bluuebunny/crossref_metadata_2025 huggingface dataset:
Operating System for Cyber-Physical Manufacturing (OSCM): A Flexible Event-Driven Shopfloor Information Platform for Advanced Manufacturing
Authors: Toro Santamaria Ricardo , Ferreira Placid M.
Published: September 2022

Factory technologies have evolved to incorporate a great deal of manufacturing flexibility. Programmable automation in the form of CNC and PLCs along with hardware innovations (quick-change tooling, for example) and various operator assist technologies enable a high level of shop-floor flexibility. Possibly, the most inflexible part of a factory is the manufacturing information system. Customized for manufacturers by system integrators, these systems are often large monolithic systems assembled around an ERP/MRP framework or a precariously integrated set of decision-support software tools with a patchwork of communications enabling information flow between them.

On the other hand, cloud-based information service platforms such as those encountered in social networks and service brokers have seen rapid and multiple cycles of evolution resulting in a meteoric rise in their ability to handle increasingly large data scales and rates, while still maintaining their elasticity and flexibility. This rapid evolution of cloud-based information services has ignited a new era in the manufacturing industry as evidenced by emerging manufacturing cyberphysical system technologies such as the Industrial Internet of Things (IIoT), and Cloud Manufacturing (CM). These technologies are part of the broader context of what is thought to be the unfolding fourth industrial revolution (Industry 4.0 or Digital Manufacturing). This revolution places at its core, connectivity, information, and machine-based intelligence to create a new paradigm for manufacturing that is highly flexible, scalable, responsive, and intelligent.

This paper describes how we leveraged the newest advances in CPS, IIoT, CM, and distributed systems to create a flexible manufacturing information system infrastructure that separates information collection and distribution for decision-making functions. The first part of the paper introduces the architecture for a novel full-stack manufacturing infrastructure that is envisioned to facilitate and track the interaction between a manufacturing job, physical resources, and the software services (or apps) around them. We call this platform the Operating System for Cyber-physical Manufacturing (OSCM). In the second part of the paper, we introduce an event-based architecture for OSCM so that resource or transaction related events/data can be flexibly distributed to different decision-making/manufacturing software tools through an event/message exchange/bus. Further, such an architecture allows modularization and incremental development of different manufacturing software tools and services as new needs are identified.
Unexpectedly High Yields in Chemical Vapor Deposition of Carbon Nanotubes Based on Reactor Wall Thermochemical History
Authors: Tomaraei Golnaz , Abdulhafez Moataz , Bedewy Mostafa
Published: September 2022

While reactor wall preconditioning was previously shown to influence the growth of carbon nanotubes (CNTs) by chemical vapor deposition (CVD), it was previously only limited to studying the accumulating carbon deposits over the history of a large number of growth runs. However, the effect of leaving the reactor walls for an extended period of time between growth runs was not previously systematically studied. Here, we combine experimental measurements with a mathematical model to investigate the effect of thermochemical history of reactor walls on growth yield of vertically aligned CNT forests. Importantly, we demonstrate unexpectedly high CNT yield, exceeding one-order-of-magnitude taller forests, by increasing the interim period between runs (IPBR). We explain the results based on previously unexplored process sensitivity to trace amounts of oxygen-containing species in the reactor. In particular, uncontrolled amounts of water vapor desorbing from reactor walls during growth are modelled in this work. Our modeling results show the effect of IPBR on the outgassing dynamics revealing the underlying mechanism of generating growth promoting molecules during growth. By installing a new humidity sensor in our multizone rapid thermal CVD reactor, we are able to uniquely correlate the amount of moisture within the reactor to real-time measurements of growth kinetics, as well as ex situ characterization of CNT alignment and atomic defects. Our findings enable a scientifically grounded approach toward both boosting growth yield and improving its consistency by reducing run-to-run variations. Accordingly, engineered growth recipes can be envisioned to leverage this effect for improving manufacturing process scalability and robustness.
Thin-Film Nitrate Sensor Performance Prediction Based on Image Analysis and Credibility Data to Enable a Certify As Built Framework
Authors: Wang Xihui , Saha Ajanta , Mi Ye , Shakouri Ali , Ashraful Alam Muhammad , Chiu George T. C. , Allebach Jan P.
Published: September 2022

In the modern industrial setting, there is an increasing demand for all types of sensors. The demand for both the quantity and quality of sensors is increasing annually. Our research focuses on thin-film nitrate sensors in particular, and it seeks to provide a robust method to monitor the quality of the sensors while reducing the cost of production.

We are researching an image-based machine learning method to allow for real-time quality assessment of every sensor in the manufacturing pipeline. It opens up the possibility of real-time production parameter adjustments to enhance sensor performance. This technology has the potential to significantly reduce the cost of quality control and improve sensor quality at the same time. Previous research has proven that the texture of the topical layer (ion-selective membrane (ISM) layer) of the sensor directly correlates with the performance of the sensor. Our method seeks to use the correlation so established to train a learning-based system to predict the performance of any given sensor from a still photo of the sensor active region, i.e. the ISM. This will allow for the real-time assessment of every sensor instead of sample testing. Random sample testing is both costly in time and labor, and therefore, it does not account for all of the individual sensors.

