bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characterization of Nanoporous Polyvinylidene Fluoride (PVDF) Sensors Under Tensile Loading
Authors: Gao Zhaolin , Danley Matthew J. , Kloster Jack T. , Lai Victor K. , Zhao Ping 
Published: October 2021

Abstract
A Polyvinylidene Fluoride (PVDF) sensor with integrating nanoporous structures was developed and fabricated to improve its piezoelectric effect. The sensor samples with different porosities ranging from 3.3% to 42.0% were made. The porosity effect on the piezoelectric coefficient d31 of the sensors was studied under tensile loading. The results showed that the d31 value increased from ∼21.3 pC/N to ∼51.3 pC/N as the porosity increased from 3.3% to 23.7%. With a further increase in porosity, the d31 value had a considerable declining trend. The optimal porosity value was determined to be 23.7% as the sensor exhibited the strongest piezoelectric effect at this point. Meanwhile, a cyclic load was applied to the sensors to investigate their sensing effect and the results indicated that the sensors can properly detect a dynamic load ranging from 0 to 10 N. It was also found that the voltage output produced from the sensors significantly changed with the porosity and the sensor with 23.7% porosity showed the best sensing performance, which was in an agreement with the piezoelectric coefficient d31.
Feature Generation and Selection for Identification of Damage in Thin-Walled Structures Based on a Statistical Approach
Authors: Sattarifar Afshin , Nestorović Tamara 
Published: October 2021

Abstract
Ultrasonic guided waves are recognized as one of the promising approaches to detect damage in the structures. Furthermore, machine learning algorithms with their distinguished capability in recognizing and classifying the patterns in a dataset can be employed as an extension to conventional damage detection techniques. In the current study, a damage detection framework is proposed, which is based on the result of the numerical simulation of wave propagation in an aluminum plate. The feature vector required for the training of the classifiers is generated by employing statistical analysis of the time domain signals as well as their Hilbert transform. This study shows the importance of the selection of the right combination of the features for the classification of the state of the structure. The result of this study contributes to devising a more automated and generalized process for damages detection in metallic structures.
Design of a Bio-Inspired Soft Robot for Break Bulk Manipulation in Transport Engineering
Authors: Bui Duc Trung Tin , Jovanova Jovana 
Published: October 2021

Abstract
This research explores the possibility of upscaling bio-inspired designed soft robots in transport engineering application with the focus on grabbing and manipulating break bulk such as windmill blades or rolls of steel. Upscaling current state soft robotic systems includes challenges regarding the structural strength of the robot. Also certain actuation methods could be affected by upscaling the actuators as well. The design of the proposed bio-inspired soft robot is determined by analysing the functions and constraints of the design as well as evaluating different types of gripping solutions based on the different types of shapes of the object. In this research the claw gripping is selected to be applied in break bulk manipulation. This gripping solution could potentially be combined with the vacuum gripping solution to be able to manipulate more types of objects. The three fingers of the claw are designed based on the trunk of an elephant as the trunk of an elephant can lift heavy loads and can therefore be seen as a good starting point to design a high load capacity gripper.
A Translation-to-Rotation Converter for Scavenging Energy From Human Walking
Authors: Pan Qiqi , Wang Biao , Zhang Lingling , Yang Zhengbao 
Published: October 2021

Abstract
Human motion is a rich source of energy. However, the ultra-low frequency and the irregular feature of the motion make the above prospects still far from being effective. In this work, we present a translation-to-rotation converter for energy harvesting during human walking. We here propose the harvester that enables conversion of low-frequency translational vibration to high-speed rotations and further generates electricity via the electromagnetic effect. The transducer is composed of an internal thread sleeve, an external thread driving shaft, a spring, a gearbox, and a limit frame. Our design features low cost, low fabrication difficulty, and high power density. Experiments conducted under pseudo-walking conditions confirmed that the stiffness of the spring and the pitch of the sleeve are the two key parameters for the performance of the harvester. The harvester mounts in a shoe heel and engages power generation in the whole gait cycle. Test subjects walking with one device with optimal spring stiffness on each shoe produce a peak power of 3.7 watts at a pace frequency of 1 Hz, which is about one magnitude higher than that of shoe-mounted devices under pseudo-walking excitation. Moreover, the proposed device could open an alternative pathway for powering smart wearable or portable electronics.
The Effect of Sensitivity Matrix Formulation on Damage Detection in Carbon Fiber Composites With Surface-Mounted Electrodes via Electrical Impedance Tomography
Authors: Sannamani M. , Tallman T. N. 
Published: October 2021

