bluuebunny/crossref_metadata_2025 huggingface dataset:
Repurposing medical devices as “button” esophagostomy tubes for extended nutritional support
Authors: Craven Melanie D.
Published: November 2021

Background

Esophagostomy tubes (E‐tubes) are widely utilized for extended nutritional support in dogs and cats. Problems associated with their use include the unwieldy excess (10‐20 cm) of external tubing, constant need for neck wraps and necessity for skin sutures, suture tract infection, and tube loss if sutures fail.

Objectives

To evaluate 2 different, low profile (LP) “button” products intended for use in people as enteral (jejunostomy [J] and gastrojejunostomy [G‐J]) feeding tubes for suitability as LP E‐tubes in dogs and cats.

Animals

A young giant breed dog that required extended (>6 months) nutritional and fluid support during recovery from severe neurological illness with protracted adipsia, anorexia, and dysphagia.

Methods

Prospective evaluation of 2 commercially available LP feeding devices after placement of a standard E‐tube. An LP J‐tube and an LP G‐J tube were assessed in consecutive 4‐week trials, for tube retention, patient comfort, stoma health, and functionality.

Results

Both products performed extremely and equally well as LP E‐tubes in this clinical patient, enhancing patient freedom and comfort by eliminating external tubing, skin sutures, and bandaging. The dual port G‐J tube allows medication delivery (eg, sucralfate) to the entire esophagus, but for safety alone (ie, to avoid aspiration), the single port J‐tube appears the best device for client‐owned patients.

Conclusions and Clinical Importance

The LP enteral feeding tubes from the human medical field can be successfully used as LP E‐tubes in dogs and cats, offering superior patient comfort, with no obvious detriment to the patient and main drawback of higher cost.
The fragmentation of public administration: Differentiated and decentered governance in the (dis)United Kingdom
Authors: Elliott Ian C. , Bottom Karin A. , Carmichael Paul , Liddle Joyce , Martin Steve , Pyper Robert
Published: November 2021

This paper analyzes a UK polity that is characterized by fragmentation, differentiation, and decentered governance which is evident at multiple layers of public policy and administration. The development of devolved governments as well as ongoing debates around regional and local governance have created increasingly fragmented places. The intensification of policies associated with the new public management has fragmented the provision of public services. And the absence of a common approach to professional development has led to growing fragmentation of public service workers from different professions and sectors. We argue that these trends reflect many of the aspects of an advanced or late‐stage new public governance. This is ripe territory for further research and demonstrates that UK public administration continues to have much to offer to international scholars. It also raises important questions about what forms of public administration might emerge next.
Reflecting on over 100 years of public administration education
Authors: Farrell Catherine , Hatcher William , Diamond John
Published: November 2021

Public administration education has an interesting history rooted in numerous scholarly disciplines, such as sociology, political science, economics, and engineering. The article reflects on the last 100 years of scholarship on public administration education, starting with an article on the topic in the first issue of Public Administration in 1923. We provide a concise review focused on the development of public administration education over this time. Next, we discuss scholarship in top journals on public administration education, Journal of Public Affairs Education and Teaching Public Administration. We use Denhardt's (2001) big questions in public administration education as a framework to examine this scholarship. We conclude by discussing the future of public administration education and advocating a community‐based approach to pedagogy practice and research in the field.
A multiplex PCR marker distinguishes between a series of four LanFTc1 alleles regulating flowering time in narrow‐leafed lupin (Lupinus angustifolius)
Authors: Taylor Candy M. , van der Zanden Julian , Saradadevi Renu , Berger Jens D. , Kamphuis Lars G. , Pradhan Aneeta , Sharma Darshan , Nelson Matthew N. , Cowling Wallace A.
Published: November 2021

We designed and validated a new multiplex PCR marker which discriminates between four insertion/deletion (INDEL) alleles in the 5′ regulatory region of a major flowering time gene in Lupinus angustifolius, LanFTc1. The four INDEL alleles were the wild‐type allele (ku) in variety ‘Geebung’ (G), a 1,208‐bp deletion allele in accession P22660 (P), a 1,423‐bp deletion allele (Ku) in variety ‘Tanjil’ (T) and a 5,162‐bp deletion allele (Jul) in variety ‘Krasnolistny’ (K). F2 PCR marker genotypes segregated as expected in populations K × G, K × T, P × G and P × T. Heritability of flowering times based on F2:3 parent:offspring correlation was high in K × G (0.81 ± 0.09), P × G (0.76 ± 0.10) and P × T (0.81 ± 0.11) but low in K × T (−0.04 ± 0.15) due to similar early‐flowering phenotypes produced by Ku and Jul. Progeny homozygous for the 1,208‐bp deletion allele resulted in a unique array of mid‐season phenology in the F2, F3 and F4 generations, which may improve agronomic adaptation. This multiplex PCR marker will improve the efficiency of introgression of the new INDELs into future lupin varieties.
Autogenous vaccination in aquaculture: A locally enabled solution towards reduction of the global antimicrobial resistance problem
Authors: Barnes Andrew C. , Rudenko Oleksandra , Landos Matt , Dong Ha Thanh , Lusiastuti Angela , Phuoc Le Hong , Delamare‐Deboutteville Jerome
Published: November 2021