Sensor measurement is a crucial portion of the data collection process. To measure the performance of the sensors, the sensors are taken to a specialized lab to be measured for performance. During the measurement process, noise and error are unavoidable; therefore, we generated credibility data based on the performance data to show the reliability of each sensor performance signal at each sample time.

In this paper, we propose a machine learning based method to predict sensor performance using image features extracted from the non-contact sensor images guided by the credibility data. This will eliminate the need to test every sensor as it is manufactured, which is not practical in a high-speed roll-to-roll setting, thus truely enabling a certify as built framework.
Review of KEI Method-Based Dimensional Measurement, Positioning Control and Part Inspection
Authors: Wang Zhikun , Lee ChaBum
Published: September 2022

We have developed knife-edge interferometry (KEI) for various engineering applications, including displacement measuring sensors for dynamic system controls and edge quality of the parts, such as cutting tools, corrosive blades, and photomask patterns. This paper reviewed the modeling, design, and data analysis of KEI. With the expanding market of manufacturing industries, edge topography and instrumentation technology become more and more vital to industrial manufacturing-related applications such as cutting tool wear inspection, photomask edge roughness determination, and edge corrosion propagation monitoring. Due to the limitation of measurement requirements like non-contact (photomask inspection), in-situ (cutting tool inspection), and real-time (corrosion propagation monitoring), there are only a few methods available in the market above, and those methods are based on post-processing. The KEI is capable of on-machine measurements, especially for the nanopositioning systems, providing a large working range and positioning accuracy compared with the conventional displacement sensor. This review addresses the current and future KEI technology. Here, including the theoretical approaches to KEI, this review details the data analysis method to feature the edge topographical information.
Development and Evaluation of a Computer Vision System for Assembly Bolt Pattern Traceability and Poka-Yoke
Authors: Kozikowski Eric , Hartman Nathan W. , D. Camba Jorge
Published: September 2022

Decisions made based on manufacturing data can help identify key problem areas in an assembly line and mitigate any defects from progressing through to the next step in the assembly process. But what if the products’ “as manufactured” data was inaccurate or did not exist at all? This paper outlines the development and validation of a system for tracking and error-proofing the assembly of bolted joints that require specific torque patterns in an industrial environment. Using a machine vision system, our solution recognizes the type of fastener being used, traces the tool location relative to the mechanical fastener, and records the order in which the fasteners were torqued in. If an error is detected, the system does not allow the user to progress through the assembly process. We leverage open source machine learning algorithms to allow efficient object detection model training. Our solution was validated using a series of tests and evaluated using the STEP method. Results show that the proposed system provides an effective and intuitive human interface for cyber-physical systems and an approach toward the digitalization of human skills needed for product assembly and their utilization in manufacturing.
Analytical Study of Shear-Thinning Fluid Flow in Direct Ink Writing Process
Authors: Guo Zipeng , Fei Fan , Song Xuan , Zhou Chi
Published: September 2022

As a facile and versatile additive manufacturing technology, direct ink writing (DIW) has attracted considerable interest in academia and industry to fabricate three-dimensional structures with unique properties and functionalities. However, so far, the physical phenomena during the DIW process are not revealed in detail, leaving a research gap between the physical experiments and the underlying theories. Here, we presented a comprehensive simulation study of non-Newtonian ink flow during the DIW process. We used the computational fluid dynamics (CFD) method and revealed the shear-thinning behavior during the extrusion process. Different nozzle geometry models were adopted in the simulation. The advantages and drawbacks of each syringe-nozzle geometry were analyzed. In addition, the ink shear stress and velocity fields were investigated and compared in the case studies. Based on these investigations and analysis, we proposed an improved syringe-nozzle geometry towards high-resolution DIW. Consequently, the high-resolution and high shape fidelity DIW could enhance the DIW product performance. The results developed in this work offer valuable guidelines and could accelerate further advancement of DIW.
A Dynamic Cloud Bayes Network-Based Cleaning Method of Multi-Source Unstructured Data
Authors: Chao Yin , Xinian Liao , Xiaobin Li
Published: September 2022

Aiming at the problems of data redundancy and data abnormality of multi-source unstructured data such as video, picture, and text in the process of processing quality inspection and equipment status monitoring of discrete intelligent production line, a multi-source unstructured data cleaning method based on dynamic cloud Bayesian network is proposed. We analyze the characteristics of multi-source unstructured data in the processing operation of the discrete intelligent production line and construct a multi-source unstructured data description model. combine dynamic Bayesian network and cloud model theory to design a multi-source unstructured data cleaning framework and processing flow based on dynamic cloud Bayesian network. finally, the feasibility of the proposed method is demonstrated by simulation analysis of arithmetic cases.
Real-Time Structured Light Scanning Characterization of Surface Topography of Direct Energy Deposited 316L Stainless Steel
Authors: Shen Weijun , Zhang Xing , Liao Yiliang , Li Beiwen
Published: September 2022

