bluuebunny/crossref_metadata_2025 huggingface dataset:
Influence of Composite Polymer Coatings on the Insertion Force of Needle-Like Structure in Soft Materials
Authors: Patel Kavi I. , Zhu Long , Reddy Gidde Sai Teja , Ren Fei , Hutapea Parsaoran
Published: February 2021

This study is aimed to evaluate the effects of coated surgical needles with composite polymers such as polydopamine (PDA), polytetrafluoroethylene (PTFE), and carbon. The coated needle’s lubrication properties were measured using 3 DOF force sensors and 3D robot system by the repetitive insertion in soft tissue materials. Needle durability is a measure of needle sharpness after repeated passage through high stiffness tissue materials. The composite coatings were shown to reduce the insertion force by ∼49% and retraction forces by ∼46% when tested using a bovine kidney. The surface roughness and the lateral friction force of the needle are measured using the Atomic Force Microscope (AFM). The adhesion energy of the different coating on the needle will be measured using a nano-scratch method.
Quantifying the Effects of Convective Heat Transfer on Photovoltaic Performance and Optimal Tilt Angle
Authors: Ghabuzyan Levon , Kuo Jim , Baldus-Jeursen Christopher
Published: February 2021

Electrical performance of photovoltaic (PV) cells are affected by their operating temperatures, which lead to changes in the performance of the PV panel. The performance and efficiency of a PV system is dependent upon many factors, such as its angle of incidence, accumulation of dust, speed and direction of natural winds. Particularly, angle of incidence between solar rays and PV modules is the most important. This paper will focus on developing a numerical tool for predicting the optimal tilt angle, based on wind flow over PV panel in a fixed tilt array, in order to observe the effects on performance. A 1.651 m long by 0.991 m wide solar PV panel is used in the analysis. The panel is mounted on top of a tall building and the tilt angle is fixed at one angle. This paper will observe how the PV panel is affected by wind flow and how the optimal tilt angle will change, and if it is necessary to account for convection. Increasing convective heat transfer has the potential to reduce the operating temperatures of photovoltaic solar panels thus increasing their efficiency and producing more power. This relationship was used in a numerical tool to predict the performance of the panel at different tilt angles and different wind speeds. The results show that wind speed and direction do affect power output and that designers should account for convective effects when designing positioning and orientation of solar panels.
A Long-Distance/Online Teaching Model With Video Technology for Engineering Courses Suitable for Emergency Situations
Authors: Rodríguez-Paz Miguel X. , González-Mendivil Jorge A. , Zamora-Hernandez Israel
Published: February 2021

In this paper we present the implementation of a model involving real-time online education sessions for the continuation of a semester in emergency situations when the university has to stop activities. This model has been used during the strong Earthquakes in Central Mexico in September 2017 and during the most recent global situation due to the coronavirus emergency.

Teaching of Engineering courses usually involves the combination of lectures, tutorials, problem solving sessions and mid-term exams. In emergency situations when the activities at the university are not possible, other models have to be implemented, usually within a short period of time. In this paper, a model involving the use of video conferencing software, namely zoom, the use of video repositories and the use of digital social media is presented as a successful model for the continuing teaching of courses of Engineering Mechanics. Results show a good acceptance by students and some suggestions given by the students in order to make this model more attractive are also presented. These findings can be applied in the future in the design of schemes for teaching or continuation of a term in higher education when the university faces an emergency that requires activities to be interrupted oncampus.

As conclusions the authors present a series of recommendations for teachers or professors interested in applying this model or in designing new schemes for teaching online when the university has to be closed.
Effect of Adding Graphene Nano-Platelets With Surfactants on Bio-Based PCM Characteristics and its Cooling Performance
Authors: Sheikh Yahya , Gadalla Mohamed , Umair Muhammed , Mehaisi Elmehaisi , Azmeer Ahmed
Published: February 2021

Phase change materials (PCM) are materials that absorb/release large amounts of thermal energy at constant temperatures during phase change. Consequently, PCMs could be effective when electronic cooling systems such as heat sinks and heat pipes are considered. In the selection of PCMs for cooling systems, bio-based PCMs are more effective when compared to inorganic PCM. However, bio-based PCMs have poor thermal conductivity and therefore suffer from poor heat transfer characteristics. The diffusion of certain additives within the PCM has proven successful in the enhancement of heat transfer during the cooling process. Graphene Nanoplatelets (GNPs) presents itself as one such additive. Using PureTemp PCM as a heat sink for an electric heater, this paper experimentally investigates the cooling performance of the heat sink when GnPs and various surfactants such as, SDS, SDBS and SSL, are added to the bio-based PCM. Finally, results indicate that the addition of GnPs increased the time taken for the heater to reach a reference temperature of 43 °C by nearly 12% when compared to PurePCM heat sink, indicating an improved cooling performance of the PCM heat sink when GnP’s were added. Furthermore, the experiment indicated that SSL surfactant showed a 9% increase in time taken to reach the reference temperature when compared to other surfactants. SDS surfactant indicated the highest increase in thermal conductivity when compared to other surfactants as it reported the highest increase of 147% when compared with the thermal conductivity of PurePCM.
Crystalline Phase Change due to High Speed Impact on A36 Steel
Authors: Slewa Muna
Published: February 2021