Antimicrobial resistance is a global public health crisis with attention focussed on food supply as part of the ‘One Health’ integration of veterinary, environmental and public health. Aquaculture has been the fastest growing livestock sector in recent decades and is critical to nutritional security in many low‐ and middle‐income countries (LMIC). With ready access to antibiotics and limited availability of veterinary support, disease control with antibiotics is poorly informed, often unrecorded and high in many countries where aquaculture growth is fastest. Vaccination of fish in LMIC with locally produced autogenous vaccines against bacterial diseases may provide a locally driven, cost‐effective means of reducing antibiotic use, replicating the successes achieved during the growth of Norway's aquaculture industry. Autogenous vaccines, as part of an informed veterinary health programme, have several advantages in terms of intellectual property, efficacy and flexibility. We consider access to fish vaccines in example countries of high aquaculture importance, including Thailand, Vietnam and Indonesia. We contrast the success of antimicrobial reduction in Norwegian salmon aquaculture with the high antibiotic use in the Chilean industry where vaccines are available, finding that regulation, planning, husbandry and environmental problems may increase disease incidence and severity. We identify technical, bureaucratic and infrastructural transitions that could facilitate implementation of autogenous vaccination in LMIC aquaculture against challenging socio‐economic and environmental backgrounds. The benefits of autogenous vaccination to animal welfare, transboundary biosecurity, local farmer and industry economics, and to public health, favour implementation in aquaculture as a locally enabled solution to the global problem of antimicrobial resistance.
Small Area Estimation of Poverty Under Structural Change
Authors: Lange Simon , Pape Utz Johann , Pütz Peter
Published: November 2021

Small area estimation is an important tool to produce estimates of poverty for regions with low or zero sample sizes. Estimates are typically obtained by combining a consumption survey reporting on poverty and a census providing the spatial disaggregation. This paper discusses an updating method that produces up‐to‐date small area estimates when only a dated census and a more recent survey are available and predictors are subject to drift over time, a situation commonly encountered in practice. Instead of using survey variables to explain consumption in the survey, the updating approach uses only variables constructed from the census. The proposed estimator has fewer data requirements and weaker assumptions than common small area estimators. Applications to simulated data and to poverty estimation in Brazil show an overall good performance, but also imply the importance of examining practical challenges in real‐world applications.
Bibenzyl synthesis in Cannabis sativa L.
Authors: Boddington Kelly F. , Soubeyrand Eric , Van Gelder Kristen , Casaretto José A. , Perrin Colby , Forrester Taylor J.B. , Parry Cameron , Al‐Abdul‐Wahid M. Sameer , Jentsch Nicholas G. , Magolan Jakob , Bozzo Gale G. , Kimber Matthew S. , Rothstein Steven J. , Akhtar Tariq A.
Published: November 2021

This study focuses on the biosynthesis of a suite of specialized metabolites from Cannabis that are known as the ‘bibenzyls’. In planta, bibenzyls accumulate in response to fungal infection and various other biotic stressors; however, it is their widely recognized anti‐inflammatory properties in various animal cell models that have garnered recent therapeutic interest. We propose that these compounds are synthesized via a branch point from the core phenylpropanoid pathway in Cannabis, in a three‐step sequence. First, various hydroxycinnamic acids are esterified to acyl‐coenzyme A (CoA) by a member of the 4‐coumarate‐CoA ligase family (Cs4CL4). Next, these CoA esters are reduced by two double‐bond reductases (CsDBR2 and CsDBR3) that form their corresponding dihydro‐CoA derivatives from preferred substrates. Finally, the bibenzyl backbone is completed by a polyketide synthase that specifically condenses malonyl‐CoA with these dihydro‐hydroxycinnamoyl‐CoA derivatives to form two bibenzyl scaffolds: dihydropiceatannol and dihydroresveratrol. Structural determination of this ‘bibenzyl synthase’ enzyme (CsBBS2) indicates that a narrowing of the hydrophobic pocket surrounding the active site evolved to sterically favor the non‐canonical and more flexible dihydro‐hydroxycinnamoyl‐CoA substrates in comparison with their oxidized relatives. Accordingly, three point mutations that were introduced into CsBBS2 proved sufficient to restore some enzymatic activity with an oxidized substrate, in vitro. Together, the identification of this set of Cannabis enzymes provides a valuable contribution to the growing ‘parts prospecting’ inventory that supports the rational metabolic engineering of natural product therapeutics.
Providing whole blood for an urban paramedical ambulance system
Authors: Sayre Michael R. , Yang Betty Y. , Murphy David L. , Counts Catherine R. , Dang Maika , Ubaldi Peter , Tuott Erin E. , Hess John R.
Published: November 2021

Introduction

Hemorrhage is the second leading cause of death among urban trauma patients, and the provision of prehospital blood‐based resuscitation can be lifesaving. We developed an efficient system to support blood‐based resuscitation by an urban advanced life support ambulance system.

