bluuebunny/crossref_metadata_2025 huggingface dataset:
Modeling and Design Exploration of Tensegrity Plate Mechanisms With Energy Dissipation Capabilities Enabled by Shape Memory Alloys
Authors: Silva Pedro , Peraza Hernandez Edwin A.
Published: November 2021

This paper presents the modeling and design exploration of tensegrity plate mechanisms with the ability of dissipating energy arising from compressive loads. The tensegrity plates are comprised of an assembly of tensegrity prisms, each formed by three compressive bars self-equilibrated by a network of tensile strings. The plates transfer a uniform compressive surface load applied along their planform area to uniaxial tension and compression within their members. The energy dissipation capabilities of plates with strings formed by three different elastoplastic metals and a pseudoelastic shape memory alloy (SMA) are explored. The constitutive parameters of these materials are calibrated from experimental data, and finite element models of the plates are created. A Taguchi design of experiments is used to evaluate the main effects of different design parameters of the plates on their energy dissipation and residual deformation responses. Results indicate that plates of larger thickness, lower diameter, and higher complexities provide higher energy dissipation per unit mass. Pseudoelastic SMA strings were the only type of strings that provided cyclic energy dissipation without the emergence of residual displacements. The studied energy absorbing mechanisms can potentially be integrated in aerospace, automotive, and civil components designed to absorb and dissipate energy from vibrations or distributed compressive loads.
Isogeometric Shape Optimization for Design Dependent Loads
Authors: Pal Arkaprabho , Rakshit Sourav
Published: November 2021

This paper presents an isogeometric shape optimization approach for a special class of problems in structural optimization known as design dependent load problems. Isogeometric method has been widely used for structural analysis and shape optimization for its advantages in modeling smooth surfaces, high accuracy, local control, and interfacing with CAD tools. Isogeometric method may be of special advantage for shape optimization problems with design dependent loads as the loads in such class of problems depend on the geometry of the designed surface. The method outlined in this paper is applicable to design dependent load problems where there is a pressure load acting on the boundary of the structure, the direction of the pressure being normal to the profile of the designed structure. In this work minimum compliance optimization subject to volume constraint is considered and isogeometric formulations based on NURBS are presented for such class of problems. The control points of the boundaries of the NURBS geometries are taken as the design variables in the optimization problems. Analytical sensitivity formulations are derived for design dependent load problems and compared with numerically derived sensitivities. A few representative 2D and 3D examples are solved and compared with existing literature to demonstrate the application of the proposed method.
A Reconfigurable Variable-Stiffness Parallel Beam for Compliant Robotic Mechanisms Towards Safe Human Interaction
Authors: Fu Jiaming , Gan Dongming
Published: November 2021

To co-work with humans, robotic mechanisms need to have variable stiffness with high rigidity for performance and low compliance for safe interactions. This paper introduces a reconfigurable variable-stiffness parallel beam (VSPB) which can be used in both robotic joints and links for variable compliance. The VSPB is a compliant cantilever mechanism with hollow parallel beams in the middle and solid connections at both ends. Stiffness adjusting can be realized by changing the cross-sectional area property of the hollow beam segment discretely through a bistable mechanism block or continuously by the block sliding. Detailed stiffness models of the two VSPB stiffness modes with the block on and off are derived using the approach of serially connected beam modeling and superposition combination. The developed model not only works for thin-walled flexure beams but also general thick beam models. The stiffness change relationship with various design parameters is investigated using the developed model and validated by finite element analysis (FEA) results. The correlation between parameters and errors between FEA and theoretical values is observed and analyzed to optimize the model. These methods and results provide a new concept and theoretical basis for developing new variable stiffness robotic mechanisms towards safe human-robot interaction applications.
In Search of the Jerk Element
Authors: Belyaev Zachary P. , Downes Samuel N. , Voglewede Philip A.
Published: November 2021

Mechanical components, such as springs, dampers and mass, alter and influence an engineered system’s motion based upon a system’s position, velocity and acceleration, respectively. This paper aims to discover and develop another element (dubbed the damper) which provides a force proportional to a system’s jerk (i.e., the derivative of acceleration) to better engineer a system’s response. By utilizing the known applications of jerk in motion planning and control theory, existing possible physical implementations and uses of jerk and the jerk element are discussed in relation to its influence on the system’s response, specifically vibration. Using a Buckingham Pi approach, the theoretical background of the jerk element is presented and possible physical parameters are combined to show how the jerk element could be created from common elements and parameters. The most promising approach of varying the magnetic field of existing magneto-rheological dampers is developed to give an example of the jerk element along with the difficulties and concerns in developing the jerk element. This paper serves less of a purpose towards answering all questions of the jerk element, but rather focuses more on posing the appropriate questions which sets the stage for an easily realizable future jerk element which can improve system performance.
Computational Investigation of Tissue and Blood Vessel Growth Trade-Offs in Hierarchical Lattices
Authors: Arefin Amit M. E. , Egan Paul F.
Published: November 2021