The well-known industrial standard called A36 alloy steel is an iron-based alloy that has many applications due to its ability to be easily machined and welded. The alloy has less than 0.3% carbon by weight and is therefore considered a low carbon alloy. Because of this low carbon content, the alloy is useful as a general-purpose steel. It is altogether strong, tough, ductile, weldable, and formable. It is used in the construction of bridges, buildings, automobiles, and heavy equipment as well as in the construction industry. A36 steel also contains small amounts of other elements including manganese, sulfur, phosphorus, and silicon. These elements are added to give the steel alloy desired mechanical and chemical properties. The A36 steel alloy gets the number 36 in its name because of its yield strength. The steel, in most to all configurations, will have a yield strength of a minimum of 36,000 pounds per square inch. This shows high ductility in the material.

The physical characteristics and molecular structure of A36 steel are also well known. However, there is little known about the effect of high-velocity impact on the crystalline structure and material phase of this metal alloy. Sections of approximately 90 × 90 square microns were cut off the test samples, keeping with the required standards for surface finish. These surfaces were examined and analyzed after impact. The surface sections were selected from a range of areas including those immediately under the impact crater to locations not physically affected by the impact. Three different impact speeds were applied, and the prepared samples were examined. An EBSD (Electron Backscatter Diffraction) imaging microscope is used to examine the crystalline structure of the test sample post-impact.

Most metals crystallize in one of three prevalent structures: body-centered cubic (BCC), hexagonal close-packed (HCP), or face-centered cubic (FCC). Since these crystalline structures are the most expected lattice formations, the samples are examined post impact for changes in the allocation of molecular structure. The results were then tabulated according to the regions relative to the impact crater. In previous research, results show that post-impact inspection of HCP phase change, in iron specifically, is completely and rapidly reversible during impact. However, in this study, traces of HCP were found at some locations in all stages of post-impact. This study also found that the BCC crystalline structure remained the dominant phase structure after impact. This is true with all test samples and all levels of shock loading.
Modelling and Performance Analysis of Different Types of Li-Ion Battery
Authors: Durganjali C. Santhi , Raghavan Harini , Radhika Sudha
Published: February 2021

Lithium ion batteries are at present, the most widely used battery technology in the world. Every battery’s performance is characterized by certain parameters like the State of Charge, and Depth of Discharge, C-rate etc. To explore the possibility of more efficient types of Li-ion batteries for more applications a wide demand in identifying, modeling and testing of different possible combinations of electrode materials and electrolytes of Li-ion batteries arose. Taking this demand into consideration authors of this paper focus on the modeling and simulation of a wide variety of possible combinations of Li-ion battery in a 2-dimensional model. In addition to that, a thermal model of a cylindrical lithium ion battery was built in 3-dimensions and was validated with experimental data. The simulations were carried out on COMSOL:Multiphysics.
Application of Deep Neural Network in the Design of Microresonators Subject to Microfabrication Constraints
Authors: Alaie Seyedhamidreza
Published: February 2021

Deep Neural Networks (DNNs) have transformed various fields, yet their application in design of microsystem has been limited. Here, we demonstrate a framework for application of adversarial generative networks in design of microresonators targeting for operation in MHz frequencies. The topology of the microresonators are constrained based on the critical dimension common in the photolithography process. The design-space includes a free standing window of Si film on an SOI wafer that is supported on its four sides. The film is etched through a mask with an arbitrary 2D layout. We employ DNNs in finding 2D layouts that result in a membrane with desirable natural frequencies. For this purpose, deep generative networks (generators) and deep neural networks (discriminators) are employed. Two datasets representing desirable and undesirable layouts are created using finite element analysis. Subsequently, the discriminator is trained to classify desirable and undesirable layouts as well as those generated by the generator. Simultaneously, the generator is trained to sample layouts that are more likely to be classified as desirable by the discriminator. The results show that this framework is capable of producing designs with desirable vibrational features, encouraging further research in this topic.
A New Kinematic Error Modelling and Identification Method of the Parallel Manipulator
Authors: Li Weitao , Wang Liping
Published: February 2021

Parallel manipulators have broad application prospects on hybrid machine tools. Kinematic error modelling and identification are two key processes to improve the accuracy of parallel manipulators. The traditional kinematic error modelling method adopts the partial differentiation of the ideal kinematic model. However, the partial differentiation method is pure mathematical calculation, which ignores physical meaning of error terms corresponding to each link. In the process of error identification, the Jacobian matrix obtained from the partial differentiation method is usually ill-conditioned, which leads to non-convergence of the identification process. In order to solve the above problems, this paper proposes a new kinematic error modelling method and an error identification model. Firstly, the basic error terms for single link are analyzed. Based on basic error terms, the kinematic error model is established by using the practical connection point of two adjacent links. Then, a new error identification model is derived from the kinematic error model. Finally, as a study case, a 3-DOF parallel tool head is used to verify the correctness of the proposed method. The numerical results show that the proposed method is effective and the accuracy of the 3-DOF parallel tool head improves significantly after compensation of error terms.
Wide Bandwidth Piezoelectric Energy Harvester With Transverse Movable Mass
Authors: Rodriguez Luis A. , Jackson Nathan
Published: February 2021