Abstract
Carbon fiber reinforced polymers (CFRPs) are valued in aerospace and other weight-conscious applications for their high strength-to-weight ratio. However, with the adoption of these lightweight materials emerges challenges not seen in traditional monolithic materials such as complex internal (i.e. outwardly invisible) damages like delamination or fiber failure in the structure. Robust methods of damage detection and health monitoring are therefore important. It is also desirable to utilize an intrinsic property of these materials, such as electrical conductivity, as an indicator of damage to render the material as self-sensing. Electrical impedance tomography (EIT) has been widely explored for damage detection and health monitoring in self-sensing materials. To date, however, studies involving EIT have been largely limited to materials with less electrical anisotropy than is seen in CFRPs and using only edge-placed electrodes (e.g. electrodes placed on the edges of a plate). These limitations are important because the inability to handle highly electrically anisotropic materials precludes EIT from a great number of existent CFRP structures. Furthermore, many real structures lack well-defined edges on which electrodes can be placed. In this paper, we tackle these challenges by presenting a preliminary study into the role of EIT sensitivity matrix formulation and surface-mounted electrodes on damage detection and localization in CFRPs. In our approach, the conductivity is modeled as being anisotropic, and the sensitivity matrix is formed using three methods — with respect to a scalar multiple of the conductivity tensor, the out-of-plane conductivity, and the in-plane conductivity. It was found that through-hole damage can be adeptly identified using the combination of surface-mounted electrodes and a sensitivity matrix formed with respect to either a scalar multiple of the conductivity tensor or the in-plane conductivity. The findings presented in this work take an important step towards translating EIT out of the laboratory and into real applications on CFRPs.
A Novel Design of Broadband Piezoelectric Vibration Energy Harvester With Cross-Coupled L-Shaped Structure
Authors: Sun Shilong , Zheng Yulong , Zhang Xiao 
Published: October 2021

Abstract
The piezoelectric vibration energy harvester can collect energy from the ambient vibration. The vibrations from the environment are usually random and also from various directions. The current energy harvester cannot efficiently collect the energy from vibration and also the energy transfer efficiency is very low, and the bandwidth is limited. Therefore, this paper proposed a novel cross-coupled L-shaped piezoelectric vibration energy harvester (CL-PVEH) to solve the low efficiency and narrow bandwidth. This structure consists of a vertical beam and a horizontal beam joint crosswise to complete a multi-directional energy harvester. The finite element analysis (FEA) and analytical study are performed in comparison that the ability of energy conversion efficiency for the cross-coupled and traditional L-shaped structures. The results demonstrate that the CL-PVEH can harness energy effectively under excitations from three perpendicular directions while the TL-PVEH can harness energy under excitation from only two directions effectively. Meanwhile, the CL-PVEH can generate three output peaks under a frequency range of 10Hz–100Hz, which are 18.8Hz, 24.8Hz, and 91.5Hz under multi-directional excitations. The multiple natural resonance frequencies under different direction excitations display that the CL-PVEH has a great ability of broadband energy harvesting and can be more flexible in mechanical structure health and human health status monitoring, especially in complex and multi-directional vibrational environment.
A Nonlinear Piezoelectric Energy Harvester With Auxetic Structures
Authors: Chen Keyu , Gao Qiang , Fang Shitong , Zou Donglin , Yang Zhengbao , Liao Wei-Hsin 
Published: October 2021