Methods

We worked with our state health department for permission for fire department paramedics to initiate blood transfusion and built protocols for field whole blood resuscitation. Our regional trauma center transfusion service provided 2 units of O positive, low‐titer, leukoreduced whole blood in an internally monitored and sealed ice box weighing 10 pounds to the fire department paramedic supervisor. When notified, the supervisor transported the blood to the sites of anticipated need. Total blood use and wastage were recorded.

Results

Following two public hearings, we obtained state‐wide approval for the initiation of emergency uncrossmatched blood transfusion by paramedics. Over a 1‐year period beginning August 27, 2019, 160 units of whole blood were made available for use, and 51 units were transfused to 39 patients, 30 of whom were trauma patients. Other recipients include patients in shock from massive gastrointestinal, peripartum, or other suspected bleeding. Unused units were returned to the providing transfusion service after 1 week and used for hospital patient care without loss. The estimated cost of providing blood per mission was $0.28 and per patient transfused was $1138.

Conclusions

With appropriate attention to detail, it is possible to provide whole blood to an urban paramedical ambulance system with efficient blood component usage, minimal blood wastage, and low cost.
Air Flow Acceleration Effect on Water Droplet Flow Behavior in Solid Rocket Motor
Authors: Abousabae Mohamed , Amano Ryoichi S.
Published: November 2021

Investigating the mechanical erosion of the solid rocket motor convergent-divergent (C-D) nozzle is essential to overcome its development barriers. Consequently, the break-up mechanism of the aluminum oxide agglomerates was studied to determine the influence of the exhaust gas flow acceleration during the flight. Water and air flows were used as a substitute for aluminum oxide and exhaust gases. Experiments were conducted at different water flowrates and constant air velocity, where the results were used to validate a numerical model. The results revealed an excellent acceptance between the numerical, the experimental data (6–19%), and the effect of increasing the water flowrate on the break-up mechanism. The validated numerical model was further used to study the airflow acceleration impact on the break-up process. It was found that applying acceleration to the airflow subjects the water surface to rapid and sudden changes in the relative velocity between the gas and liquid, thus separating more water fragments from the primary liquid. In other words, it enhances the break-up process by reducing the average diameter with a range from 6.5% to 9% compared to the no-acceleration case and increasing the average droplets’ number (8.5–17%).
Mass Advection–Diffusion in Creeping Flow Through an Orifice Plate: A Model for Nanoporous Atomically Thin Membranes
Authors: Atwal Harpreet K. , Wong Anika O. K. , Boutilier Michael S. H.
Published: November 2021

Continuum transport equations are commonly applied to nanopores in atomically thin membranes for simple modeling. Although these equations do not apply for nanopores approaching the fluid or solute molecule size, they can be reasonably accurate for larger nanopores. Relatively large graphene nanopores have applications in small particle filtration and appear as unwanted defects in large-area membranes. Solute transport rates through these nanopores determine the rejection performance of the membrane. Atomically thin membranes commonly operate in a regime where advection and diffusion both contribute appreciably to transport. Solute mass transfer rates through larger nanopores have previously been modeled by adding continuum estimates for pure diffusion and pure advection through an infinitesimally thick orifice plate, as if the separate contributions were independent. We show here that estimating the transport rate in this way is accurate to within 30%. We further derive an expression for the net mass transfer rate in advection–diffusion through an infinitesimal thickness orifice plate at low Reynolds numbers that is accurate to within 1% for positive Péclet numbers (where diffusion is in the same direction as advection) and applies for negative Péclet numbers as well. Based on our expression, we devise an equation for the net mass transfer rate in creeping flow through orifice plates of arbitrary thickness that matches finite volume calculations to within 3% for positive Péclet numbers. These simple but accurate analytical equations for mass transfer rates in creeping flow through an orifice plate are useful tools in constructing approximate transport models.
An Investigation of the Influence of Disciplinary Distance in Interdisciplinary Education Through Faculty’s Experience
Authors: Feng Xiaoqi , Hölttä-Otto Katja
Published: November 2021