Direct energy deposition (DED) has been widely used for additive manufacturing of metallic components toward a variety of applications. Surface characteristics of DED-fabricated components play key roles in determining the property and performance. Besides the average surface roughness which has been extensively investigated in literature, surface skewness and kurtosis are critical for surface integrity, particularly its durability due to stress concentration points. In this work, surface skewness and kurtosis of DED-fabricated 316L stainless steel as affected by processing parameters are investigated. In particular, the surface quality is measured using a microscopic structured light scanning (SLS) system, which is a relatively fast, low-cost, high-efficiency dimensional inspection metrology as compared to other methods. The results demonstrated the correlations between the printing parameters (laser power and scanning speed) and the surface topography of DED printed parts. It is found that the skewness and kurtosis of the surface are more sensitive to the change in scanning speed within a relatively low laser power range. Skewness is positively correlated with the scanning speed, while kurtosis shows a negative correlation with the scanning speed. Given a high scanning speed, Kurtosis and Skewness are more sensitive to the changes of scanning speed. Understanding the relationship between DED processing parameters and areal surface characteristics provides guidance and insights for process optimization and post-processing design towards additive manufacturing of high-performance metallic components.
CFRP Milling and Drilling Process Monitoring by Using a Spindle-Integrated Three Axis Force Sensor
Authors: Kim Jungsub , Chun Heebum , Lee ChaBum
Published: September 2022

This paper introduces a spindle-integrated 3-axis force sensor consisted of 2-axis curved-edge sensor (CES) for the radial direction and single axis capacitive sensor (CS) for the axial direction. The proposed single unit force sensor was used to monitor the carbon fiber-reinforced plastic (CFRP) milling and drilling processes and to understand their machining mechanics. Unlike a conventional cutting force sensor can non-contact measure the displacement of the spindle and estimate the cutting force by multiplying the spindle stiffness and the measured displacement. The force sensor unit was successfully integrated with the spindle and measured the cutting force while machining the CFRP plates with 0°, 45° and 90° fiber orientation. The conventional 3-axis force sensor was also used for a baseline comparison with the cutting force results measured by the proposed method. To monitor and characterize the delamination effect of CFRP, the time-frequency domain scalogram images analyzed form the cutting force data were used. Unique features were extracted according to the fact of existence and nonexistence of the delamination. Laser, the sensor measured capability, allowing for in-process CFRP machining process monitoring and CFRP defect mode prediction was discussed.
Assessing the Impacts of Real-Time Price Prediction Quality on Demand Response Management for Sustainable Smart Manufacturing
Authors: Yun Lingxiang , Li Lin
Published: September 2022

The emerging smart manufacturing technologies pave the way for flexible and autonomous monitoring and control of complex manufacturing systems, which facilitate the implementation of real-time price (RTP) based demand response management towards sustainability. The demand response management requires scheduling of smart manufacturing systems in advance, and thus the quality of RTP predictions directly impacts the performance of demand response. Although several prediction evaluation metrics are currently available, they are designed to show the similarities between prediction and actual RTP, which are not necessarily related to demand response performance. Therefore, in this study, the daily energy cost reductions obtained by solving a demand response management problem are adopted as an indicator of demand response performance. Six commonly used evaluation metrics are examined, and their correlations with energy cost reductions are investigated. In addition, a new metric called k-peak distance considering the characteristics of the demand response problem is proposed and compared with the other six metrics. The case studies show that the proposed metric has two to four times higher correlation with energy cost reductions and only about half of the standard error compared to other metrics. The results indicate that the proposed metric can better represent the prediction quality in the demand response problem.
Robust and Scalable Synthesis of High Surface Area Porous Copper Spheriodized Powders by Electroless Chemical Dealloying
Authors: Niauzorau Stanislau , Kublik Natalya , Hasib Amm , Azeredo Bruno
Published: September 2022

In the past decade, nanoporous metals have been a point of interest in the scientific community because they exhibit chemical, optical, and mechanical properties that are unique from their bulk counterparts. One of the most prominent method for its synthesis is chemical dealloying. While, under electrolytic conditions, dealloying can use process-inputs such as current density and electrical potential to control the ligament size during its synthesis with excellent reproducibility, electroless methods are plagued by the lack of local control of dealloying rates which introduces batch-to-batch variations in ligament size. Given that powder is a format incompatible with electrolysis, this study shows an approach to safely scale fabrication of spherical porous copper powders containing oxides from gas atomized Cu-Al powders. Additionally, the agglomeration that is commonly associated with porous powder fabrication was addressed by its functionalization with an anionic surfactant and powder washing in both deionized water (polar) and anhydrous ethanol (nonpolar). Additionally, hazards associated with its production scaling such as excessive hydrogen evolution, heat generation due to its high-reactivity and exothermic reaction and pyrophoricity are discussed and addressed. As a result of this study, a robust and scalable approach was developed to produce 100 of grams of porous metal powders.
Manufacturing of the Eriedescent Sterilizing Device
Authors: Sharifbaev A. , Mamidi R. , Gottimukkula M. R. , Gacura M. , Vanderlaan G. , Ji X. , Piovesan D.
Published: September 2022