High Q-Factor vibrational energy harvesters are ideal as they maximize power generation, but a narrow bandwidth limits the potential use in most commercial applications, and it is a major challenge that has not been resolved. Numerous designs have been investigated to solve this challenge but most of the attempts are based on frequency sweeping mechanism or require complex design/fabrication which are not practical especially for MEMS devices. This paper reports for the first time a transverse vertical moving mass inside the proof mass as a method to widen the bandwidth which is independent of frequency sweeping. The out-of-plane movable mass is achieved by fabricating a vertical cavity in the proof mass and partially filling the cavity with metallic spheres. Ultra-wide bandwidth was achieved for low (0.5g) and high (1g) accelerations with an increase in bandwidth from 3.9 Hz (control) to 56 Hz (movable mass). This transverse method of widening the bandwidth is potentially scalable to MEMS devices.
Internal Resistance Based Assessment Model for the Degradation of Li-Ion Battery Pack
Authors: Wulandari Iffandya Popy , Pan Min-Chun
Published: February 2021

As one pioneer means for energy storage, Li-ion battery packs have a complex and critical issue about degradation monitoring and remaining useful life estimation. It induces challenges on condition characterization of Li-ion battery packs such as internal resistance (IR). The IR is an essential parameter of a Li-ion battery pack, relating to the energy efficiency, power performance, degradation, and physical life of the li-ion battery pack. This study aims to obtain reliable IR through applying an evaluation test that acquires data such as voltage, current, and temperature provided by the battery management system (BMS). Additionally, this paper proposes an approach to predict the degradation of Li-ion battery pack using support vector regression (SVR) with RBF kernel. The modeling approach using the relationship between internal resistance, different SOC levels 20%–100%, and cycle at the beginning of life 1 cycle until cycle 500. The data-driven method is used here to achieve battery life prediction.based on internal resistance behavior in every period using supervised machine learning, SVR. Our experiment result shows that the internal resistance was increasing non-linear, approximately 0.24%, and it happened if the cycle rise until 500 cycles. Besides, using SVR algorithm, the quality of the fitting was evaluated using coefficient determination R2, and the score is 0.96. In the proposed modeling process of the battery pack, the value of MSE is 0.000035.
Feature Selection for Audio-Based Fault Detection in Pumps
Authors: Adegboye Victor O. , Rife Jason H.
Published: February 2021

Whilst extensive work has been done on fault detection in bearings using sound, very little has been accomplished with other machine components and machinery partly due to the scarcity of datasets. The recent release of the Malfunctioning Industrial Machine Investigation and Inspection (MIMII) dataset opens the opportunity for research into malfunctioning machines like pumps, fans, slide rails, and valves. In this paper, we compare common features from audio recordings to investigate which best support the classification of malfunctioning pumps. We evaluate our results using the Area Under the Curve (AUC) as a performance metric and determine that the log mel spectrum is a very useful feature, at least for this dataset, but that other features can enhance detection performance when ambient noise is present (improving AUC from 0.88 to 0.94 in one case). Also, we find that mel Frequency Cepstral Coefficients (MFCC) perform substantially poorer as features than a sampled mel spectrogram.
Material Dependent Laser-Induced Patterns for Metal-Plastic Hybrids Directly Jointed Using Injection Molding
Authors: Peng Fei , Yang Can , Li Chunbo , Yang Huan , Yin Xiao-Hong
Published: February 2021

In the present work, the nanosecond-pulsed laser micro machining was applied to induce surface patterns with three different metals (i.e., titanium, aluminum as well as magnesium alloys) for producing metal-plastic hybrid (MPH) joints by injection molding. Specifically, laser variables such as the scanning speed, laser frequency, and scan repetition were altered to obtain different surface patterns. The surface morphologies were observed using scanning electron microscope (SEM). It’s found from SEM observations that due to the thermal ablation of the laser, micro patterns such as grooves and protrusions exist on all metal surfaces. However, distinct morphologies can be seen for different metals, with the most variable microstructures for the titanium alloy. Moreover, the surface wettability to the distilled water for all metal surfaces was examined with a contact angle measuring instrument. It’s shown that the contact angle characterizing the surface hydrophilicity is not necessarily related to process condition but surface morphologies. The tensile tests of the injection molded MPH joints showed that the titanium alloy surfaces with bumpy morphology facilitated forming micro-scale mechanical interlocking between the metal and the plastic, leading to enhanced MPH joint strength.
Feature Extraction Based on Teager-Kaiser Energy Operation and Envelope Spectra for Fault Detection of a Reciprocating Compressor
Authors: Hou Chin-Che , Pan Min-Chun
Published: February 2021