Interdisciplinary initiatives have been encouraged in higher education curricula, especially in mechanical engineering as a result of the industry’s calls for talent with multidisciplinary competencies to solve complex real-world problems. However, disciplinary distance, due to disciplinary differences, poses great challenges in interdisciplinary teaching and learning. How can interdisciplinary faculty members collaborate effectively in teaching? How can students with different backgrounds learn significant knowledge? Collaboration for interdisciplinary education across disciplines is challenging, as co-teachers are usually affiliated with different departments or even schools, and they tend to speak different disciplinary languages and value different disciplinary cultures. Similarly, students in engineering design teams come from different backgrounds. Consistent with Klein’s concepts of Wide Interdisciplinarity and Narrow Interdisciplinarity, we propose the concept of disciplinary distance to present the research findings of disciplinary differences and their implications on interdisciplinary teaching and learning. This paper presents a qualitative analysis of disciplinary distance, as manifested in interdisciplinary education from faculty members’ perspectives. From 13 semi-structured interviews, we find that disciplinary distance plays a vital role in interdisciplinary teaching and learning. It influences teamwork — both in co-teacher teams and student teams. Interdisciplinary course content and interdisciplinary co-teacher teams can also create a wide disciplinary distance that serves as a barrier for interdisciplinary learning. We further find that interdisciplinary collaboration may help to mediate the negative impact of disciplinary distance.
Application of Smart, Swarm and Small UAV’s for Methane Emission Reduction
Authors: An Di , Chen YangQuan
Published: November 2021

In this paper, we present the research challenges and opportunities in methane reduction within the smart, swarm, and small Unmanned Aircraft Vehicles (UAVs). Methane is a kind of greenhouse gas (GHG) that contributes to global temperature warming and climate changes through trapping infrared radiation in the atmosphere. The related literature of the current methane measurements and suppression of methane approaches are reviewed, and they are often limited due to the maintenance, installment, and calibration requirements of these sensing systems. To overcome these limitations, an emerging technology, UAVs, as considered mobile sensors to measure and control methane emissions, would extend detection range and acquired fine-grained information that helps to capture methane emissions in a much effective way. However, many challenges need to be explored: In the sensing field, the improvement of positive methane detection rate, which contradicts the methane diffusion in the atmosphere. The swarm UAVs for optimal coverage control, the substances of suppression methane usage, and reaction time in the control field. Different methane diffusion disturbances types could affect the strategy of swarming UAVs movement, especially under wind field. Besides, we also talk about the impact of methane reduction and related technology development for the future. Finally, we concluded that the Digital Twin would be the next methane reduction revolution to prevent potential global warming.
Real-Time Measurement Method of Rail Vehicle Wheel Flange Wear Using Inductive and Temperature Sensors
Authors: Ndodana Njaji James , Nkundineza Celestin
Published: November 2021

Railway systems are expected to be in their most safe state ensuring safe operations of trains. The contact between rail and wheel is one of the most fundamental aspects in railway systems. Therefore, instruments and measurement systems that give critical information about operating railway systems are expected to work efficiently and effectively. Previous research on using inductive displacement sensor for wheel flange wear measurement has focused on the light rail vehicles, and considered effect of temperature negligible, as opposed to mainline vehicle where the wheel temperature variation is large. Also, the filtering of noises has been done using non-real time data. This paper focuses on the real-time measurement system for freight vehicle wheel flange wear by fusing measurement data from inductive displacement and thermocouple sensors, and filtering of the noises. A CAD model of the sensor support fixed on the bogie frame is presented. Several experimental measurements are carried in the lab on a moving disk heated at different temperatures. Then multiple regression analysis of the data is carried out to come up with the measurement model equation. This equation is used for calibration in LabVIEW program interfaced with data acquisition system for real time measurement. Experimental results show effect of temperature on the inductive sensor measurement data. This effect is taken into account to quantify the clearance between the disk and the sensor tip. The precision and accuracy are determined to be 0.06 Volts and 0.03 mm, respectively. This system is expected to enhance the real-time and/or online monitoring of the safety of rail vehicles. Also, it can be integrated with Automatic Train Protection (ATP) and the detection of track lateral irregularities from the wheel flange real time measurement data.
The Importance of the Mode II Term on the Analysis of Angled Cracks in Unidirectional Carbon Fiber Composites
Authors: Biddlecom Jacob , Pataky Garrett J.
Published: November 2021

Carbon fiber reinforced polymers (CFRP) have been used in many high-performance applications where strength to weight ratio is an important characteristic. The goal of this research was to analyze the effects of Mode II, also known as shear loading, on the displacement fields surrounding a crack for unidirectional carbon fiber composites. Tensile and fatigue experiments were conducted on angled unidirectional CFRP coupled with digital image correlation (DIC) to analyze the full field displacement. Angled CFRP cracks experienced mixed mode loading which required addition insight due to the complex stresses on the fiber/matrix interface. The experimental displacement fields acquired from DIC were used as inputs for an anisotropic regression analysis to determine the mode I and mode II stress intensity factor ranges. The results from the regression analysis were used to predict the displacement fields around a crack. When comparing the experimental results with the predicted results, the inclusion of Mode II increased the agreement between predicted and experimental displacement fields around a crack tip for two different fiber orientation angles. Crack growth rate analysis and analytical stress intensity factor ranges were used to expand on the agreement of the results as well as bring to light CFRP specific fracture mechanisms that lead to disagreements.
Multi-Sensor Data Fusion for Rotating Machinery Fault Diagnosis Using Residual Convolutional Neural Network
Authors: Xie Tingli , Huang Xufeng , Choi Seung-Kyum
Published: November 2021

