihong , Bian Linkan
Published: January 2021

Laser-Based Additive Manufacturing (LBAM) provides unprecedented possibilities to produce complicated parts with multiple functions for lots of engineering applications. Melt pool is one of the most important signatures in LBAM and is indicative of process anomalies and part defects. High-speed temperature images of the melt pool captured during LBAM make it possible for in-situ melt pool monitoring and porosity prediction. This paper aims to broaden current knowledge of the underlying relationship between process and porosity in LBAM and provide new possibilities for efficient and accurate porosity prediction. We present a deep learning-based data fusion method to predict porosity in LBAM parts by leveraging the measured melt pool thermal history and deep learning. A PyroNet, based on Convolutional Neural Networks, is developed to correlate in-process pyrometer images with layer-wise porosity; an IRNet, based on Long-term Recurrent Convolutional Networks, is developed to correlate sequential thermal images from infrared camera with layer-wise porosity. Predictions from PyroNet and IRNet are fused at the decision level to obtain a more accurate prediction of layer-wise porosity. The model fidelity is validated with LBAM Ti-6Al-4V thin-wall structure. Our method can achieve 100% accuracy with high efficiency, allowing the method to be applicable for in-situ porosity detection in LBAM.
A Novel Edge Computing Based Architecture for Intelligent Tool Condition Monitoring
Authors: Liu Rui
Published: January 2021

Edge computing has been recognized as a potential solution to enable intelligent manufacturing in the machining industry, especially for the small and medium-sized manufacturers. However, while various research studies have proposed their edge-based architectures for intelligent systems, there still exists a lack of practical and affordable technological plans that can be applied to complex machining process designs in actual production scenario. The objective of this research is to realize the tool condition monitoring (TCM) in machining by the edge computing based architecture for actual mass production. This study creatively proposes a calibration-based TCM system to monitor the cutting tool conditions in repetitive machining operations by comparing the characteristic signals generated by the reference cutting tools in the calibration procedure with the signal generated by the cutting tool in production through a concise similarity analysis, which can be easily integrated into typical cyber-psychical systems to realize the edge computing in a very efficient and flexible way. To validate the performance of the proposed architecture, a case study is demonstrated for tool wear monitoring of repetitive milling operations with a complex machining process design. Experimental validation has shown that the proposed edge-based TCM system can effectively monitor the tool wear progression which is in good agreement with actual wear measurements.
Two new species of the genus Raphignathus (Acari: Raphignathidae) from Hamedan, Iran, with a key to the known species

Authors: Pishehvar Shahram , Khanjani Mohammad
Published: January 2021

Two new species of the genus Raphignathus, R. seraji sp. nov. and R. rakhshandehi sp. nov., are described and illustrated based on females collected from soil under Astragalus sp. bushes, along Gamasiab river, Nahavand, Hamedan province, Iran. An updated key to all known species of Raphignathus is given.
New larval host records and locality data for Nuttalliella namaqua Bedford, 1931 (Acari: Nuttalliellidae)

Authors: Apanaskevich Dmitry A.
Published: January 2021

New larval hosts and locality data of an enigmatic tick, Nuttalliella namaqua Bedford, 1931 (Acari: Nuttalliellidae) are recorded. Most of the discovered larvae were found on various species of murid rodents (Rodentia: Muridae), while few larvae were collected on a petromurid rodent (Rodentia: Petromuridae), canid (Carnivora: Canidae), hares (Lagomorpha: Leporidae) and elephant shrew (Macroscelidea: Macroscelididae). Eight species of hosts are new host records for larvae of N. namaqua. This tick species is recorded for the first time from Botswana and Mozambique as well as from new localities in Namibia and South Africa.
Teratological anomalies of an adult Asiatic blue tick, Rhipicephalus microplus (Acari: Ixodidae)