Computational design is growing in necessity for advancing biomedical technologies, particularly when considering complex systems with numerous trade-offs among design decisions and resulting biomechanical behavior. In tissue engineering applications, porous bone scaffold structures enabled by 3D printing can have intricate lattice structures and hierarchical features that mimic the biological hierarchy of natural bone. However, these hierarchies create challenges in predicting the tissue regeneration process and how different scales of the hierarchy drive varied biological behaviors. Smaller pores facilitate tissue growth while larger pores are necessary for blood vessel growth, however, identifying favorable trade-offs to maximize growth of both tissue and blood vessels remains a challenge, especially for complex 3D printed structures. Here, we adapt tissue and blood vessel growth models for predicting biological growth in scaffolds with varied combinations of beam diameter size, unit cell topology, and hierarchical pore size/distribution. Findings demonstrate that on a normalized scale lattices with no large voids provide greater tissue growth but less blood vessel growth in comparison to lattice layouts with large void areas. A lattice with large void channels provided the greatest blood vessel growth but poorer tissue growth, while a lattice with evenly distributed large voids provided a better compromise between the two types of growth. Overall, these findings demonstrate the merit in computational investigations for design trade-off comparisons in tissue scaffolds, and provide a foundation for future explorations of biological design decisions for regenerative medicine and 3D printed systems.
3D Linear Identification of Mechanical Joint Using FRF Decoupling and Inverse Structural Modification Methods
Authors: Soleimani Hossein , Cigeroglu Ender , Özgüven H. Nevzat
Published: November 2021

Mechanical connections such as bolts and rivets are inevitable in most engineering structures and may significantly affect the dynamic behavior of the structures. Therefore, modeling a joint simply and accurately is essential for assembled structures. On the other hand, the most important step is the determination of these joint model parameters which will be used in the calculation of dynamic response of assembled structures. For this purpose, in this paper, FRF Decoupling Method (FRF-DM), proposed in an earlier study for bolted beam connections is extended in two ways: Firstly, the bolt model proposed for 2D beam elements is extended to 3D finite element models of structural systems, and thus the dynamics of a bolted connection is modeled as an equivalent 6 × 6 complex stiffness matrix including linear and torsional stiffnesses. Secondly, FRF-DM is extended to include measurements at connection degrees of freedoms, which improves the accuracy in identification. Several equations for the identification of joint parameters are derived utilizing FRF-DM. Joint parameters are calculated by using developed FRF decoupling relations, as well as by employing a recently developed method called Inverse Structural Modification Method (ISMM) in a case study consisting of two beams connected by a 6 × 6 stiffness and viscous damping matrices. The accuracy and the advantages of each method/formulation are discussed by using the case study based on simulated experiments.
Design and High Accuracy Numerical Implementation of Fractional Order PI Controller for a PMSM Speed System
Authors: Wang Baokun , Wang Shaohua , Luo Ying
Published: November 2021

In this paper, a systematic design and high accuracy implementation of fractional order proportional integral (FOPI) controller is proposed for a permanent magnet synchronous motor (PMSM) speed system, and the numerical implementation performance of the fractional order operator is evaluated with comprehensive investigation using different implementation methods. Three commonly used numerical implementation methods of fractional operators are investigated and compared in this paper. Futhermore, for the impulse response invariant method, the effects of different discretization orders on the system control performance are compared. The simulation results show that the high accuracy numerical implementation method of the designed high-order FOPI controller has improved performance over normal accuracy fractional order operation implementation.
Enabling Multi-Robot Cooperative Additive Manufacturing: Centralized vs. Decentralized Approaches
Authors: Elagandula Saivipulteja , Poudel Laxmi , Zhou Wenchao , Sha Zhenghui
Published: November 2021

This paper presents a decentralized approach based on a simple set of rules to carry out multi-robot cooperative 3D printing. Cooperative 3D printing is a novel approach to 3D printing that uses multiple mobile 3D printing robots to print a large part by dividing and assigning the part to multiple robots in parallel using the concept of chunk-based printing. The results obtained using the decentralized approach are then compared with those obtained from the centralized approach. Two case studies were performed to evaluate the performance of both approaches using makespan as the evaluation criterion. The first case is a small-scale problem with four printing robots and 20 chunks, whereas the second case study is a large-scale problem with ten printing robots and 200 chunks. The result shows that the centralized approach provides a better solution compared to the decentralized approach in both cases in terms of makespan. However, the gap between the solutions seems to shrink with the scale of the problem. While further study is required to verify this conclusion, the decrease in this gap indicates that the decentralized approach might compare favorably over the centralized approach for a large-scale problem in manufacturing using multiple mobile 3D printing robots. Additionally, the runtime for the large-scale problem (Case II) increases by 27-fold compared to the small-scale problem (Case I) for the centralized approach, whereas it only increased by less than 2-fold for the decentralized approach.
Vibration Suppression of a Harmonically Forced Oscillator via a Parametrically Excited Centrifugal Pendulum
Authors: Gupta Aakash , Tai Wei-Che
Published: November 2021