Diagnosis of mechanical faults in the manufacturing systems is critical for ensuring safety and saving cost. With the development of data transmission and sensor technologies, the measuring systems can easily acquire multi-sensor and massive data. The traditional fault diagnosis methods usually depend on the features extracted by experts manually. The feature extraction process is usually time-consuming and laborious, which has a significant impact on the final results. Although Deep-Learning (DL) provides an end-to-end way to address the drawbacks of traditional methods, it is necessary to do deep research on an intelligent fault diagnosis method based on Multi-Sensor Data and Data Fusion. In this project, a novel intelligent diagnosis method based on Multi-Sensor Data Fusion and Convolutional Neural Network (CNN) is explored, which can automatically extract features from raw signals and achieve superior recognition performance. Firstly, a Multi-Signals-to-RGB-Image conversion method based on Principal Component Analysis (PCA) is applied to fuse multi-signal data into three-channel RGB images, which can eliminate the effect of handcrafted features and obtain the feature-level fused information. Then, the improved CNN with residual networks and the Leaky Rectified Linear Unit (LReLU) is defined and trained by the training samples, which can balance the relationship between computational cost and accuracy. After that, the testing data are fed into CNN to obtain the final diagnosis results. Two datasets, including the KAT bearing dataset and Gearbox dataset, are conducted to verify the effectiveness of the proposed method. The comprehensive comparison and analysis with widely used algorithms are also performed. The results demonstrate that the proposed method can detect different fault types and outperform other methods in terms of classification accuracy. For the KAT bearing dataset and Gearbox dataset, the proposed method’s average prediction accuracy is as high as 99.99% and 99.98%, which demonstrates that the proposed method achieves more reliable results than other DL-based methods.
Tolerancing for an Apple Pie
Authors: Campbell Joshua Roland , Hazelrigg George A.
Published: November 2021

Tolerancing began with the notion of limits imposed on the dimensions of realized parts both to maintain functional geometric dimensionality and to enable cost-effective part fabrication and inspection. Increasingly however, component fabrication depends on more than part geometry as many parts are fabricated as a result of a “recipe” rather than dimensional instructions for material addition or removal. Referred to as process tolerancing, this is the case, for example, with IC chips. There has emerged an extensive literature on both geometric and process tolerancing, much of it with a focus on tolerance optimization. In the case of tolerance optimization, a typical objective is cost minimization while achieving required functionality or “quality.” This paper takes a different look at tolerances, suggesting that rather than ensuring merely that parts achieve a desired functionality at minimum cost, the underlying goal of product design is to make money, and tolerances comprise additional design variables amenable to optimization in a decision theoretic framework. We recognize that a theory of tolerancing must apply equally to processes and procedures, and note that tolerances introduce additional product attributes that relate to product characteristics such as consistency, quality, reliability and durability. These important attributes complicate the computation of the expected utility of candidate designs, requiring additional computational steps for their determination. Nonetheless, their proper consideration is an important element in the evaluation of product design alternatives. The resulting theory of tolerancing presented here is illustrated using the example of tolerancing for an apple pie.
Conformal Topology Optimization of Heat Conduction Problems on Manifolds Using an Extended Level Set Method (X-LSM)
Authors: Xu Xiaoqiang , Chen Shikui , Gu Xianfeng David , Wang Michael Yu
Published: November 2021

In this paper, the authors propose a new dimension reduction method for level-set-based topology optimization of conforming thermal structures on free-form surfaces. Both the Hamilton-Jacobi equation and the Laplace equation, which are the two governing PDEs for boundary evolution and thermal conduction, are transformed from the 3D manifold to the 2D rectangular domain using conformal parameterization. The new method can significantly simplify the computation of topology optimization on a manifold without loss of accuracy. This is achieved due to the fact that the covariant derivatives on the manifold can be represented by the Euclidean gradient operators multiplied by a scalar with the conformal mapping. The original governing equations defined on the 3D manifold can now be properly modified and solved on a 2D domain. The objective function, constraint, and velocity field are also equivalently computed with the FEA on the 2D parameter domain with the properly modified form. In this sense, we are solving a 3D topology optimization problem equivalently on the 2D parameter domain. This reduction in dimension can greatly reduce the computing cost and complexity of the algorithm. The proposed concept is proved through two examples of heat conduction on manifolds.
Exploring Empathy in Student Design Teams
Authors: Apfelbaum Meredith , Sharp Kendra , Dong Andy
Published: November 2021