Authors: Diyes Chulantha P. , Rajakaruna Rupika S.
Published: January 2021

While identifying 2, 628 ticks collected from a cross sectional, island-wide survey of ticks infesting goats in Sri Lanka, one Rhipicephalus microplus specimen was found with external teratological anomalies. The observed anomaly was complete absence of right leg IV (ectromély). This is the first known case of teratological changes observed for ticks in Sri Lanka however, such anomaliies have previously been reported for R. microplus.
Multiple screening approaches reveal HDAC6 as a novel regulator of glycolytic metabolism in triple-negative breast cancer
Authors: Dowling Catríona M. , Hollinshead Kate E. R. , Di Grande Alessandra , Pritchard Justin , Zhang Hua , Dillon Eugene T. , Haley Kathryn , Papadopoulos Eleni , Mehta Anita K. , Bleach Rachel , Lindner Andreas U. , Mooney Brian , Düssmann Heiko , O’Connor Darran , Prehn Jochen H. M. , Wynne Kieran , Hemann Michael , Bradner James E. , Kimmelman Alec C. , Guerriero Jennifer L. , Cagney Gerard , Wong Kwok-Kin , Letai Anthony G. , Chonghaile Tríona Ní
Published: January 2021

Discovery of a new HDAC6 inhibitor reveals role for HDAC6 in the regulation of glycolytic metabolism.
Translational and rotational critical-like behaviors in the glass transition of colloidal ellipsoid monolayers
Authors: Zheng Zhongyu , Ni Ran , Wang Yuren , Han Yilong
Published: January 2021

Two critical behaviors in glasses of ellipsoids show thermodynamic and dynamic glass transitions with distinct relaxation.
Metallic line defect in wide-bandgap transparent perovskite BaSnO
3
Authors: Yun Hwanhui , Topsakal Mehmet , Prakash Abhinav , Jalan Bharat , Jeong Jong Seok , Birol Turan , Mkhoyan K. Andre
Published: January 2021

A metallic line defect is found in wide-bandgap perovskite oxide thin films.
Ultrahigh-yield on-surface synthesis and assembly of circumcoronene into a chiral electronic Kagome-honeycomb lattice
Authors: Telychko Mykola , Li Guangwu , Mutombo Pingo , Soler-Polo Diego , Peng Xinnan , Su Jie , Song Shaotang , Koh Ming Joo , Edmonds Mark , Jelínek Pavel , Wu Jishan , Lu Jiong
Published: January 2021

Bottom-up surface-assisted synthesis of circumcoronene self-assembly enables realization of artificial electronic lattice.
Inhibitory signaling sustains a distinct early memory CD8
+
T cell precursor that is resistant to DNA damage
Authors: Johnnidis Jonathan B. , Muroyama Yuki , Ngiow Shin Foong , Chen Zeyu , Manne Sasikanth , Cai Zhangying , Song Shufei , Platt Jesse M. , Schenkel Jason M. , Abdel-Hakeem Mohamed , Beltra Jean-Christophe , Greenplate Allison R. , Ali Mohammed-Alkhatim A. , Nzingha Kito , Giles Josephine R. , Harly Christelle , Attanasio John , Pauken Kristen E. , Bengsch Bertram , Paley Michael A. , Tomov Vesselin T. , Kurachi Makoto , Vignali Dario A. A. , Sharpe Arlene H. , Reiner Steven L. , Bhandoola Avinash , Johnson F. Bradley , Wherry E. John
Published: January 2021

An early memory CD8
+
T cell precursor with distinct genome maintenance capacity depends on inhibitory receptor signaling.
Differential Roles of a Family of Flavodoxin-Like Proteins That Promote Resistance to Quinone-Mediated Oxidative Stress in Candida albicans
Authors: Foderaro Jenna E. , Konopka James B.
Published: January 2021

Survival of the fungal pathogen
Candida albicans
within a mammalian host relies on its ability to resist oxidative stress. The four flavodoxin-like proteins (Pst1, Pst2, Pst3, and Ycp4) that reside on the inner surface of the
C. albicans
plasma membrane represent a recently discovered antioxidant mechanism that is essential for virulence.
Supplemental Material: Late Mesoproterozoic low-P/T–type metamorphism in the North Wulan terrane: Implications for the assembly of Rodinia
Authors: Wang Lu , Chen Nengsong , al. et
Published: January 2021