Vibration suppression has been a widely studied topic for a long time, with various modifications in passive vibration mitigation devices to improve the efficacy. One such modification is the addition of the inerter. The inerter has been integrated into various vibration mitigation devices, whose mass amplification effect could be used to enhance the performance of dynamic vibration absorbers. In the current study, we consider an inerter based pendulum vibration absorber (IPVA) system and conduct a theoretical study on vibration suppression of the device. The IPVA system operates based on the principle of nonlinear energy transfer, wherein the energy of the primary structure is transferred into the pendulum vibration absorber. This is the result of parametric resonance of the pendulum, where the primary resonance of the system becomes unstable and a harmonic regime containing a frequency half the resonant frequency emerges (referred to as secondary regime). We use the harmonic balance method along with bifurcation analysis using Floquet theory to study the stability of primary resonance. It is observed that a pitchfork bifurcation and period-doubling bifurcation are necessary for nonlinear energy transfer to occur. Furthermore, we integrate the IPVA with a linear, harmonically forced oscillator to demonstrate its efficacy compared with a linear benchmark. We also examine the effects of various system parameters on the occurrence of the secondary regime. Moreover, we verify the nonlinear energy transfer phenomenon (due to the occurrence of the secondary regime) by numerical Fourier analysis.
Electric Vehicle Battery Simulation: How Electrode Porosity and Thickness Impact Cost and Performance
Authors: Zhao Yixin , Behdad Sara
Published: November 2021

Lithium-ion batteries almost exclusively power today’s electric vehicles (EVs). Cutting battery costs is crucial to the promotion of EVs. This paper aims to develop potential solutions to lower the cost and improve battery performance by investigating its design variables: positive electrode porosity and thickness. The open-access lithium-ion battery design and cost model (BatPac) from the Argonne National Laboratory of the United States Department of Energy, has been used for the analyses. Six pouch battery systems with different positive materials are compared in this study (LMO, LFP, NMC 532/LMO, NMC 622, NMC 811, and NCA). Despite their higher positive active material price, nickel-rich batteries (NMC 622, NMC 811, and NCA) present a cheaper total pack cost per kilowatt-hour than other batteries. The higher thickness and lower porosity can reduce the battery cost, enhance the specific energy, lower the battery mass but increase the performance instability. The reliability of the results in this study is proven by comparing estimated and actual commercial EV battery parameters. In addition to the positive electrode thickness and porosity, six other factors that affect the battery’s cost and performance have been discussed. They include energy storage, negative electrode porosity, separator thickness and porosity, and negative and positive current collector thickness.
In-Process Data Fusion for Process Monitoring and Control of Metal Additive Manufacturing
Authors: Yang Zhuo , Lu Yan , Li Simin , Li Jennifer , Ndiaye Yande , Yang Hui , Krishnamurty Sundar
Published: November 2021

To accelerate the adoption of Metal Additive Manufacturing (MAM) for production, an understanding of MAM process-structure-property (PSP) relationships is indispensable for quality control. A multitude of physical phenomena involved in MAM necessitates the use of multi-modal and in-process sensing techniques to model, monitor and control the process. The data generated from these sensors and process actuators are fused in various ways to advance our understanding of the process and to estimate both process status and part-in-progress states. This paper presents a hierarchical in-process data fusion framework for MAM, consisting of pointwise, trackwise, layerwise and partwise data analytics. Data fusion can be performed at raw data, feature, decision or mixed levels. The multi-scale data fusion framework is illustrated in detail using a laser powder bed fusion process for anomaly detection, material defect isolation, and part quality prediction. The multi-scale data fusion can be generally applied and integrated with real-time MAM process control, near-real-time layerwise repairing and buildwise decision making. The framework can be utilized by the AM research and standards community to rapidly develop and deploy interoperable tools and standards to analyze, process and exploit two or more different types of AM data. Common engineering standards for AM data fusion systems will dramatically improve the ability to detect, identify and locate part flaws, and then derive optimal policies for process control.
Earthworm-Like Planar Locomotion Robot Based on Yoshimura-Origami Structure
Authors: Zhang Qiwei , Xu Jian , Fang Hongbin
Published: November 2021

Inspired by the biological characteristics of the earthworm and the prominent deformability of origami structure, this research proposes an origami-based earthworm-like robot to achieve effective planar locomotion. Origami is attractive for building earthworm-like robots’ ‘body’ because it can exhibit excellent compliance and reduce the cost of fabrication. In this paper, we choose Yoshimura structure incorporated with hybrid actuators and anchoring mechanisms to construct the robot segment. The Yoshimura structure is composed of multiple layers and each layer is assumed to have uniform deformation. Kinematic analysis indicates that the Yoshimura structure has excellent axial and bending deformability, and the deformability is closely related to the number of layers. To control the axial and bending deformation of the robot segment individually, each segment contains two types of actuators: pneumatic balloon and SMA spring. The balloon is used to actuate the expansion and contraction of the segment, while the SMA spring is used to actuate the bending behavior of the segment. The experiment is performed to verify that the robot can achieve rectilinear and planar locomotion. Our results could lead to the development of origami-based locomotion robots and deepen our understanding of them.
Finite Element/Contact Mechanics Analysis of Spur Gear Pairs With Tooth Root Cracks
Authors: Wang Yaosen , Hood Adrian A. , Cooley Christopher G.
Published: November 2021