Beyond an exceptional human toll, one of the most evident impacts of the ongoing COVID-19 pandemic is that of disrupted supply chain dynamics. Lessons learned here might help ameliorate the ability of frontline workers to secure personal protective equipment (PPE) such as N95 filtering facepiece respirators (FFRs) to prevent similar issues in future pandemics. A related concern is FFR waste streams, and the ability to recycle N95s using chemical or physical germicidal methods would greatly contribute to lessening PPE scarcity and providing relief to overall supply chains for all essential services. Early in 2020, the U.S. Food and Drug Administration (FDA) issued official guidance for sterilizers, disinfectant devices, and air purifiers with regards to the COVID-19 pandemic as a public health emergency bulletin. This guidance provided nonbinding recommendations for PPE and FFR decontamination processes, involving a wide spectrum of chemical and physical methods of sterilization. Many of the sterilization methods employ high heat or utilize polar chemical disinfectants that can compromise either the physical structure or the electrostatic properties of FFR fibers, thus attenuating the overall protection provided to the frontline worker.

Ultraviolet germicidal irradiation (UVGI) has been employed for nearly a century to sterilize instruments and whole environments. UVGI offers numerous advantages as it is transitory by nature, leaving no chemical residue on the treated artifact. UVGI is also rapid, and depending on illumination sources, UVGI can easily scale to provide coverage to large areas.

Here we provide an analysis of the regulatory aspect related to the use of UVC devices and describe our engineered design of a cost-efficient sterilization chamber that utilizes UVC for decontamination. Our design stresses a low-cost price point to facilitate easy manufacture for not only rapid deployment but also minimal impacts on supply chains. The device is intended to be easy to use, without any specialized training, and thus targets the general public for sanitizing non-washable materials, including PPE, FFR and other potential fomites, including electronic devices of daily use, that otherwise might harbor bacterial, viral and fungal pathogens.
Experimental Investigation of Nanosecond Laser Modification of Bulk Metallic Glass
Authors: Ma J. , Jahan M. P. , Lei Shuting , Gueli Mark
Published: September 2022

Bulk metallic glass (BMG), a comparatively new engineering material, is gaining popularity for its amorphous structure, improved mechanical properties, (i.e., high elasticity, hardness, and fracture toughness), and corrosion resistance. Some of the recent and prospective areas of applications of BMGs include biomedical implants, nuclear reactor, and space and electronic applications. As a result, machinability and surface treatment of BMGs have become an important area of research. In this study, a nanosecond laser with 1064 nm wavelength is used to modify the surface of a Zr-based bulk metallic glass Vitreloy 1b. (Zr67Cul0.6Ni9.8Ti8.8Be3.8). The effects of laser pulse energy level and the lens-to-sample distance on the crater and slot forming are assessed. Single shot mode of the laser system is used to generate craters, and totally six laser pulse energy levels are used. In addition, three lens-to-sample distance values are selected. These six energy levels are 0.053 J, 0.122 J, 0.296 J, 0.415 J, 0.526 J, and 0.662 J. The three different lens-to-sample distance values are 150 mm, 170 mm, and 190 mm. The focal length of the lens is 150 mm. Continuous shot mode of the laser system is used to machine slots on the BMG. For slot forming, two energy levels (0.296 J and 0.662 J) and two distance values between the lens and the workpiece (150 mm and 190 mm) along with two different overlapping ratios (0.75 and 0.95) are used. An interesting observation on the modified surface of BMG is the ripple formation at the edge of the craters, while the center of the crater has comparatively a smoother surface. The modified surface using focal length (150 mm) generated craters with higher number of wrinkles or ripples at the edge compared to the other distances between the lens and the workpiece. The characteristic of formation of ripples remains the same for slot forming also, although the intensity of ripple formation or number of ripples is decreased. Finally, a 3D surface profilometer is used to study the variation of crater depth with laser parameters. The scanning electron microscope (SEM) and energy dispersive x-ray spectroscopy (EDS) analyses are used to investigate surface topography, ripple formation, surface modification, and laser-induced elemental composition on the BMG surfaces.
Minimizing Shrinkage in Microstructures Printed With Projection Two-Photon Lithography
Authors: Kim Harnjoo , Saha Sourabh K.
Published: September 2022

Two-photon lithography (TPL) is a photopolymerization-based additive manufacturing technique capable of fabricating complex 3D structures with submicron features. Projection TPL (P-TPL) is a specific implementation that leverages projection-based parallelization to increase the rate of printing by three orders of magnitude. However, a practical limitation of P-TPL is the high shrinkage of the printed microstructures that is caused by the relatively low degree of polymerization in the as-printed parts. Unlike traditional stereolithography (SLA) methods and conventional TPL, most of the polymerization in P-TPL occurs through dark reactions while the light source is off, thereby resulting in a lower degree of polymerization. In this study, we empirically investigated the parameters of the P-TPL process that affect shrinkage. We observed that the shrinkage reduces with an increase in the duration of laser exposure and with a reduction of layer spacing. To broaden the design space, we explored a photochemical post-processing technique that involves further curing the printed structures using UV light while submerging them in a solution of a photoinitiator. With this post-processing, we were able to reduce the areal shrinkage from more than 45% to 1% without limiting the geometric design space. This shows that P-TPL can achieve high dimensional accuracy while taking advantage of the high throughput when compared to conventional serial TPL. Furthermore, P-TPL has a higher resolution when compared to the conventional SLA prints at a similar shrinkage rate.
Assessment of Shape Descriptors for Distortion Prediction in Powder Bed Fusion Process
Authors: Anandan Kumar Hemnath , Kumaraguru Senthilkumaran
Published: September 2022