Abstract
In this paper, we design and experimentally validate an auxetic nonlinear piezoelectric energy harvester. This harvester combines a clamp-clamp beam and auxetic structures, which can improve the efficiency and bandwidth of the energy harvesting based on a pure mechanical structure without outer magnets or stoppers. Finite element analysis is performed to analyse the effects of the auxetic structures on the efficiency and nonlinearity of the energy harvester. The lumped parameter model is utilized to predict the performance of the energy harvester, which well matches the experimental results. In the experimental validation, under 0.1g base excitation, the power output of the two types of auxetic energy harvesters is 173% and 94% higher than the conventional nonlinear energy harvester. Besides, the bandwidths of the two types of auxetic energy harvesters are broadened by 1556% and 2142% compared with the linear systems.
Unit Cell Optimization of Polymer Filled Honeycomb Composites
Authors: Squibb Carson , Philen Michael 
Published: October 2021

Abstract
Hexagonal honeycombs and their use in composite structures has become commonplace in aerospace design and other fields. Polymer-filled honeycomb structures, where the hexagonal cells are filled with an elastomer, are of interest for their ability to increase the stiffness of the composite over that of the elastomer or honeycomb individually. Previous research by the authors has demonstrated that the effective behavior of such composites is determined by both the honeycomb geometry as well as the material properties of the infill and cell wall. Infill stiffness amplifications of over three orders of magnitude have been predicted, which could be an attractive option for improving the performance of smart materials such as shape memory polymers. Considering the benefits of such composites, it is of interest to optimize the honeycomb cell geometry to maximize the stiffness increase observed in the infill material. To meet this objective, in this work a unit cell finite element model was created for a hexagonal, thin walled honeycomb. Six design variables describing the honeycomb geometry were selected, and parametric studies of these design variables in the objective have been generated. Informed by these studies, an estimation of the Pareto front has been completed, with chosen objectives of the maximum composite in-plane modulus and modulus ratio, in one material direction. Promising designs are identified, and the range of effective composite properties if discussed. While this problem considers fixed infill properties, the methods applied could readily be extended to smart material infills. The contour plots and performance estimation employed in this research provides an important step in the design of improved smart composites for use in morphing and variable stiffness structures.
Stochastic Signal Analysis and Processing of Non-Harmonic, Periodic Vibrational Energy Harvesters
Authors: Germer Maxim , Marschner Uwe , Richter Andreas 
Published: October 2021

Abstract
This study presents a novel signal description based on stochastic signal analysis, applicable to electromagnetic, piezomagnetic or other transducers without energy storage as a capacitor. At present the peak power and average power are used to characterize the energy transducer. As for non-harmonic signals the last-mentioned quantities compress the time in a way, that inhibits predicting the transferable energy for different charge based interface circuits to charge a storage capacitor.
The main objectives are first, to represent the data meaningfully, second, to incorporate the effect of lossy rectifiers on the raw data and third, to evaluate the performance of chosen energy harvesters together with the interface circuits efficiently. The foundation relies in considering the measured time signal as a realization of an ergodic process. The probability density function (PDF) and the cumulated density function (CDF) build the fundament and are used to link the signal magnitudes to their probability of occurrence. New distribution functions are introduced to determine both, the charges and the energy of an electromagnetic transducer above a specific signal amplitude, which can be imposed by a voltage drop of one or several components. The presented method is further applied on the well-known full wave rectifier and to calculate its momentary efficiency, being limited by 92% for a sinusoidal signal.
As a result, the paper applies the new stochastic signal representation to energy harvesters to extends the state-of-the-art time and frequency signal analysis. Different interface circuits with energy storage can be quickly calculated for different initial storage voltages, much faster than powerful network simulators.
Machine Learning-Assisted Modeling and Design Optimization of Hybrid Shape Memory Alloy Axial Actuators
Authors: Guan Weilin , Hewakuruppu Hasitha J. , Peraza Hernandez Edwin A. 
Published: October 2021