This study analyzes the nonlinear static and dynamic response in spur gear pairs with tooth root crack damage. A finite element/contact mechanics (FE/CM) model is used that accurately captures the elastic deformations on the gear teeth due to kinematic motion, tooth and rim deformations, vibration, and localized increases in compliance due to a tooth root crack. The damage is modeled by releasing the connectivity of the finite element mesh at select nodes near a tooth crack. The sensitivity of the calculated static transmission errors and tooth mesh stiffnesses is determined for varying crack initial locations, final locations, and the path from the initial to final location. Gear tooth mesh stiffness is calculated for a wide range of tooth root crack lengths, including large cracks that extend through nearly all of the tooth. Mesh stiffnesses are meaningfully reduced due to tooth root crack damage. The dynamic response is calculated for cracks of varying length. Larger cracks result in increased peak dynamic transmission errors. For small tooth root cracks the spectrum of dynamic transmission error contains components near the natural frequency of the gear pair. The spectrum of dynamic transmission error has broadband frequency response for large tooth root cracks that extend further than one-half of the tooth’s thickness.
The effect of different information sources on prosodic boundary perception
Authors: Ludusan Bogdan , Morii Masahiro , Minagawa Yasuyo , Dupoux Emmanuel
Published: November 2021

This study aims to quantify the effect of several information sources: acoustic, higher-level linguistic, and knowledge of the prosodic system of the language, on the perception of prosodic boundaries. An experiment with native and non-native participants investigating the identification of prosodic boundaries in Japanese was conducted. It revealed that non-native speakers as well as native speakers with access only to acoustic information can recognize boundaries better than chance level. However, knowledge of both the prosodic system and of higher-level information are required for a good boundary identification, each one having similar or higher importance than that of acoustic information.
Spurious-sound-free measurement of parametric acoustic array using optical interferometry
Authors: Ishikawa Kenji , Shiraki Yoshifumi , Moriya Takehiro
Published: November 2021

When measuring a parametric acoustic array (PAA) with a microphone, the sound often suffers from so-called spurious sound, the noise generated by the nonlinearity of the microphone. This paper proposes a spurious-sound-free measurement method for a PAA using optical interferometry and Gaussian beam expansion. Comparison between the proposed method and numerical simulation by the finite element method confirmed that the proposed method measures the demodulated audio sound without any effect from spurious sound.
Re-identification of individuals in genomic datasets using public face images
Authors: Venkatesaramani Rajagopal , Malin Bradley A. , Vorobeychik Yevgeniy
Published: November 2021

Face re-identification from genomic data is harder than you think!
Felsic volcanism as a factor driving the end-Permian mass extinction
Authors: Zhang Hua , Zhang Feifei , Chen Jiu-bin , Erwin Douglas H. , Syverson Drew D. , Ni Pei , Rampino Michael , Chi Zhe , Cai Yao-feng , Xiang Lei , Li Wei-qiang , Liu Sheng-Ao , Wang Ru-cheng , Wang Xiang-dong , Feng Zhuo , Li Hou-min , Zhang Ting , Cai Hong-ming , Zheng Wang , Cui Ying , Zhu Xiang-kun , Hou Zeng-qian , Wu Fu-yuan , Xu Yi-gang , Planavsky Noah , Shen Shu-zhong
Published: November 2021

Felsic volcanism in South China with Cu, Hg, and S released exacerbated environmental changes that drove the end-Permian extinction.
Activation of the NRF2 antioxidant program sensitizes tumors to G6PD inhibition
Authors: Ding Hongyu , Chen Zihong , Wu Katherine , Huang Shih Ming , Wu Warren L. , LeBoeuf Sarah E. , Pillai Ray G. , Rabinowitz Joshua D. , Papagiannakopoulos Thales
Published: November 2021

In Nrf2-activated tumors, G6pd inhibition depletes TCA intermediates and suppresses tumor growth.
Antisense therapy in a rat model of Alexander disease reverses GFAP pathology, white matter deficits, and motor impairment
Authors: Hagemann Tracy L. , Powers Berit , Lin Ni-Hsuan , Mohamed Ahmed F. , Dague Katerina L. , Hannah Seth C. , Bachmann Gemma , Mazur Curt , Rigo Frank , Olsen Abby L. , Feany Mel B. , Perng Ming-Der , Berman Robert F. , Messing Albee
Published: November 2021

Gfap
-antisense prevents disease with early treatment and reverses clinical phenotypes with late treatment in a rat model of Alexander disease.
In-Depth Characterization of the Chikungunya Virus Replication Cycle
Authors: Reis Erik V. S. , Damas Beatriz M. , Mendonça Diogo C. , Abrahão Jônatas S. , Bonjardim Cláudio A.
Published: November 2021