Metal additive manufacturing paves the way for industries to create new applications through unique design capabilities. The powder bed fusion process is one among many metal additive manufacturing technologies that are commercially successful. Despite its numerous advantages and application in various fields, defects may occur during processing, which causes premature failure of components. Distortion is one of the major defects, and it depends on process settings, geometry, and orientation related. These distortions and dimensional deviations should be predicted faster for part qualification for many industrial applications. This work attempts to predict distortions based on shape descriptors to address this issue. Shape descriptors are definitions used to identify the details of the shape of a model to be printed. It can be either two dimensional or three dimensional. In this work, 2D shape descriptors are selected for analysis. These 2D shape descriptors can help identify how the design features significantly affect the part distortion in the PBF process. In this work, a few 2D shape descriptors are defined and modelled as a design feature to achieve the objective. Then the respective models are subjected to distortion analysis. The relationship between shape descriptors and distortion are studied through inherent strain method based simulation of distortion. It is observed from the results that most shape descriptors defined in this work can be used to predict the distortion. This work serves as a base and can help create knowledge for proposing design guidelines for the metal powder bed fusion process and helps in redesigning to prevent distortions.
Hybrid Modeling the Influence of Post Processing Heat Treatments on the Strengthening Mechanisms of Additively Manufactured Inconel 718
Authors: Alafaghani Ala’aldin , Ali Majed , Almotari Abdalmageed , Sun Jian-Qiao , Qattawi Ala
Published: September 2022

Due to the layering nature of additive manufacturing, additively manufactured parts exhibit a unique microstructure and are more susceptible to defects. Post-processing heat treatments of additively manufactured parts have shown great promise in improving their quality and reliability. However, the previous studies presented here demonstrated that additively manufactured parts respond to heat treatments differently compared to their traditional counterparts. This demonstrates a need for models that can predict the influence of different heat treatments on the mechanical behavior of additively manufactured parts. A hybrid approach between data-driven and physically informed models was adopted to model the influence of post-processing heat treatments on the strengthening mechanisms of additively manufactured Inconel 718. This work focuses on Inconel 718 for its common use in additive manufacturing and because it is one of the most studied additively manufactured alloys which resulted in producing more data that can be used to model its behavior.
Characterization of vacuum ultraviolet-irradiated surface modification of CoO(111) crystal by low-energy atom scattering spectroscopy
Authors: Tan G. , Fukuta H. , De Silva K. K. H. , Matsuda A. , Yoshimura M. , Yoshimoto M. , Umezawa K.
Published: September 2022

The surface of a CoO(111) single crystal was treated with vacuum ultraviolet (VUV) light at a wavelength of 172 nm without heat treatment. We studied the surface structural analysis of CoO(111) before and after VUV light irradiation in air using low-energy atom scattering spectroscopy. The primary beam was 3 keV-4He0, and backscattered 4He particles from Co atoms were detected using a microchannel plate detector. We compared the experimental spectra to simulation results, and the results demonstrated that the rock-salt CoO(111) surface was transformed to a spinel Co3O4(111) surface after VUV light irradiation. We also identified details about the chemical properties and topmost layers of CoO(111) surfaces before and after VUV light irradiation.
Mitochondrial pyruvate supports lymphoma proliferation by fueling a glutamate pyruvate transaminase 2–dependent glutaminolysis pathway
Authors: Wei Peng , Bott Alex J. , Cluntun Ahmad A. , Morgan Jeffrey T. , Cunningham Corey N. , Schell John C. , Ouyang Yeyun , Ficarro Scott B. , Marto Jarrod A. , Danial Nika N. , DeBerardinis Ralph J. , Rutter Jared
Published: September 2022

The fate of pyruvate is a defining feature in many cell types. One major fate is mitochondrial entry via the mitochondrial pyruvate carrier (MPC). We found that diffuse large B cell lymphomas (DLBCLs) consume mitochondrial pyruvate via glutamate-pyruvate transaminase 2 to enable α-ketoglutarate production as part of glutaminolysis. This led us to discover that glutamine exceeds pyruvate as a carbon source for the tricarboxylic acid cycle in DLBCLs. As a result, MPC inhibition led to decreased glutaminolysis in DLBCLs, opposite to previous observations in other cell types. We also found that MPC inhibition or genetic depletion decreased DLBCL proliferation in an extracellular matrix (ECM)–like environment and xenografts, but not in a suspension environment. Moreover, the metabolic profile of DLBCL cells in ECM is markedly different from cells in a suspension environment. Thus, we conclude that the synergistic consumption and assimilation of glutamine and pyruvate enables DLBCL proliferation in an extracellular environment-dependent manner.
Pattern recognition with neuromorphic computing using magnetic field–induced dynamics of skyrmions
Authors: Yokouchi Tomoyuki , Sugimoto Satoshi , Rana Bivas , Seki Shinichiro , Ogawa Naoki , Shiomi Yuki , Kasai Shinya , Otani Yoshichika
Published: September 2022