In this paper, signal analysis techniques based on Teager-Kaiser energy operation and envelope spectra for fault detection of the discharge valve of a reciprocating compressor is proposed. The method can accurately identify the existing fault of vibration signal features that it simulated by the synthetic signals. A two-phase study was designed to explore the signals simulation and the experimental validation. Signals simulation, which is based on the operation of a reciprocating compressor, and experiment design, which uses three conditions. The first stage is to simulate the operation of the reciprocating compressor, which is to simulate a synthetic signal for the cycle and impact. The synthetic signal is composed of a noise, square wave, and pulse wave. In this study, the synthetic signal is signal-processed by the Teager-Kaiser energy operator and the envelope spectrum that they can effectively extract feature signal and the noise almost is eliminated. The second stage is applied to the signal processing technique proposed in the first stage. Experimental verification of experiment design by the different operating conditions of reciprocating compressor valves. Through the above analysis technology, it is proved that the synthetic signal can be eliminated the background noise to obtain the feature signal. The feasibility of the proposed approach is verified by simulation results, the experiment is to validate with the measurement signals from a six-cylinder reciprocating compressor under different valve conditions. Simulations and experimental results support the proposed technology positively.
Modeling Vapor Transport in a Hollow Fiber Membrane Humidifier Using ε-NTU Approach
Authors: Vu Hoang Nghia , Nguyen Xuan Linh , Yu Sangseok
Published: February 2021

In a fuel cell vehicle, the water content of the gas supply within certain ranges plays a key role in improving the performance of a proton exchange membrane. The lower limit of water content in the air supply is to avoid the problem of drying-out, while the upper prevents flooding. Water management can be accomplished by a membrane humidifier which allows water vapor to permeate the mixture from the side having the higher water concentration, moving to the other side of the membrane.

In this study, the variation in water content collected at the outlet of a membrane humidifier is investigated with a one-dimensional mass exchanger model and various operating variables. The vapor concentration of outlet flows is affected by operating temperature and relative humidity of the membrane humidifier. Relative humidity of the dry side at the point of outlet flow, to be supplied to the fuel cell module, is the key characteristic. The analogy of the effectiveness-NTU approach for heat transfer is used to analyze the characteristics of the mass exchanger. Mass flux through the membranes is estimated with an overall mass transfer coefficient which represents vapor transport characteristics moving through the membrane module. This coefficient has a similar role to the overall heat transfer coefficient in heat exchanger analysis. This parametric study is conducted to understand the effects of different variables. The Effectiveness-NTU methodology of mass transfer uses the overall mass transfer coefficient and the mass transfer rate, as evaluated experimentally. Simulink software is then employed to deliver outcomes of the model for different operating conditions.
Numerical Analysis of Machining Part Distortion in Aircraft Aluminum Structures
Authors: Ledesma-Orozco Elías , Rodríguez-Sánchez Alejandro E.
Published: February 2021

The inherent residual stresses in the raw materials of large monolithic structural components whereby machining procedures are needed to produce aircraft components, cause deviations, and distortions that are undesired and rise challenges for engineering design and engineering production teams of the aerospace companies. A numerical approach to address part distortion is proposed in this paper. An algorithm was developed and implemented as a finite element subroutine in the software ANSYS APDL, which uses the raw inherent residual stress parameters of the aluminum alloy and the machining locations of a structural specimen to simulate the machining distortion phenomenon in aircraft aluminum structures. This algorithm uses as inputs the finite element mesh of a component, the coefficients of residual stresses functions, and the machining location parameters from where a part is made of a raw material blank. The numerical results predicted the part distortion phenomenon with an Absolute Error of 2.79% with respect to initial experimental measurements of part distortion. Additionally, the proposed approach was used to develop part distortion curves by considering the machining location of the specimen. From these, numerical optimization techniques led to determine the machining location of the representative specimen that attained lower distortions. Such location corresponded to a vertical value around of 3.15 mm for the two simulated residual stresses conditions in the material. An additional measurement was carried out to validate the optimal numerical results and errors below 3% were obtained. Consequently, the proposed approach can be of use to determine, to reduce and to optimize part distortion without further experimental testing in structural aluminum 7050-T7451 alloy aircraft components.
Fatigue Crack Analysis of Magnesium ZK60 V-Notched Specimen Using X-Ray Tomography
Authors: Albinmousa Jafar , Al-Dakheel Hussain , Temitope Idris , Al-Sadah Jihad , Muhammad Raashid
Published: February 2021

Magnesium alloys are attractive lightweight structural materials that have the potential to be used in aerospace, automotive and medical industries. However, fatigue is a major cause of failure in structural components. It is also known that notches, which are unavoidable, have a detrimental effect on fatigue resistance. Fatigue damage is associated with the formation of crack(s). Therefore, it is necessary to understand the fatigue crack growth behavior for better design analysis.