The objective of this paper is to develop a methodology to better understand behavioral empathy in the design process for the purpose of addressing user needs. To accomplish this, content analysis was conducted on undergraduate student assignments that documented group projects designing a consumer product. Using qualitative data analysis, the assignments and presentations were coded for their levels of behavioral empathy, using a scale that applied psychology and design theories. The Interpersonal Reactivity Index was administered to the students to assess their trait empathy. Results from these two analyses showed little connection between levels of behavioral empathy and self-assessed trait empathy of the student groups. The student assignments did reveal empathic waves that demonstrated comprehension and application of expressed user needs, evidenced by ascending and descending the empathy scale. These results indicate that is it not trait empathy that leads to empathic design, but rather applied empathy in the design process; developing internal empathy is not sufficient if it does not effectively translate user needs to technical requirements in the final design.
“No, We’re Not!” the Classification and Impact of Blocking Behavior in Design Team Meetings
Authors: Mitchell John , Henderson Daniel , Halleran Grace , Singh Aditya , Jablokow Kathryn , Sonalkar Neeraj , Edelman Jonathan
Published: November 2021

This paper proposes a framework through which emergent disagreements during design team meetings may be classified by their tendency to reinforce or challenge the status quo. We investigate the use of the framework in measuring the effects of these disagreements on team productivity. The Interaction Dynamics Notation (IDN) [1] provides the basis for identifying disagreements through blocking behavior. Kirton’s Adaption-Innovation (A-I) Theory [2] is used to classify the style of a Block as Adaptive (status quo-preserving) or Innovative (status quo-challenging). Emergent disagreements like Blocks are potentially risky during team meetings, because they obstruct the flow of discussion. However, certain styles of Blocks, as classified using A-I Theory, may be better suited to idea generation and thus, be worth the risk.

This paper addresses the following questions: (1) Can IDN Blocks be reliably classified using A-I Theory constructs? (2) How do different styles of Blocks impact productivity (e.g., the generation of ideas) during design meetings? A set of 104 Blocks observed in 14 academic teams during design ideation sessions was coded using the proposed framework and reliably determined to be Adaptive, Innovative, or Neither. Blocks were not entirely inhibitory and led to new design ideas under certain conditions. Neither Adaptive nor Innovative Blocks led to more efficient generation of ideas. Innovative Block sequences had greater variance in length than Adaptive Block sequences, while Deflected Blocks more frequently led to idea generation than Overcome or Unresolved Blocks. This research has implications for the productivity of design teams in their problem solving and decision making across settings in academia and industry.
Design and Analysis of a Contact-Aided Variable Stiffness Flexure Hinge (CVSFH)
Authors: Dai Shenyuan , Qiu Lifang , Chen Qichao , Li Yanlin
Published: November 2021

Flexure hinges are the basis of compliant mechanisms. The stiffness is one of the important indexes to evaluate the performance of a flexure hinge, and the rotation angle when the stiffness changes affects its motion characteristics. Thus, based on the constant rectangular cross-section flexure hinge and contact interaction, this paper proposed a contact-aided variable stiffness flexure hinge (CVSFH). With the deformation under an external load, the contact interaction with different parts of the CVSFH itself can achieve the purpose of variable stiffness. The equivalent mechanical model is built and the theoretical equation of the stiffness is given. CVSFHs with different dimensions are designed, and a finite element analysis (FEA) is done. The FEA results of the design examples are coincide with the theoretical results, which verifies the feasibility of the design and the correctness of the theoretical equation.
A Machine Learning Method for State of Charge Estimation in Lead-Acid Batteries for Heavy-Duty Vehicles
Authors: Luciani Sara , Feraco Stefano , Bonfitto Angelo , Tonoli Andrea , Amati Nicola , Quaggiotto Maurizio
Published: November 2021

In the automotive framework, an accurate assessment of the State of Charge (SOC) in lead-acid batteries of heavy-duty vehicles is of major importance. SOC is a crucial battery state that is non-observable. Furthermore, an accurate estimation of the battery SOC can prevent system failures and battery damage due to a wrong usage of the battery itself. In this context, a technique based on machine learning for SOC estimation is presented in this study. Thus, this method could be used for safety and performance monitoring purposes in electric subsystem of heavy-duty vehicles. The proposed approach exploits a Genetic Algorithm (GA) in combination with Artificial Neural Networks (ANNs) for SOC estimation. Specifically, the training parameters of a Nonlinear Auto-Regressive with Exogenous inputs (NARX) ANN are chosen by the GA-based optimization. As a consequence of the GA-based optimization, the ANN-based SOC estimator architecture is defined. Then, the proposed SOC estimation algorithm is trained and validated with experimental datasets recorded during real driving missions performed by a heavy-duty vehicle. An equivalent circuit model representing the retained lead-acid battery is used to collect the training, validation and testing datasets that replicates the recorded experimental data related to electrical consumers and the cabin systems or during overnight stops in heavy-duty vehicles. This article illustrates the architecture of the proposed SOC estimation algorithm along with the identification procedure of the ANN parameters with GA. The method is able to estimate SOC with a low estimation error, being suitable for deployment on common on-board Battery Management Systems (BMS).
LSTM-Enabled Level Curve Tracking in Scalar Fields Using Multiple Mobile Robots
Authors: Parikh Kunj J. , Wu Wencen
Published: November 2021