Table S1: Representative electron microprobe data for minerals of garnet, spinel, biotite, cordierite, feldspar, and amphibole from garnetite (sample WL13-16), pelitic gneiss (sample WL16-27), and quartz schist (sample WL13-12) in the Statherian–Calymmian unit of the North Wulan terrane; Table S2: Monazite U-Pb data for the three analyzed metasedimentary samples in the North Wulan terrane, NW China, and external standard.
Heart rate during the first 24 hours in term-born infants
Authors: Tveiten Lars , Diep Lien My , Halvorsen Thomas , Markestad Trond
Published: January 2021

Objective

Heart rate (HR) is an important clinical parameter in newborn infants, but normal ranges are poorly defined. Our aim was to establish normal reference ranges and individual variations in HR as obtained by auscultation in healthy term-born infants during the first 24 hours of life.

Design

Observational study.

Setting

Single hospital in Norway.

Methods

HR was assessed by auscultation for 30 s at 2, 4, 8, 16 and 24 hours of age. Auscultation was validated against ECG recordings.

Subjects

Healthy term-born infants who were asleep or awake in a quiet resting state.

Main outcome measures

Construction of percentile curves for resting HR.

Results

The study included 953 infants. The 50th percentile was 126 beats per minute (bpm) at age 2 hours and thereafter 120–122 bpm. The respective 2nd and 98th percentiles were 102 (thereafter 96–100) bpm and 162 (thereafter 150–156) bpm. The mean HR was 5.6 bpm higher when awake than asleep, 4.9 bpm higher when on the mother’s chest than in the cot, 1.6 bpm higher in girls than in boys, and increased by 0.5 bpm per 0.1°C increase in rectal temperature. Mode of delivery, meconium staining, birth weight and maternal smoking during pregnancy were of no significance. For each infant, HR varied considerably during the first 24 hours (intraclass correlation 0.21 (95% CI 0.18 to 0.24), coefficient of variation 9.2%).

Conclusions

The HR percentiles allow for a scientifically based use of HR when assessing newborn infants born at term.
Randomised study of heart rate measurement in preterm newborns with ECG plus pulse oximetry versus oximetry alone
Authors: Murphy Madeleine C , Jenkinson Allan , Coveney John , McCarthy Lisa K , O Donnell Colm Patrick Finbarr
Published: January 2021

Aim

To determine whether the IntelliVue monitor (ECG plus Masimo pulse oximeter (PO)) displays heart rate (HR) at birth more quickly than Nellcor PO (PO alone) among infants of 29–35 weeks’ gestational age.

Methods

Unmasked parallel group randomised (1:1) study.

Results

We planned to enrol 100 infants; however, the study was terminated due to the COVID-19 pandemic when 39 infants had been enrolled (17 randomised to IntelliVue, 22 to Nellcor). We found no differences between the groups in the time to first HR display (median (IQR) IntelliVue ECG 49 (33, 71) vs Nellcor 47 (37, 86) s, p>0.999), in the proportion who had a face mask applied for breathing support, or in the time at which it was applied. Infants monitored with IntelliVue were handled more frequently and for longer.

Conclusion

IntelliVue ECG did not display HR more quickly than Nellcor PO in preterm infants. We found no differences in the rate of or time to intervention between groups. Our study was terminated early so these findings should be interpreted with caution.

Trial registration number

ISRCTN16473881
Patients presenting with metastases: stage IV uveal melanoma, an international study
Authors: Garg Gaurav , Finger Paul T , Kivelä Tero T , Simpson E Rand , Gallie Brenda L , Saakyan Svetlana , Amiryan Anush G , Valskiy Vladimir , Chin Kimberly J , Semenova Ekaterina , Seregard Stefan , Filì Maria , Wilson Matthew , Haik Barrett , Caminal Josep Maria , Catala-Mora Jaume , Gutiérrez Cristina , Pelayes David E , Folgar Anibal Martin , Jager Martine Johanna , Doğrusöz Mehmet , Luyten Gregorius P M , Singh Arun D , Suzuki Shigenobu
Published: January 2021

Objective

To analyse ocular and systemic findings of patients presenting with systemic metastasis.