In this research, a V-notched specimen machined from ZK60 magnesium extrusion is tested under cyclic axial loading. Fatigue experiment was performed under completely reserved force-controlled loading with an amplitude of 12 kN and under standard laboratory conditions. The fatigue test was interrupted 14 times in order to perform ex-situ x-ray tomographic analysis using the Nikon XTH 225 ST system. The sample failed after 184,005 cycles. A gray-level thresholding process was performed using MATLAB on the selected slices to convert each pixel to either white or black color. Then, these slices were stacked using imaging software to make 2D representations of the crack surface at different cycles. As a result, the areas of the crack surfaces were measured for all scans. The result suggests an exponential relationship between the crack surface area and the number of cycles.
Atomistic Molecular Dynamics Simulation Based Failure Criterion of Polycrystalline Graphene Under Biaxial Loading
Authors: Shishir MD Imrul Reza , Tabarraei Alireza
Published: February 2021

Graphene sheets produced by chemical vapor deposition (CVD) are polycrystalline and the presence of grain boundaries (GBs) alter their mechanical properties relative to single-crystal graphene. In this study, we have performed a series of molecular dynamics simulations using REBO2+S potential in order to develop a failure criterion for infinite polycrystalline graphene sheets under biaxial tension. We have studied the effect of temperature on mechanical properties of polycrystalline graphene for both uniaxial and biaxial loading conditions. The normal stresses are normalized with respect to the corresponding uniaxial ultimate strength values and the normalized stresses are used to define the failure envelope of polycrystalline graphene. Our study suggests that a bilinear failure envelope or a circular failure envelope can be used to represent with reasonable accuracy the tensile strength of polycrystalline graphene under biaxial loading at different temperatures.
Strain Response and Aerodynamic Damping of a Swirl Distortion Generator Using Computational Fluid Dynamics
Authors: Hayden Andrew , Untaroiu Alexandrina
Published: February 2021

Boundary layer ingestion (BLI) concepts have become a prominent topic in research and development due to their increase in fuel efficiency for aircraft. Virginia Tech has developed the StreamVane™, a secondary flow distortion generator, which can be used to efficiently test BLI and its aeromechanical effects on turbomachinery. To ensure the safety of this system, the complex vanes within StreamVanes must be further analyzed structurally and aerodynamically. In this paper, the induced strain of two common vane shapes at three different operating conditions is computationally determined. Along with these observations, the aerodynamic damping of these vanes are calculated to predict flutter conditions at the same three operating points. Steady CFD calculations are done to acquire the aerodynamic pressure loading on the vanes. Finite element analysis (FEA) is performed to obtain the strain and modal response of the StreamVane structure. The mode shapes and steady CFD are used to initialize an unsteady CFD analysis which determines the aerodynamic damping of the vanes. The testcase used for this evaluation was specifically designed to overstep the structural limits of a StreamVane, and the results provide an efficient computational method to observe flutter conditions of stationary systems.
Multi-Fidelity Aerodynamic Modeling of a Floating Offshore Wind Turbine Rotor
Authors: Zhang Kai , Bilgen Onur
Published: February 2021

This paper presents a comparison of low- and mid-fidelity aerodynamic modelling of floating offshore wind turbine rotors. The low-fidelity approach employs the conventional Blade Element Momentum theory implemented in AeroDyn of OpenFAST. This model ignores the aerodynamic interactions between different blade elements, and the forces on the blade are determined from the balance between momentum theory and blade element theory. With this method, it is possible to calculate the aerodynamic performance for different settings with low computational cost. For the mid-fidelity approach, the Actuator Line Modeling method implemented in turbinesFoam (an OpenFOAM library) is used. This method is built upon a combination of the blade element theory for modeling the blades, and a Navier-Stokes description of the wake flow field. Thus, it can capture the wake dynamics without resolving the detailed flows near the blades. The aerodynamic performance of the DTU 10 MW reference wind turbine rotor is studied using the two methods. The effects of wind speed, tip speed ratio, and blade pitch angles are assessed. Good agreement is observed between the two methods at low tip speed ratios, while the Actuator Line Modeling method predicts slightly higher power coefficients at high tip speed ratios. In addition, the ability of the Actuator Line Modeling Method to capture the wake dynamics of the rotor in an unsteady inflow is demonstrated. In the future, the multi-fidelity aerodynamic modules developed in this paper will be integrated with the hydro-kinematics and hydro-dynamics of a floating platform and a mooring system, to achieve a fully coupled framework for the analysis and design optimization of floating offshore wind turbines.
High-Fidelity Structural Analysis of a 10 MW Offshore Floating Wind Turbine Rotor Blade
Authors: Yaghmaie Reza , Bilgen Onur
Published: February 2021

This paper presents a comparison of low- and high-fidelity structural analyses of a 10 MW offshore floating wind turbine rotor blade. For low-fidelity analysis, BeamDyn as a part of the OpenFAST toolset is used. For high-fidelity analysis, the Toolkit for the Analysis of Composite Structures (TACS) finite element method is used. First, several numerical examples with reference solutions from the literature are investigated to compare the accuracy and efficiency of the low- and high-fidelity structural models. Next, the DTU 10 MW reference wind turbine blade is analyzed using both the low- and high-fidelity methods. The bending response of the blade is analyzed. The results show that the high-fidelity model agrees with low-fidelity results and reference solutions. The high-fidelity model represents the deformations more accurately than the low-fidelity model and therefore is appropriate for structural analysis of complex wind turbine blade shapes.
Cutting-Tools Degradation Assessment for Structural-Steel Machining Centers
Authors: Huang Tsung-Ren , Chen Hao-Ting , Pan Min-Chun
Published: February 2021