In this work, we investigate the problem of level curve tracking in unknown scalar fields using a limited number of mobile robots. We design and implement a long short term memory (LSTM) enabled control strategy for a mobile sensor network to detect and track desired level curves. Based on the existing work of cooperative Kalman filter, we design an LSTM-enhanced Kalman filter that utilizes the sensor measurements and a sequence of past fields and gradients to estimate the current field value and gradient. We also design an LSTM model to estimate the Hessian of the field. The LSTM enabled strategy has some benefits such as it can be trained offline on a collection of level curves in known fields prior to deployment, where the trained model will enable the mobile sensor network to track level curves in unknown fields for various applications. Another benefit is that we can train using larger resources to get more accurate models, while utilizing a limited number of resources when the mobile sensor network is deployed in production. Simulation results show that this LSTM enabled control strategy successfully tracks the level curve using a mobile multi-robot sensor network.
A Subspace-Inclusive Sampling Method for the Computational Design of Compositionally Graded Alloys
Authors: Allen Marshall , Kirk Tanner , Malak Richard , Arroyave Raymundo
Published: November 2021

Compositionally graded alloys, a special class of functionally graded materials (FGMs), utilize localized variations in composition within a single metal part to achieve higher performance than traditional single-material parts. In previous work [1], the authors presented a computational design methodology that avoids common issues which limit a gradient alloy’s usefulness or feasibility, such as deleterious phases or properties, and also optimizes gradients for performance objectives. However, the previous methodology only samples the interior of a composition space, meaning designed gradients must include all elements in the space at every step in the gradient. Because the addition of even a small amount of an alloying element can introduce a new deleterious phase, this characteristic often neglects potentially simpler solutions to otherwise unsolvable problems and, consequently, discourages the addition of new elements to the state space. The present work improves upon the previous methodology by introducing a sampling method that includes subspaces with fewer elements in the design search. The new sampling method samples within an artificial expanded form of the state space and projects samples outside the true region to the nearest true subspace. This method is evaluated first by observing the distribution of samples in each subspace of a 2-D, 3-D, and 4-D state space. Next, a parametric study in a synthetic 2-D problem compares the performance of the new sampling scheme to the previous methodology. Lastly, the updated methodology is applied to design a gradient from stainless steel to equiatomic NiTi that has practical uses such as embedded shape memory actuation and for which the previous methodology fails to find a feasible path.
Modal Analysis to Interpret Localization Phenomena in Two Nonlinear Tuned Mass Dampers
Authors: Harata Yuji , Ikeda Takashi
Published: November 2021

This study investigates localization phenomena in two identical nonlinear tuned mass dampers (TMDs) installed on an elastic structure, which is subjected to external, harmonic excitation. In the theoretical analysis, the mode shapes of the system are determined, and the modal equations of motion are derived using modal analysis. These equations are demonstrated as forming an autoparametric system in which external excitation directly acts on the first and third vibration modes, whereas the second vibration mode is indirectly excited due to the nonlinear coupling with the other modes. Van der Pol’s method is employed to obtain the frequency response curves for both physical and modal coordinates. The two TMDs vibrate in phase for the first and third modes, but vibrate out of phase for the second mode. Consequently, when all modes appear, the two TMDs may vibrate at different amplitudes, i.e., localization phenomena may occur because the TMD motions are expressed by the summation of motions for all modes. The numerical calculations clarify that the localization phenomena may occur in the two TMDs when all three modes appear simultaneously. Moreover, there are two steady-state solutions of the harmonic oscillations for the second mode with identical amplitudes; however, their phases differ by π. Hence, which TMD vibrates at higher amplitudes depends on which of these two steady-state solutions for the phase.
Measuring Designers’ Empathic Understanding of Users by a Quick Empathic Accuracy (QEA)
Authors: Li Jie , Surma-aho Antti , Hölttä-Otto Katja
Published: November 2021

Empathy is an essential ability for designers to step into users’ shoes and potentially discover their latent needs. However, although empathy helps designers to better understand users, the degree to which designers can actually understand them remains unclear. Consequently, it is essential to measure the accuracy of designers’ empathic understanding. In our previous work, we have adopted an experimental procedure from psychology to quantify designers’ empathic accuracy. However, the measure as such is time-consuming. Therefore, we attempted to shorten the experimental time while retaining the validity of the measure. This paper reports on the process of shortening the measure and compares the original instrument with the shortened one. The data collected from the shortened instrument shows excellent internal consistency and between subject variance and is able to produce similar results to the original longer measure.
Direct Longitudinal Force Feedback for High-Performance Vehicle Dynamics Control Systems
Authors: Riva Giorgio , Mozzarelli Luca , Corno Matteo , Formentin Simone , Savaresi Sergio M.
Published: November 2021