The understanding of virus biology is essential to containing virus dissemination, and exploring the virus replication cycle is a powerful tool to do this. There are many points in the biology of the chikungunya virus that need to be clarified, especially regarding its replication cycle.
SARS-CoV-2 Variants and Their Relevant Mutational Profiles: Update Summer 2021
Authors: Alkhatib Mohammad , Svicher Valentina , Salpini Romina , Ambrosio Francesca Alessandra , Bellocchi Maria Concetta , Carioti Luca , Piermatteo Lorenzo , Scutari Rossana , Costa Giosuè , Artese Anna , Alcaro Stefano , Shafer Robert , Ceccherini-Silberstein Francesca
Published: November 2021

Since the emergence of SARS-CoV-2, several recurrent mutations, particularly in the spike protein, arose during human-to-human transmission or spillover events between humans and animals, generating distinct worrisome variants of concern (VOCs) or of interest (VOIs), designated as such due to their clinical and diagnostic impacts. Characterizing these variants and their related mutations is important in tracking SAR-CoV-2 evolution and understanding the efficacy of vaccines and therapeutics based on monoclonal antibodies, convalescent-phase sera, and direct antivirals.
SARS-CoV-2 B.1.1.7 Decline Is Not Driven by the Introduction of a More Successful Variant
Authors: Rodríguez-Grande Cristina , Buenestado-Serrano Sergio , Alcalá Luis , Sola-Campoy Pedro J. , Molero-Salinas Andrea , Otero-Sobrino Álvaro , Rodríguez-Grande Jorge , de la Cueva García Víctor Manuel , Adán-Jiménez Javier , Rico-Luna Carla , Losada Carmen , Catalán Pilar , Muñoz Patricia , Pérez-Lago Laura , García de Viedma Darío
Published: November 2021

Our data indicate that the dynamics of SARS-CoV-2 VOCs turnover in our setting differ from those proposed for other countries. A systematic genomic analysis, updated on a weekly basis, of representative randomly selected samples of SARS-CoV-2 circulating variants allowed us to define a lapse of 7 weeks between the start of VOC Alpha decline and the final emergence of VOC Delta.
Supplemental Material: Geologic map of southern Panamint Valley, southern Panamint Range and central Slate Range, California (USA)
Authors: Andrew J.E.
Published: November 2021

Digital map data files in ArcGIS shapefile format for data collection points, geologic contacts, and geologic unit polygons.
Prediction of in-hospital mortality ofClostriodiodes difficileinfection using critical care database: a big data-driven, machine learning approach
Authors: Du Hao , Siah Kewin Tien Ho , Ru-Yan Valencia Zhang , Teh Readon , En Tan Christopher Yu , Yeung Wesley , Scaduto Christina , Bolongaita Sarah , Cruz Maria Teresa Kasunuran , Liu Mengru , Lin Xiaohao , Tan Yan Yuan , Feng Mengling
Published: November 2021

Research objectives

Clostriodiodes difficileinfection (CDI) is a major cause of healthcare-associated diarrhoea with high mortality. There is a lack of validated predictors for severe outcomes in CDI. The aim of this study is to derive and validate a clinical prediction tool for CDI in-hospital mortality using a large critical care database.

Methodology

The demographics, clinical parameters, laboratory results and mortality of CDI were extracted from the Medical Information Mart for Intensive Care-III (MIMIC-III) database. We subsequently trained three machine learning models: logistic regression (LR), random forest (RF) and gradient boosting machine (GBM) to predict in-hospital mortality. The individual performances of the models were compared against current severity scores (Clostridiodes difficile Associated Risk of Death Score (CARDS) and ATLAS (Age, Treatment with systemic antibiotics, leukocyte count, Albumin and Serum creatinine as a measure of renal function) by calculating area under receiver operating curve (AUROC). We identified factors associated with higher mortality risk in each model.

Summary of results

From 61 532 intensive care unit stays in the MIMIC-III database, there were 1315 CDI cases. The mortality rate for CDI in the study cohort was 18.33%. AUROC was 0.69 (95% CI, 0.60 to 0.76) for LR, 0.71 (95% CI, 0.62 to 0.77) for RF and 0.72 (95% CI, 0.64 to 0.78) for GBM, while previously AUROC was 0.57 (95% CI, 0.51 to 0.65) for CARDS and 0.63 (95% CI, 0.54 to 0.70) for ATLAS. Albumin, lactate and bicarbonate were significant mortality factors for all the models. Free calcium, potassium, white blood cell, urea, platelet and mean blood pressure were present in at least two of the three models.

Conclusion

Our machine learning derived CDI in-hospital mortality prediction model identified pertinent factors that can assist critical care clinicians in identifying patients at high risk of dying from CDI.
Cohort profile: the Mâncio Lima cohort study of urban malaria in Amazonian Brazil
Authors: Johansen Igor C , Rodrigues Priscila T , Tonini Juliana , Vinetz Joseph , Castro Marcia C , Ferreira Marcelo U
Published: November 2021

Purpose

This population-based open cohort study aims to investigate biological and sociodemographic drivers of malaria transmission in the main urban hotspot of Amazonian Brazil.