Abstract
Shape memory alloys (SMAs) are materials that can generate and recover moderate inelastic strains through temperature modulation. This characteristic enables SMAs to function as lightweight and compact thermomechanical actuators. The synthesis of SMA actuators for systems with specific requirements on their actuation path (displacement stroke vs. temperature) currently relies on complex and expensive material processing and characterization. This paper first presents a geometric approach for synthesizing novel SMA axial actuators, termed as hybrid SMA actuators, whose dimensions (length and cross-sectional area) and material distribution are modulated to approximate a target actuation path. Through the combination of multiple SMA wire sections in series, the hybrid SMA actuators can exhibit actuation paths not achievable by using single monolithic SMA wires. The paper then presents a machine learning-assisted framework for the surrogate modeling of hybrid SMA actuators. This approach allows for the prediction of their actuation path without the use of structural simulations leveraging numerical implementations of constitutive models, allowing for simplified and computationally efficient modeling and circumventing convergence issues. A surrogate model consisting of an ensemble of binary decision trees is trained using data obtained via a design of experiments performed using structural simulations. A validation test using 5000 design samples for hybrid SMA actuators with two sections demonstrates R2 values of 0.99983 and 0.99979 for the actuation displacement during heating and cooling, respectively. The evaluation time for the validation samples using the trained surrogate model is less than 8 minutes, while the evaluation time using structural simulations is 59 minutes. Finally, a surrogate-based optimization approach is demonstrated through the synthesis of hybrid SMA actuators capable of exhibiting prescribed displacement vs. temperature target actuation paths.
ACOUSTICAL STANDARDS NEWS
Authors: Blair-DeLeon Nancy A. , Struck Christopher J. 
Published: October 2021

American National Standards (ANSI Standards) developed by Accredited Standards Committees S1, S2, S3, S3/SC 1, and S12 in the areas of acoustics, mechanical vibration and shock, bioacoustics, animal bioacoustics, and noise, respectively, are published by the Acoustical Society of America (ASA). In addition to these standards, ASA publishes a catalog of Acoustical American National Standards. To browse the latest copy of our catalog, visit our website at https://acousticalsociety.org/download-catalog/.
Comments are welcomed on all material in Acoustical Standards News.
This Acoustical Standards News section in JASA, as well as the National Catalog of Acoustical Standards and other information on the Standards Program of the Acoustical Society of America, are also available via the ASA Standards home page: https://acousticalsociety.org/acoustical-society-standards/.
Challenges of continuation of live liver donor programme during COVID-19 pandemic in Pakistan: outcomes and lessons learned
Authors: Dogar Abdul Wahab , Uddin Shams , Ghaffar Abdul , Abbas Syed Hasnain , Izzo Hala , Hussain Azhar , Ullah Kaleem , Shoaib Azam , Ud Din Siraj , Ahmed Bilal , Hamza Muhammad Ameer , Zafar Munaza , Qaiser Muhammad Affan , Raza Hamid , Baig Muhammad Asif , Husnain Ali , Mumtaz Khalid 
Published: October 2021

BackgroundCOVID-19 pandemic has globally affected healthcare including the transplantation programmes.Materials and methodsWe retrospectively studied the impact of COVID-19 on live liver donor (LLD) programme at liver transplant centre in Gambat, Pakistan. Standard operative procedures (SOPs) including COVID-19 nasopharyngeal swab PCR, CT scans, personal protective equipment use, 6-feet distancing were developed for LLD and transplant team to mitigate COVID-19 exposure. We compared the complications, healthcare utilisation (hospital stay, readmission) and mortality between two LLD cohorts—before and during COVID-19 pandemic from March 2019 to December 2020.ResultsDuring study period 300 LLD surgeries were performed. There was an increase in rate of LLDs from 132 (44%) in pre-COVID to 168 (56%) during COVID-19 era. Average numbers of transplants per month performed during pre-COVID and during COVID-19 era were 10.1 and 14, respectively. No donor has developed COVID-19 infection during hospitalisation. Rate of all LLD complications (32 (21.47%) and 49 (29.16%), p=0.43), uneventful discharges (120/168 (71.4%) and 88/132 (66.6%), p<0.05), mean hospital stay (6±2 days and 5±2 days, p=0.17) and readmission (5 (4%) and 3 (1.8%), p=0.43) were similar during the pre-COVID and COVID-19 era. No donor mortality was observed during study period.ConclusionWith the implementation of mindful SOPs, rate of LLD increased without any case of COVID-19 infection. Our SOPs were helpful in continuation of LLD programme in a developing country during COVID-19 pandemic.
High endothelial venule is a surrogate biomarker for T-cell inflamed tumor microenvironment and prognosis in gastric cancer
Authors: Park Hyung Soon , Kim Yoo Min , Kim Sewha , Lee Won Suk , Kong So Jung , Yang Hannah , Kang Beodeul , Cheon Jaekyung , Shin Su-Jin , Kim Chan , Chon Hong Jae 
Published: October 2021