State of the art vehicle dynamics control systems do not exploit tire road forces information, even though the vehicle behaviour is ultimately determined by the tire road interaction. Recent technological improvements allow to accurately measure and estimate these variables, making it possible to introduce such knowledge inside a control system. In this paper, a vehicle dynamics control architecture based on a direct longitudinal tire force feedback is proposed. The scheme is made by a nested architecture composed by an outer Model Predictive Control algorithm, written in spatial coordinates, and an inner longitudinal force feedback controller. The latter is composed by four classical Proportional-Integral controllers in anti-windup configuration, endowed with a suitably designed gain switching logic to cope with possible unfeasible references provided by the outer loop, avoiding instability. The proposed scheme is tested in simulation in a challenging scenario where the tracking of a spiral path on a slippery surface and the timing performance are handled simultaneously by the controller. The performance is compared with that of an inner slip-based controller, sharing the same outer Model Predictive Control loop. The results show comparable performance in presence of unfeasible force references, while higher robustness is achieved with respect to friction curve uncertainties.
Surface Functionalization of Silicon MEMS Biochemical Sensors for the Detection of Foodborne Pathogens
Authors: Khalil Bhuiyan Md Ebrahim , Smith Dustin , Voss Eric J. , Wei Chin-Chuan , Shavezipur Mohammad
Published: November 2021

This work presents the surface modification of silicon chips as a platform for silicon-based biosensors with applications aiming for the detection of foodborne bacteria in aqueous solution. The detection requires high selectivity as the solution may contain a variety of biological species, which affect the outcome of the sensing process. The silicon surface is functionalized by a self-assembled monolayer (SAM) with thiol groups followed by immobilizing a thiol-linked DNA aptamer. The DNA aptamer used in this work has reported to recognize a biological species, E. coli ATCC 25922. The presence of DNA aptamer on the sensor surface allows the capture of the specific E. coli cells on the surface, while other potential biological (and chemical) species would not attach to the sensor surface, thus improving the selectivity of the sensor. The uniform formation of the SAM on the surface is an important step toward uniformly coating the sensor surface with the desired DNA aptamer. The SAM is created on the silicon surface by surface modification with the MPTS (3-mercaptopropyl trimethoxy silane) solution. Then the aptamer DNA solution is applied as droplets on the chip followed by a cure process. The attachment of the SAM and DNA aptamers are verified by atomic force microscopy (AFM). The surface functionalization presented in this work can be used for sensors made of silicon coated with a thin layer of native oxide, and can be adopted for detection of other cells and biological agents using the proper SAM and DNA aptamer.
Comparison of Neural Network-Based Pose Estimation Approaches for Mobile Manipulation
Authors: Chowdhury Arindam B. , Li Juncheng , Cappelleri David J.
Published: November 2021

In this paper, we present two distinct neural network-based pose estimation approaches for mobile manipulation in factory environments. Synthetic datasets, unique to the factory setting, are created for neural network training in each approach. Approach I uses a CNN in conjunction with RBG and depth images. Approach II uses the DOPE network along with RGB images, CAD dimensions of the objects of interest, and the PnP algorithm. Each approach is evaluated and compared across pipeline complexity, dataset preparation resources, robustness, platform and run-time resources, and pose accuracy for manipulation planning. Finally, recommendations for when to use each method are provided.
The Use of Analogies and the Design Brief Information: Impact on Creative Outcomes
Authors: Koronis Georgios , Casakin Hernan , Silva Arlindo , Siew Jing Wen William
Published: November 2021

This study is aimed at ways to assess and improve design students’ creative outcomes and assist educators in crafting design briefs for design studios. The procedure entails a controlled yet analytical experiment in a university setting intended to test the potential of using analogical thinking to enhance the Novelty and Usefulness of design solutions. The control group received a brief that contained stimuli in the form of typical examples without instructions to use analogies. A second group was provided with a brief including stimuli elicited by text representations in the form of word pairs, and instructions to use textual analogies. The last group received the same stimuli as the other groups above; however, with instructions to identify negative features before using textual analogies.

One hundred and seven first-year undergraduate students took part in the study. The results demonstrated that design briefs with specific instructions to use textual-based analogies contributed to highly novel outcomes. However, when analogies were elicited by statements concerning negative issues of the design task, students were able to produce more useful outcomes. We suggest that textual-based analogies can be employed as a good in-class pedagogical tool for improving novice designers’ creative outcomes overall.
An Effective Approach to Model Parallel Robots With Flexible Links
Authors: Stefano Brillarelli , Palpacelli Matteo-Claudio
Published: November 2021

This paper is focused on the development of an effective hardware and software architecture that is useful to improve the performance of slender parallel manipulators. The latter can perform high acceleration in fast pick and place applications, but their features can be also exploited in more advanced operations, where path following is a central issue. A simple and effective approach to model the elastodynamic behavior of flexible parallel manipulator is proposed, conceived to be fast and easy to implement in model-based control schemes. Moreover, a workbench architecture based on camera acquisitions is essential to calibrate the elastodynamic model and provide all the required information that are needed to improve path following of flexible mechanims.