To assess cutting-tools degradation, mounted accelerometers and current clamp probes were used to acquire machining vibration for both the band-saw machine and the drilling machine, of which a structural-steel machining center is composed. Significant features were first extracted through spectral analysis, and tool degradation assessment was conducted through using a supervised learning scheme, self-organizing map. The results reveal that 10% remaining useful life can be predicted before the band-saws and drills wore out.
Infusing Entrepreneurial Mindset Into Engineering Education: Five Strategies for Implementation Success
Authors: Lichtenstein Gary , Collofello James S.
Published: February 2021

The Ira A. Fulton Schools of Engineering (FSE) received a two-year grant to institutionalize entrepreneurial mindset (EM) throughout the college. This paper summarizes the history of entrepreneurial education in engineering, then reviews metrics of initial implementation success across 17, ABET-accredited programs. Five strategies were deployed during the implementation stage of the initiative, which strived to engage 66 faculty who taught one of three EM-focus courses in each undergraduate program: a first-year engineering course, a required design or technical course in the second or third year, and Capstone. Strategies were: 1) Adopting a 21st Century Engineer orientation to entrepreneurial education; 2) Operationalizing EM using a single, consistent framework across all courses and programs; 3) Modeling implementation based on ABET accreditation processes; 4) Infusing the initiative with substantial faculty support; and 5) Incentivizing faculty with stipends to promote initial implementation. Challenges revolve around sustaining implementation while improving effectiveness of EM instruction and assessment, particularly after grant funding. Lessons learned are that 1) institutionalization of the initiative needs to be strategized during initial implementation and 2) faculty are more likely to support an initiative that includes activities and outcomes about which they have always cared, including student success, professional development, and collegial interaction.
Modelling, Control and Design of a Clutched Parallel Elastically Actuated Articulated Robotic Leg Through Virtual Tunable Damping
Authors: Tanfener Emre , Candan Sinan Şahin , Turgut Ali Emre , Saranlı Uluç
Published: February 2021

In this study, design, modelling and control of a clutched parallel elastically actuated articulated leg is presented. Clutch mechanism is introduced to disengage the parallel elastic element when it is not needed. Some of the design principles concerning the ease of manufacturing and assembly are underlined. While the system has two joints at hip and knee that can be actuated, for simplicity, restrained motion of the system in vertical direction is considered only with hip actuation. Controller is based on a template model and the desired motion is obtained by equating (embedding) dynamics of the physical system (anchor) to the template model. Spring loaded inverted pendulum (SLIP) model including a virtual viscous damper is chosen as the template. Controller decides on the virtual damping constant in the template to reach desired apex positions. A wrapping cam mechanism is introduced to equate the potential energy function of the parallel spring to the desired linear spring of SLIP model. To complete embedding, necessary torque is calculated by equating the virtual works of the inputs. Overall, simulation of the hopping system and the important aspects of design are presented.
Investigation of Nonlinear Effects in a Bolted Joint Beam Using the Base Excitation
Authors: Doranga Sushil
Published: February 2021

In this paper, the nonlinearity detection, characterization and identification of a bolted beam assembly is presented. The new approach based on the force reconstruction using the base excitation as an input is used for the identification of nonlinear parameters. The nonlinear effect in the bolted beam assembly was induced by reducing the bolt clamping loads. A collection of frequency response functions (FRFs) are shown at different clamping loads to detect and characterize the nonlinearities. Once the nonlinearities are detected and characterized, the restoring force surface method using the reconstructed force was used to identify the nonlinear parameters in the modal space. Four different base excitation (energy) levels with three different tightening torques were considered in the tests in order to study the energy dependence of the damping nonlinearities. In all the cases, the nonlinear system identification methodology employed was successful in identifying the damping and stiffness nonlinearities.
Oklahoma City Contaminant Dispersion: Concentration Data Processing and Analysis for a Scaled Puff Release Experiment
Authors: Homan Ty
Published: February 2021

Magnetic resonance techniques were leveraged to obtain velocity and concentration measurements for a puff release contaminant dispersion study. The study involved a scaled model of downtown Oklahoma City as it was in 2003, and sought to provide a high fidelity, three-dimensional data set for comparison with JU2003 and subsequent studies. The scaled model was placed in a water channel with fully turbulent flow (Re = 36,000), and an MRI system was used to take scans at 12 time-specific measurement phases throughout the puff injection cycle. The present work details processing methods applied to the nearly 650 million magnetic resonance concentration (MRC) data points obtained from the study. Processing entailed the calculation of a concentration field through background subtraction and normalization involving several distinct scan types. Uncertainty was reduced through the scaling and combination of high molarity scans. Processing methods are followed by a preliminary investigation of the results, which highlights noteworthy elements of scalar transport within the data set and the need for further investigation of the complex flow field. The study ultimately demonstrates the applicability of magnetic resonance techniques to puff release and dynamic experimental conditions, as well as a method for working with data from phase-locked experiments.
A predictive model of gene expression reveals the role of network motifs in the mating response of yeast
Authors: Pomeroy Amy E. , Peña Matthew I. , Houser John R. , Dixit Gauri , Dohlman Henrik G. , Elston Timothy C. , Errede Beverly
Published: February 2021