Nonlinear phenomena in physical systems can be used for brain-inspired computing with low energy consumption. Response from the dynamics of a topological spin structure called skyrmion is one of the candidates for such a neuromorphic computing. However, its ability has not been well explored experimentally. Here, we experimentally demonstrate neuromorphic computing using nonlinear response originating from magnetic field–induced dynamics of skyrmions. We designed a simple-structured skyrmion-based neuromorphic device and succeeded in handwritten digit recognition with the accuracy as large as 94.7% and waveform recognition. Notably, there exists a positive correlation between the recognition accuracy and the number of skyrmions in the devices. The large degrees of freedom of skyrmion systems, such as the position and the size, originate from the more complex nonlinear mapping, the larger output dimension, and, thus, high accuracy. Our results provide a guideline for developing energy-saving and high-performance skyrmion neuromorphic computing devices.
Cyberinfrastructure for collecting and integrating geology field data: Community priorities and research agenda
Authors: Mookerjee* Matty , Chan Marjorie A. , Gil Yolanda , Gill Gurman , Goodwin Charles , Pavlis Terry L. , Shipley Thomas F. , Swain Taylor , Tikoff Basil , Vieira Daniel
Published: September 2022

In order to address the most important Earth science questions, field scientists must incorporate new cyberinfrastructure (CI) technologies into their workflow and replace some of the traditional, analog methodologies that still prevail today (e.g., notebook, pen, and transit compass). Geologic field data collected via analog methods are far less likely to be fully digitized and integrated with other datasets. Cyberinfrastructure allows data longevity beyond the original investigator. Digital platforms that facilitate data sharing will help break down the artificial barriers between subfields within the Earth sciences and allow researchers to ask new types of questions and provide the means to contend with those that were previously unanswerable.

Close communication and coordination between field-based geologists and computer scientists will facilitate the best cyberinfrastructure and data management for the future. Through a National Science Foundation (NSF)/EarthCube–funded project, discussions between these two groups of scientists were undertaken in a field setting so that computer scientists could better understand the type of data geologists collect and how those geoscientists desire to integrate various types of data into their workflow. Similarly, geologists gained a better understanding of how computer scientists can represent, manipulate, and archive complex data in data management systems, with potential solutions to field data challenges. These discussions centered on the unique issues faced by the geological community regarding the collection, storage, manipulation, representation, and integration of field-based data.
Impact of meibomian gland dysfunction on quality of life and mental health in a clinical sample in Ghana: a cross-sectional study
Authors: Asiedu Kofi , Dzasimatu Selassie , Kyei Samuel
Published: September 2022

Objectives

This study aimed to determine the impact of meibomian gland dysfunction (MGD) on quality of life and psychosomatic conditions.

Design

This was a clinic-based cross-sectional study.

Setting

This study was conducted at the eye clinic of the University of Cape Coast, Ghana.

Participants

215 clinical subjects visiting the clinic for a comprehensive eye examination.

Primary and secondary outcome measures

Symptomatic MGD, asymptomatic MGD, quality of life scores, depression, anxiety and stress.

Results

215 clinical subjects consented to participate in the study, but 212 were included in the analysis. The mean age was 21.9 (± 3.8) years, 54 had MGD and 158 did not have MGD served as controls. There was no statistically significant difference in the mean quality of life scores between subjects with MGD and subjects without MGD (t=1.57, p=0.12). The quality of life scores (DEQS) (p=0.022) were significantly higher in the symptomatic MGD group compared with the asymptomatic MGD group. There was no significant difference in quality of life scores (DEQS) (p=0.251) in the asymptomatic MGD group compared with healthy controls. Using Pillai’s trace in the MANOVA, there was a significant effect of MGD on depression, anxiety and stress (V=0.05, F(3,208)=3.76, p=0.012). Furthermore, Pillai’s trace in the MANOVA showed a significant difference between asymptomatic and symptomatic MGDs for depression, anxiety and stress scores stress (V=0.24, F(3, 51)=5.24, p=0.003).