Participants

Nearly 20% of the households in the northwestern town of Mâncio Lima were randomly selected and 2690 participants were enrolled since April 2018. Sociodemographic, housing quality, occupational, behavioural and morbidity information and travel histories were collected during consecutive study visits. Blood samples from participants>3 months old were used for malaria diagnosis and human genetic studies; samples from participants with laboratory-confirmed malaria have been cryopreserved for genetic and phenotypic characterisation of parasites. Serology was introduced in 2020 to measure the prevalence and longevity of SARS-CoV-2 IgG antibodies.

Findings to date

Malaria prevalence rates were low (up to 1.0% forPlasmodium vivaxand 0.6% forP. falciparum) during five consecutive cross-sectional surveys between April–May 2018 and October–November 2020; 63% of infections diagnosed by microscopy were asymptomatic. Malaria risk is heterogeneously distributed, with 20% study participants contributing 86% of the overall burden ofP. vivaxinfection. Adult males are at greatest risk of infection and human mobility across the urban–rural interface may contribute to sustained malaria transmission. LocalP. vivaxparasites are genetically diverse and fragmented into discrete inbred lineages that remain stable across space and time.

Future plans

Two follow-up visits, with similar study protocols, are planned in 2021. We aim to identify high-risk individuals that fuel onwards malaria transmission and represent a priority target for more intensive and effective control interventions.

Trial registration number

NCT03689036.
Improving the quality of weekend medical handover on non-receiving medical hospital wards
Authors: Nicoll Ruairidh , White Mark , Loureiro Harrison Luis , Cordiner Ruth LM , Daniel Malcolm , Choo-Kang Brian , Boyle James G
Published: November 2021

Introduction

Handover is the system by which the responsibility for immediate and ongoing care is transferred between healthcare professionals and can be an area of risk. The Royal College of Physicians (RCP) has recommended improvement and standardisation of handover. Locally, national training surveys have reported poor feedback regarding handover at Glasgow Royal Infirmary.

Aim

To improve and standardise handover from weekday to weekend teams.

Methods

The Plan–Do–Study–Act (PDSA) quality improvement framework was used. Interventions were derived from a driver diagram after consultation with relevant stakeholders. Four PDSA cycles were completed over a 4-month period:

PDSA cycle 1—Introduction of standardised paper form on three wards.

PDSA cycle 2—Introduction of electronic handover system on three wards.

PDSA cycle 3—Expansion of electronic handover to seven wards.

PDSA cycle 4—Expansion of electronic handover to all non-receiving medical wards.

The outcome of interest was the percentage of patients with full information handed over based on a six-point scale derived from the RCP. Data were collected weekly throughout the study period.

Results

18 data collection exercises were performed including 525 patients. During the initial phase there was an improvement in handover quality with 0/28 (0%) at baseline having all six points completed compared with 13/48 (27%) with standardised paper form and 21/42 (50%) with the electronic system (p<0.001). When the electronic handover form was expanded to all wards, the increased quality was maintained, however, to a lesser extent compared with the initial wards.

Conclusion

A standardised electronic handover system was successfully introduced to downstream medical wards over a short time period. This led to an in improvement in the quality of handover in the initial wards involved. When expanded to a greater number of wards there was still an improvement in quality but to a lesser degree.
Analysing and reporting of observational data: a systematic review informing the EULAR points to consider when analysing and reporting comparative effectiveness research with observational data in rheumatology
Authors: Lauper Kim , Kedra Joanna , de Wit Maarten , Fautrel Bruno , Frisell Thomas , Hyrich Kimme L , Iannone Florenzo , Machado Pedro M , Ørnbjerg Lykke M , Rotar Ziga , Santos Maria Jose , Stamm Tanja A , Stones Simon R , Strangfeld Anja , Landewé Robert BM , Finckh Axel , Bergstra Sytske Anne , Courvoisier Delphine S
Published: November 2021

Objectives

To evaluate the analysis and reporting of comparative effectiveness research with observational data in rheumatology, informing European Alliance of Associations for Rheumatology points to consider.

Methods

We performed a systematic literature review searching Ovid MEDLINE for original articles comparing drug effectiveness in longitudinal observational studies, published in key rheumatology journals between 2008 and 2019. The extracted information focused on reporting and types of analyses. We evaluated if year of publication impacted results.

Results

From 9969 abstracts reviewed, 211 articles fulfilled the inclusion criteria. Ten per cent of studies did not adjust for confounding factors. Some studies did not explain how they chose covariates for adjustment (9%), used bivariate screening (21%) and/or stepwise selection procedures (18%). Only 33% studies reported the number of patients lost to follow-up and 25% acknowledged attrition (drop-out or treatment cessation). To account for attrition, studies used non-responder imputation, followed by last observation carried forward (LOCF) and complete case (CC) analyses. Most studies did not report the number of missing data on covariates (83%), and when addressed, 49% used CC and 11% LOCF. Date of publication did not influence the results.