Signaling network motifs ensure appropriate transcriptional responses to distinct pheromone dynamics in yeast.
Effects of Regulatory Network Organization and Environment on PmrD Connector Activity and Polymyxin Resistance in
Klebsiella pneumoniae
and
Escherichia coli
Authors: Chen Annie I. , Albicoro Francisco Javier , Zhu Jun , Goulian Mark
Published: February 2021

Polymyxins are a class of cyclic peptides with antimicrobial activity against Gram-negative bacteria. In
Enterobacteriaceae
, the PhoQ/PhoP and PmrB/PmrA two-component systems regulate many genes that confer resistance to both polymyxins and host antimicrobial peptides.
Potent Bispecific Neutralizing Antibody Targeting Glycoprotein B and the gH/gL/pUL128/130/131 Complex of Human Cytomegalovirus
Authors: Su Hang , Ye Xiaohua , Freed Daniel C. , Li Leike , Ku Zhiqiang , Xiong Wei , Gao Peng , Liu Xinli , Montgomery Diana , Xu Weifeng , Espeseth Amy S. , Wang Dai , Ma Ningning , Fu Tong-Ming , Zhang Ningyan , An Zhiqiang
Published: February 2021

Human cytomegalovirus (HCMV) is a ubiquitous pathogen that can cause developmental disorders following congenital infection and life-threatening complications among transplant patients. Potent neutralizing monoclonal antibodies (MAbs) are promising drug candidates against HCMV infection.
PhenoGMM: Gaussian Mixture Modeling of Cytometry Data Quantifies Changes in Microbial Community Structure
Authors: Rubbens Peter , Props Ruben , Kerckhof Frederiek-Maarten , Boon Nico , Waegeman Willem
Published: February 2021

Microorganisms are vital components in various ecosystems on Earth. In order to investigate the microbial diversity, researchers have largely relied on the analysis of 16S rRNA gene sequences from DNA.
Effects of Seasonal Anoxia on the Microbial Community Structure in Demosponges in a Marine Lake in Lough Hyne, Ireland
Authors: Schuster Astrid , Strehlow Brian W. , Eckford-Soper Lisa , McAllen Rob , Canfield Donald E.
Published: February 2021

The oceans have an uncertain future due to anthropogenic stressors and an uncertain past that is becoming clearer with advances in biogeochemistry. Both past and future oceans were, or will be, deoxygenated in comparison to present conditions.
Genetic Modification of
Sodalis
Species by DNA Transduction
Authors: Keller Chelsea M. , Kendra Christopher G. , Bruna Roberto E. , Craft David , Pontes Mauricio H.
Published: February 2021

A large number of economically important insects maintain intimate associations with maternally inherited endosymbiotic bacteria. Due to the inherent nature of these associations, insect endosymbionts cannot be usually isolated in pure culture or genetically manipulated.
Utilisation of poor-quality optical coherence tomography scans: adjustment algorithm from the Singapore Epidemiology of Eye Diseases (SEED) study
Authors: Thakur Sahil , Yu Marco , Tham Yih Chung , Majithia Shivani , Soh Zhi-Da , Fang Xiao Ling , Cheung Carol , Boey Pui Yi , Aung Tin , Wong Tien Yin , Cheng Ching-Yu
Published: February 2021

Purpose

To evaluate the effect of signal strength (SS) on optical coherence tomography (OCT) parameters, and devise an algorithm to adjust the effect, when acceptable SS cannot be obtained.

Methods

5085 individuals (9582 eyes), aged ≥40 years from the Singapore Epidemiology of Eye Diseases population-based study were included. Everyone underwent a standardised ocular examination and imaging with Cirrus HD-OCT. Effect of SS was evaluated using multiple structural breaks linear mixed-effect models. Expected change for increment in SS between 4 and 10 for individual parameter was calculated. Subsequently we devised and evaluated an algorithm to adjust OCT parameters to higher SS.

Results

Average retinal nerve fibre layer (RNFL) thickness showed shift of 4.11 µm from SS of 5 to 6. Above 6, it increased by 1.72 and 3.35 µm to 7 and 8; and by 1.09 µm (per unit increase) above 8 SS. Average ganglion cell-inner plexiform layer (GCIPL) thickness shifted 5.15 µm from SS of 5 to 6. Above 6, increased by 0.94 µm from 7 to 8; and by 0.16 µm (per unit increase) above 8 SS. When compared with reference in an independent test set, the algorithm produced less systemic bias. Algorithm-adjusted average RNFL was 0.549 µm thinner than the reference, while the unadjusted one was 2.841 µm thinner (p<0.001). Algorithm-adjusted and unadjusted average GCIPL was 1.102 µm and 2.228 µm thinner (p<0.001).