Conclusion

The study revealed no difference in the quality of life scores between MGD and non-MGD groups. However, the symptomatic MGD group had worse quality of life and psychosomatic symptoms than the asymptomatic MGD group and non-MGD group.
Effects of impacted dynamic hollows and extending dense drops on the concave surface with practical obstacles
Authors: Sayyari Hossein , Peiravi Mohammad Mohsen , Alinejad Javad
Published: September 2022

In this study, the center of a concave surface was analytically studied using the volume of fluid approach to simulate hollow and dense droplets on a variety of solid obstacles. OpenFoam software was used to carry out the numerical simulations. The hollow droplet’s fluid phase, Glycerine, has an outer diameter of 5.25 mm and its gas phase, air, has a diameter of 4 mm. We looked at the laminar flow of an incompressible Newtonian fluid phase. Jet characteristics and droplet collision hydrodynamic behavior were investigated. Due to the interaction between droplets and shells on the obstacle’s surface and the concave surface, which causes a pressure difference and improves fluid movement, the largest jet size is consequently produced in rectangular obstacles. The sharp obstacle, on the other hand, molds the jet’s shortest length and height.
An analytical analysis of Alphabet and Google platform business models
Authors: Mishra Shrutika , Mishra Priyanshu
Published: September 2022

Over the years, due to the emergence of internet and big data, there is an immediate evolution of competitive business models and new strategies. A business model can be defined as an architectural arrangement of the components of profitable transactions developed to explore businesses’ prospects. Previously, companies were operating on a basic pipeline structure where producers puked out products from one end to another end to consumers. Since the advent of technology businesses working on platforms have managed to improve their revenue modeling, their brick and mortar working patterns have been reconsidered. Google being one of the quintessential platforms has come through over the time improving their business modeling and keeping in pace with the technology and strategizing itself and being one of the most successful platform models in value creation. This paper discusses how Google has explored its business model technology into value creation for its company.
Role of External Rotation Osteotomy of the Humerus in Patients with Brachial Plexus Injury
Authors: MADHUSUDHAN Nallatparambil Chandra , BHARDWAJ Praveen , VARADHARAJAN Vigneswaran , VENKATRAMANI Hari , SABAPATHY S. Raja
Published: September 2022

Background: A deficit of external rotation of the shoulder is a common sequelae of brachial plexus injury (BPI). This internally rotated posture of the limb becomes more apparent and functionally limiting once the patient recovers elbow flexion resulting in the hand striking the abdomen on attempted flexion (‘tummy flexion’). This precludes hand-to-mouth reach, resulting in an inability to eat with the involved hand. The aim of this study is to present the outcomes of an external rotation osteotomy of the humerus in adult BPI.

Methods: All BPI patients who underwent an external rotation osteotomy of the humerus at our institution over a 5-year period from January 2015 to December 2020 were included in this study. Data with regard to the age, gender, type of BPI, time from injury to nerve surgery and from nerve surgery till external rotation osteotomy, degree of pre- and postoperative external rotation, time to union, patient satisfaction and complications were recorded.

Results: The study included 19 patients (18 men and one woman) with an average age of 30 years (range 20–58). The average time interval from the injury to the nerve surgery was 3.8 months, and between the nerve surgery and the external rotation osteotomy was 29.5 months. No patient had any preoperative external rotation and all attained a resting posture of 15°–20° of external rotation, were able to reach the mid-line of the body, and none complained of loss of internal rotation. There was an implant failure in one patient that was managed with splinting till union and removal of implants later.

Conclusions: External rotation osteotomy of the humerus is a simple and effective procedure to place the limb in a better aesthetic and functional position.

Level of Evidence: Level IV (Therapeutic)
‘Hook’ Shape Lister Tubercle Is Associated with a Greater Incidence of Extensor Pollicis Longus Tendon Rupture after Distal Radius Fracture
Authors: OGATA Yosuke , OGAWA Takeshi , HIRABAYASHI Takumi , IWABUCHI Sho , YOSHII Yuichi , YAMAZAKI Masashi
Published: September 2022

Background: A rupture of the extensor pollicis longus (EPL) tendon located close to the Lister tubercle is an uncommon complication of distal radius fractures. This study aimed to determine whether the size and shape of Lister tubercle in patients with EPL rupture differs from a matched group of patients with distal radius fractures without EPL rupture.

Methods: We identified 15 patients with EPL rupture (3.5%) out of 426 with distal radius fractures treated conservatively at our hospital over 4 years. Out of the remaining 411 patients with distal radius fractures without EPL rupture, we selected patients using simple random sampling and pseudo-randomised them such that their age, sex and fracture type were matched with patients exhibiting EPL rupture. The size and shape of the Lister tubercle and the size of the EPL groove were measured in both groups using computed tomographic scans and compared.

Results: There was no difference in the size of the Lister tubercle or the EPL groove between both groups. A ‘hook’-shaped Lister tubercle was noted in 8 out of 15 patients with EPL rupture but in only 1 out of 15 matched patients without EPL rupture.

Conclusions: A ‘hook’-shaped Lister tubercle was seen more often in patients with EPL rupture following distal radius fracture.

Level of Evidence: Level III (Therapeutic)
Patient Characteristics Associated with Operative Treatment for Adult Traumatic Brachial Plexus Injuries at Two Tertiary Referral Hospitals in a Single US Metropolitan Area
Authors: ZHANG Dafang , ELHASSAN Bassem , GARG Rohit
Published: September 2022

Background: The primary objective of this study was to identify patient-related and socioeconomic factors associated with the operative treatment of adult traumatic brachial plexus injuries (BPI) at two tertiary referral centres in a single metropolitan area in the United States. The secondary objective was to assess surgeon variability in operative treatment.