Conclusion

Most studies did not acknowledge missing data and attrition, and a tenth did not adjust for any confounding factors. When attempting to account for them, several studies used methods which potentially increase bias (LOCF, CC analysis, bivariate screening…). This study shows that there is no improvement over the last decade, highlighting the need for recommendations for the assessment and reporting of comparative drug effectiveness in observational data in rheumatology.
Rules of Program Behavior
Authors: Duran Rodrigo , Sorva Juha , Seppälä Otto
Published: November 2021

We propose a framework for identifying, organizing, and communicating learning objectives that involve program semantics. In this framework, detailed learning objectives are written down as
rules of program behavior
(RPBs). RPBs are teacher-facing statements that describe what needs to be learned about the behavior of a specific sort of programs. Different programming languages, student cohorts, and contexts call for different RPBs. Instructional designers may define progressions of RPB rulesets for different stages of a programming course or curriculum; we identify evaluation criteria for RPBs and discuss tradeoffs in RPB design. As a proof-of-concept example, we present a progression of rulesets designed for teaching beginners how expressions, variables, and functions work in Python. We submit that the RPB framework is valuable to practitioners and researchers as a tool for design and communication. Within computing education research, the framework can inform, among other things, the ongoing exploration of “notional machines” and the design of assessments and visualizations. The theoretical work that we report here lays a foundation for future empirical research that compares the effectiveness of RPB rulesets as well as different methods for teaching a particular ruleset.
Nitric oxide could promote development of Barrett’s esophagus byS-nitrosylation-induced inhibition of Rho-ROCK signaling in esophageal fibroblasts
Authors: Fujiya Taku , Asanuma Kiyotaka , Koike Tomoyuki , Okata Tomoki , Saito Masahiro , Asano Naoki , Imatani Akira , Masamune Atsushi
Published: November 2021

Barrett’s esophagus is the condition where esophageal epithelium damaged by gastroesophageal reflux disease (GERD) is abnormally healed via replacing of metaplastic columnar epithelium, but very few studies have conducted focusing wound healing in the development of Barrett’s esophagus. Esophageal luminal nitric oxide inhibits Rho-ROCK signaling pathway in esophageal fibroblasts, which leads to delay tissue contraction, a pivotal step in proper wound healing. Moreover, this inhibition increases tissue BMP4 expression. Impaired wound healing could be related to Barrett’s esophagus.
Effect of extracellular hyperosmolality on sweat rate during metaboreflex activation in passively heated young men
Authors: Rutherford Maura M. , Akerman Ashley P. , Meade Robert D. , Notley Sean R. , Schmidt Madison D. , Kenny Glen P.
Published: November 2021

Metaboreflex activation augments sweating during mild-to-moderate hyperthermia in euhydrated (isosmotic isovolemic) individuals. Recent work indicates that extracellular hyperosmolality may augment metaboreflex-mediated elevations in sympathetic nervous activity. Our primary objective was, therefore, to test the hypothesis that extracellular hyperosmolality would exacerbate metaboreflex-mediated increases in sweat rate. On two separate occasions, 12 young men [means (SD): 25 (5) yr] received a 90-min intravenous infusion of either 0.9% saline (isosmotic condition, ISO) or 3.0% saline (hyperosmotic condition, HYP), resulting in a postinfusion serum osmolality of 290 (3) and 301 (7) mosmol/kgH2O, respectively. A whole body water perfusion suit was then used to increase esophageal temperature by 0.8°C above resting. Participants then performed a metaboreflex activation protocol consisting of 90-s isometric handgrip exercise (40% of their predetermined maximum voluntary contraction), followed by 150 s of brachial occlusion (trapping produced metabolites within the limb). Metaboreflex-induced sweating was quantified as the change in global sweat rate (from preisometric handgrip exercise to brachial occlusion), estimated as the surface area-weighted average of local sweat rate on the abdomen, axilla, chest, bicep, quadriceps, and calf, measured using ventilated capsules (3.8 cm2). We also explored whether this response differed between body regions. The change in global sweat rate due to metaboreflex activation was significantly greater in HYP compared with ISO (0.03 mg/min/cm2 [95% confidence interval: 0.00, 0.06]; P = 0.047), but was not modulated by body region (site × condition interaction: P = 0.679). These findings indicate that extracellular hyperosmolality augments metaboreflex-induced increases in global sweat rate, with no evidence for region-specific differences.
Auditory-nerve responses in mice with noise-induced cochlear synaptopathy
Authors: Suthakar Kirupa , Liberman M. Charles
Published: November 2021

Noise-induced damage to synapses between inner hair cells and auditory-nerve fibers (ANFs) can occur without permanent hair cell damage, resulting in pathophysiology that “hides” behind normal thresholds. Prior single-fiber neurophysiology in guinea pig suggested that noise selectively targets high-threshold ANFs. Here, we show that the lingering pathophysiology differs in mouse, with both ANF groups affected and a paradoxical gain-of-function in surviving low-threshold fibers, including increased onset rate, decreased onset jitter, and reduced maskability.
Oxidative Stress Disrupted Prepubertal Rat Testicular Development after Xenotransplantation
Authors: Ma Yu-Bo , Gao Ming , Zhang Tong-Dian , Chong Tie , Li He-Cheng , Wang Zi-Ming , Zhang Lian-Dong
Published: November 2021