Conclusions

OCT parameters can be adjusted for poor SS using an algorithm. This can potentially assist in diagnosis and monitoring of glaucoma when scans with acceptable SS cannot be acquired from patients in clinics.
Impact of undiagnosed type 2 diabetes and pre-diabetes on severity and mortality for SARS-CoV-2 infection
Authors: Vargas-Vázquez Arsenio , Bello-Chavolla Omar Yaxmehen , Ortiz-Brizuela Edgar , Campos-Muñoz Alejandro , Mehta Roopa , Villanueva-Reza Marco , Bahena-López Jessica Paola , Antonio-Villa Neftali Eduardo , González-Lara María Fernanda , Ponce de León Alfredo , Sifuentes-Osornio Jose , Aguilar-Salinas Carlos Alberto
Published: February 2021

Introduction

Diabetes and hyperglycemia are risk factors for critical COVID-19 outcomes; however, the impact of pre-diabetes and previously unidentified cases of diabetes remains undefined. Here, we profiled hospitalized patients with undiagnosed type 2 diabetes and pre-diabetes to evaluate its impact on adverse COVID-19 outcomes. We also explored the role of de novo and intrahospital hyperglycemia in mediating critical COVID-19 outcomes.

Research design and methods

Prospective cohort of 317 hospitalized COVID-19 cases from a Mexico City reference center. Type 2 diabetes was defined as previous diagnosis or treatment with diabetes medication, undiagnosed diabetes and pre-diabetes using glycosylated hemoglobin (HbA1c) American Diabetes Association (ADA) criteria and de novo or intrahospital hyperglycemia as fasting plasma glucose (FPG) ≥140 mg/dL. Logistic and Cox proportional regression models were used to model risk for COVID-19 outcomes.

Results

Overall, 159 cases (50.2%) had type 2 diabetes and 125 had pre-diabetes (39.4%), while 31.4% of patients with type 2 diabetes were previously undiagnosed. Among 20.0% of pre-diabetes cases and 6.1% of normal-range HbA1c had de novo hyperglycemia. FPG was the better predictor for critical COVID-19 compared with HbA1c. Undiagnosed type 2 diabetes (OR: 5.76, 95% CI 1.46 to 27.11) and pre-diabetes (OR: 4.15, 95% CI 1.29 to 16.75) conferred increased risk of severe COVID-19. De novo/intrahospital hyperglycemia predicted critical COVID-19 outcomes independent of diabetes status.

Conclusions

Undiagnosed type 2 diabetes, pre-diabetes and de novo hyperglycemia are risk factors for critical COVID-19. HbA1c must be measured early to adequately assess individual risk considering the large rates of undiagnosed type 2 diabetes in Mexico.
Grandmothers — a neglected family resource for saving newborn lives
Authors: Aubel Judi
Published: February 2021

Across the globe, the well-being of newborns is significantly influenced by the knowledge and practices of family members, yet global health policies and interventions primarily focus on strengthening health services to save newborn lives. Predominant approaches to promote newborn survival in non-western cultures across the Global South are based on a western, nuclear family model and ignore the roles of caregivers within wider family systems, whose attitudes and practices are determined by culturally prescribed strategies. In this paper, I review evidence of a neglected facet of newborn care, the role and influence of senior women or grandmothers.

Based on a family systems frame, I reviewed research from numerous settings in Africa, Asia and Latin America that provides insight into family roles related to newborn care, specifically of grandmothers. I identified primarily published studies which provide evidence of grandmothers’ role as culturally designated and influential newborn advisors to young mothers and direct caregivers. Research from all three continents reveals that grandmothers play similar core roles in newborn care while their culturally specific practices vary. This review supports two main conclusions. First, future newborn research should be conceptualised within a family systems framework that reflects the structure and dynamics of non-western collectivist cultures. Second, newborn interventions should aim not only to strengthen health services but also influential family caregivers, particularly grandmothers and the indigenous social support networks of which they are a part, in order to improve family-level newborn practices and save newborn lives.
Enablers and barriers to workplace breastfeeding in the Armed Forces: a systematic review
Authors: Taylor Hannah
Published: February 2021

Introduction

The UK has no legislation protecting employees’ access to breastfeeding facilities. Without specific breastfeeding policy, provisions to access workplace facilities can be inconsistent and negatively impact employees’ breastfeeding duration, retention and morale, particularly servicewomen who work in varied and demanding military environments. This is an important policy area for the British Army to retain talented and trained soldiers.

Methods

Using Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement principles, PubMed, Embase, CINAHL and Pro-Quest Databases were searched for studies relevant to accessing appropriate breastfeeding facilities in UK workplaces and high-income countries’ Armed Forces. Factors acting as barriers and enablers to accessing facilities were identified. UK government and Armed Forces’ websites were searched for grey literature on existing policies and guidance for accessing facilities.

Results

Barriers and enablers to access from 16 studies were described by three thematic areas: attitudes to breastfeeding, facility provisions and use of facilities. Factors which employers could influence included specific breastfeeding policy, universal workplace education, existence of suitable facilities and individualised breastfeeding plans. The key areas for policy development identified were clearly defined responsibilities; individualised risk assessments and breastfeeding plans; appropriate, but flexible, facility provision and access; signposting of relevant workplace accommodations; and physical fitness provisions.

Conclusions

Five recommendations are presented: development, implementation and evaluation of breastfeeding policy; universal workplace breastfeeding education; the need for breastfeeding risk assessments and plans based on individual breastfeeding practice; written minimal and ideal standards for breastfeeding facilities and access, which considers workplace locations; and exceptions from deployment and physical fitness testing.