Methods: Adult patients with traumatic BPI at two tertiary referral centres in a single metropolitan area from 2015 to 2019 were retrospectively identified. After applying exclusion criteria, 84 adult patients with traumatic BPI treated by 22 surgeons were included. Our response variable was operative treatment of the traumatic BPI. Bi-variate screen was performed, and multi-variable logistic regression analysis was used to identify factors associated with operative treatment. Surgeon variability was separately assessed using Fisher’s exact test.

Results: The mean age of the study cohort was 45 years, and 69% were male. The most common BPI pattern was a global injury (39%) followed by an upper trunk injury (23%). Thirty-eight patients (45%) underwent operative treatment for the traumatic BPI. Multivariable logistic regression analysis showed that younger age and out-of-state referral were associated with operative treatment. There was significant surgeon variation in the utilisation of operative treatment.

Conclusions: Out-of-state patients had more than four times higher odds of operative treatment, suggesting a regional practise pattern in which BPI requiring surgery are referred from surrounding states to our tertiary centres. Supra-regional BPI centres may facilitate timely referrals for specialty care. High-quality outcomes research in BPI is needed to mitigate surgeon treatment variation.

Level of Evidence: Level IV (Therapeutic)
Ultramicroelectrode Based Approaches to Diagnose Utility of Redox Electrolytes in Flow Batteries
Authors: Kulesza Pawel J. , Rutkowska Iwona A. , Janiszewska Claudia , Vezzu Keti , Negro Enrico , Di Noto Vito
Published: September 2022

The proposed redox electrolyte system, concentrated solutions of Keggin type silicotungstic acid (H4SiW12O40), have been tested using the microelectrode methodology to determine mass-transport (effectively diffusional) coefficients for charge propagation and homogeneous (electron self-exchange) rates of electron transfers. Silicotungstic acid (H4SiW12O40) acts as proton conductors, and undergoes fast, reversible, multi-electron electron transfers leading to the formation of highly conducting, mixed-valence (tungsten(VI,V) heteropoly blue) compounds. To develop useful electroanalytical diagnostic criteria, electroanalytical approaches utilizing ultramicrodisk electrodes have been adapted to characterization of redox electrolytes. Combination of two parallel ultramicroelectrode-based experiments performed under radial (long-term experiment; e.g., slow scan rate) and linear (short-term experiment; e.g., fast scan rate) diffusion conditions permits determination of both effective concentration of redox centers and transport (diffusion) coefficient parameters, which are crucial to evaluation of the utility of a redox electrolyte for charge storage.
(Invited) State of Charge Monitoring of Vanadium Flow Batteries Using Spectroscopic and Electrochemical Methods
Authors: Rybalchenko Maria , Quill Nathan , Buckley D. Noel , Lynch Robert P.
Published: September 2022

In this paper we demonstrate our ability to make accurate in- situ measurements of both the state-of-charge and the concentration of individual vanadium species in a lab scale vanadium flow battery. The analysis is based on our previously published characterization of the spectroscopy of mixed solutions of VII/VIII and VIV/VV. Measurements of volume changes of the electrolyte in each half-cell are also shown and used to estimate the true value of concentration for each vanadium species as the cell is charged. The feasibility of optically monitoring the state-of-charge is clearly demonstrated and the unique ability of our data processing techniques to determine actual concentrations in- situ is revealed.
Very Low Temperature Tensile and Selective Si:P Epitaxy for Advanced CMOS Devices
Authors: Kanyandekwe Joël , Bauer Matthias , Marion Tanguy , Saidi Lazhar , Pin Jean-Baptiste , Bisserier Jeremie , Richy Jérôme , Gauthier Nicolas , Dezest Pattamon , Brunet Laurent , Lapras Valérie , Dewolf Tristan , Thomas Shawn , Hartmann Jean-Michel
Published: September 2022

We demonstrate the feasibility of selectively growing highly doped and tensile-strained Si:P layers at temperatures 500°C or less on each side of advanced n-type MOS devices. To that end, we used a Cyclic Deposition Etch (CDE) strategy instead of a conventional “co-flow” approach fit for the high temperature (> 600°C) Selective Epitaxial Growth (SEG) of t-SiP films. A high order silicon precursor was used together with PH3 to benefit from high t-Si:P growth rates at 500°C and less. Selective etchings were performed with Cl2 as an etchant gas, as it yielded much higher etch rates than HCl. We first investigated the blanket growth of t-SiP on fullsheet Si wafers. 5 to 15 times higher higher growth rates than with standard precursors were obtained at low temperatures with our new HOS silicon precursor. We then investigated the etching efficiency of Cl2, with several tens of nanometers per minutes etch rates achieved at very low temperatures. Using a CDE strategy, we then probed phosphorus incorporation in blanket t-Si:P films on fullsheet wafers. High quality and smooth t-SiP layers with up to 5.4%, 4.3% and 5.8% of P and sheet resistances as low as 0.33, 0.27 and 0.21 mohm.cm were obtained at 500°C, 475°C and 450°C, respectively. We then tested our CDE SiP process for SEG, first on test structures then on each side of real FD-SOI devices, with smooth, high quality, tensile SiP layers grown at 500°C with 4.5% of P.