Methods and analysis

It is an international, multicentre, internet-enabled, registry-based retrospective data analysis. Patients were diagnosed between 2001 and 2011. Data included: primary tumour dimensions, extrascleral extension, ciliary body involvement, American Joint Committee on Cancer (AJCC)-tumour, node, metastasis staging, characteristics of metastases.

Results

Of 3610 patients with uveal melanoma, 69 (1.9%; 95% CI 1.5 to 2.4) presented with clinical metastasis (stage IV). These melanomas originated in the iris, ciliary body and choroid in 4%, 16% and 80% of eyes, respectively. Using eighth edition AJCC, 8 (11%), 20 (29%), 24 (35%), and 17 (25%) belonged to AJCC T-categories T1–T4. Risk of synchronous metastases increased from 0.7% (T1) to 1.5% (T2), 2.6% (T3) and 7.9% (T4). Regional lymph node metastases (N1a) were detected in 9 (13%) patients of whom 6 (67%) had extrascleral extension. Stage of systemic metastases (known for 40 (59%) stage IV patients) revealed 14 (35%), 25 (63%) and 1 (2%) had small (M1a), medium-sized (M1b) and large-sized (M1c) metastases, respectively. Location of metastases in stage IV patients were liver (91%), lung (16%), bone (9%), brain (6%), subcutaneous tissue (4%) and others (5%). Multiple sites of metastases were noted in 24%. Compared with the 98.1% of patients who did not present with metastases, those with synchronous metastases had larger intraocular tumours, more frequent extrascleral extension, ciliary body involvement and thus a higher AJCC T-category.

Conclusions

Though higher AJCC T-stage was associated with risk for metastases at diagnosis, even small T1 tumours were stage IV at initial presentation. The liver was the most common site of metastases; however, frequent multiorgan involvement supports initial whole-body staging.
Do ‘pathologic’ cardiac murmurs in adolescents identify structural heart disease? An evaluation of 15 141 active adolescents for conditions that put them at risk of sudden cardiac death
Authors: Austin Ashley V , Owens David S , Prutkin Jordan M , Salerno Jack C , Ko Brian , Pelto Hank F , Rao Ashwin L , Siebert David M , Carrol Jennifer S , Harmon Kimberly G , Drezner Jonathan A
Published: January 2021

Objectives

We assessed whether the presence and character of a cardiac murmur in adolescents were associated with structural heart disease that confers risk of sudden cardiac death (SCD).

Methods

We performed a retrospective analysis of 15 141 adolescents age 12–19 who underwent a heart screen with history, physical examination and ECG. Participants with any screening abnormality underwent an echocardiogram for the assessment of structural heart disease. Murmurs were classified as physiological or pathological according to standard clinical criteria, and participants with murmurs were compared with a comparison group without murmurs. The primary outcome was echocardiogram-detected structural heart disease associated with SCD.

Results

905 participants with a cardiac murmur (mean age 15.8; 58% male) and 4333 participants without a murmur (comparison group; mean age 15.8; 55% male) had an echocardiogram to detect structural heart disease. 743 (82%) murmurs were described as physiological and 162 (18%) as pathological. Twenty-five (2.8%) participants with murmurs and 61 (1.4%) participants without murmurs had structural heart disease. Three (0.3%) participants in the murmur group were diagnosed with hypertrophic cardiomyopathy (HCM) which was the only identified condition associated with SCD. Two participants with HCM had physiological murmurs, one had a pathological murmur, and all three had an abnormal ECG. The most common minor structural heart disease was bicuspid aortic valve in both the murmur (7; 0.8%) and comparison (20; 0.5%) groups. The positive predictive value of physiological versus pathological murmurs for identifying any structural heart disease was 2.4% versus 4.3% (p=0.21), respectively. The positive predictive value of having any murmur versus no murmur for identifying structural heart disease was 2.8% versus 1.4% (p=0.003), respectively.

Conclusions

In adolescents, the traditional classification of cardiac murmurs as ‘physiologic’ or ‘pathologic’ does not differentiate for structural heart disease that puts individuals at risk for SCD. We recommend ECG evaluation in all patients with a cardiac murmur found during preparticipation screening to increase detection of HCM.