BackgroundHigh endothelial venule (HEV) is a specialized vasculature for lymphocyte trafficking. While HEVs are frequently observed within gastric cancer (GC), the vascular–immune interaction between HEV and tumor-infiltrating lymphocytes (TILs) has not been well elucidated. In this study, we aimed to unveil the potential value of HEVs as a surrogate marker for T-cell inflamed immune microenvironment in GC using a large number of prospectively collected surgical specimens of GC.MethodsWe included 460 patients with GC who underwent surgical resection. Nanostring PanCancer immune profiling was performed to evaluate the immunological phenotype of GCs. HEV density and three distinct patterns of TILs (Crohn-like lymphoid reaction, peritumoral lymphoid reaction, and intratumoral lymphoid reaction) were analyzed for their relationship and evaluated as prognostic factors for relapse-free survival (RFS) and overall survival (OS).ResultsHEV-high GC revealed increased infiltration by immune cell subsets, including dendritic cells, CD8+ cytotoxic T cells, and CD4+ helper T cells. In addition, HEV-high GC demonstrated increased immune-modulating chemokines, type I or II interferon pathway, and immune checkpoints, all of which indicate the inflamed tumor microenvironment (TME). All three distinct patterns of TILs were associated with HEV density. In survival analysis, patients with HEV-high GC displayed significantly longer RFS and OS than those with HEV-low GC (p<0.001 for RFS, p<0.001 for OS). Multivariate analysis demonstrated that HEV was the most significant immunological prognostic factor for RFS (patients with high HEV compared with those with low HEV; HR 0.412, 95% CI 0.241 to 0.705, p=0.001) and OS (HR 0.547, 95% CI 0.329 to 0.909, p=0.02) after adjustment for age, stage, and TIL.ConclusionHEV is the most significant immunological prognosticator for RFS and OS in resected GC, indicating inflamed TME.
AN EXPLORATION OF THE RELATIONSHIP BETWEEN THE QUALITY OF PUBLIC GOVERNANCE AND INCOME INEQUALITY: A CASE STUDY OF VIETNAM
Authors: PHAN PHUC VAN 
Published: October 2021

Public governance and income inequality relationship is complex and debatable. This paper examines the extent to which the quality of local governance affects inequality in Vietnam spanning the 2006–2016 period. I apply a generalized method of moments (GMM) estimators to a dynamic panel data extracted from the Vietnam’s provincial competitiveness index and the Vietnam household living standard surveys. The findings are that there is a positive inequality — corruption link but no statistically significant correlation coefficient between the overall level of governance and income disparity. The study, therefore, suggests that the Vietnamese Government at all levels should consider both more effective legal practices and economic low-cost solutions to mitigate corruption.
A tradução como um exercício analítico: Fazil Iskander entre duas culturas
Authors: Silva Gabriela Soares da 
Published: October 2021

Fazil Iskander (1929-2016) é um dos mais representativos escritores soviéticos remanescentes da geração do degelo. Sua primeira novela, Sozvezdie Kozlotura (1966), uma sátira sobre a política desenvolvimentista de Khrushiov, traz uma mescla entre a cultura soviética e abkhaziana, constituindo no campo da linguagem uma variação entre a retórica burocrática soviética e o lirismo digressivo do autor com a singularidade de sua origem não-russa. No que concerne a tradução, foi realizada uma abordagem analítica e de contextualização, de modo a compreender Sozvezdie Kozlotura em sua complexidade histórica, social e cultural.