In the past two decades, testicular tissue grafting and xenografting have been well established, with the production of fertilization‐competent sperm in some studies. However, few studies have been carried out to observe the development of grafted prepubertal testicular tissue of rats and compare the biological differences between in situ testis and grafted testis. In this study, we established the prepubertal testicular tissue xenografting model using a 22‐day‐old rat and evaluated certain parameters, including testicular histology, testosterone production, and ultrastructure of the grafted testes. We also assessed gene expression of cell proliferation markers, testicular cell markers, and antioxidative defense system. Our results showed that 47 days after transplantation, intratesticular testosterone concentration was not significantly altered; however, cell proliferation, spermatogenesis, and Sertoli cell markers in the transplanted testes were significantly disrupted compared with the control group, accompanied by aggravated apoptosis and oxidative damage. Moreover, the transplanted testes showed smaller tubular diameter and disrupted spermatogenic epithelium with apparent vacuoles, distorted and degenerated germ cells with obscure nuclear margin, and no spermatids in the center of the tubules. Although testis xenografting has been extensively tested and attained great achievement in other species, the prepubertal rat testicular tissue xenografting to immunodeficient mice exhibited obvious spermatogenesis arrest and oxidative damage. The protocol still needs further optimization, and there are still some unknown factors in prepubertal rat testes transplantation.
Physical Attributes of Bardeen Stellar Structures in
f

R

Gravity
Authors: Shamir M. Farasat , Usman Ammara , Naz Tayyaba
Published: November 2021

The main aim of our study is to explore some relativistic configurations of compact object solution in the background of

f

R

gravity, by adopting the Krori-Barua spacetime. In this regard, we establish the field equations for spherically symmetric spacetime along with charged anisotropic matter source by assuming the specific form of the metric potentials, i.e.,

ν

r

=
B

r

2

+
C

and

λ

r

=
A

r

2

. Further, to calculate the constant values, we consider the Bardeen model as an exterior spacetime at the surface boundary. To ensure the viability of the

f

R

gravity model, the physical characteristics including energy density, pressure components, energy bonds, equilibrium condition, Herrera cracking concept, mass-radius relation, and adiabatic index are analyzed in detail. It is observed that all the outcomes by graphical exploration and tabular figures show that the Bardeen black hole model describes the physically realistic stellar structures.
Diagnosis of Diabetic Retinopathy through Retinal Fundus Images and 3D Convolutional Neural Networks with Limited Number of Samples
Authors: Tufail Ahsan Bin , Ullah Inam , Khan Wali Ullah , Asif Muhammad , Ahmad Ijaz , Ma Yong-Kui , Khan Rahim , Kalimullah  , Ali Md. Sadek
Published: November 2021

Diabetic retinopathy (DR) is a worldwide problem associated with the human retina. It leads to minor and major blindness and is more prevalent among adults. Automated screening saves time of medical care specialists. In this work, we have used different deep learning (DL) based 3D convolutional neural network (3D‐CNN) architectures for binary and multiclass (5 classes) classification of DR. We have considered mild, moderate, no, proliferate, and severe DR categories. We have deployed two artificial data augmentation/enhancement methods: random weak Gaussian blurring and random shift along with their combination to accomplish these tasks in the spatial domain. In the binary classification case, we have found the performance of 3D‐CNN architecture trained by deploying combined augmentation methods to be the best, while in the multiclass case, the performance of model trained without augmentation is the best. It is observed that the DL algorithms working with large volumes of data may achieve better performances as compared to the methods working with small volumes of data.
Machine Learning for Ischemic Heart Disease Diagnosis Aided by Evolutionary Computing
Authors: Alsaffar Mohammad , Alshammari Abdullah , Alshammari Gharbi , Aljaloud Saud , Almurayziq Tariq S. , Abdoon Fadam Muteb , Abebaw Solomon
Published: November 2021

Heart disease is the leading cause of death from chronic diseases in the developing countries. The difficulty of making an accurate and timely diagnosis is exacerbated by a lack of resources and professionals in some areas, which contributes to this reality. Medical professionals may benefit from technological advancements that aid in the accurate diagnosis of patients. In light of these findings, a hybrid diagnostic tool has been developed that combines several computational intelligence (machine learning) techniques capable of analyzing clinical histories and images of electrocardiogram signals and indicating whether or not the patient has ischemic heart disease with up to 97.01% accuracy. Working with medical experts and a database containing clinical data on approximately 1020 patients and their diagnoses was required for this project. Both were put to use. A picture database containing 92 images of electrocardiogram signals was also used in this project for the analysis of the Artificial Neural Network. After extensive research and testing by the medical community, which supported the project and provided positive feedback, a successful tool was developed. This demonstrated the tool’s effectiveness.
[Retracted] Analysis of College Student Registration Management and Change Prediction Based on Mutated Fuzzy Neural Network Algorithm
Authors: Wang Yao , Jiao Lie , Liu Chunzhi
Published: November 2021

Nowadays, a large number of students′ academic registrations change every year in universities, but most of these cases are recorded and mathematically and statistically analysed through forms or systems, which are cumbersome and difficult to find some potential information in them. Therefore, timely and effective prediction of student registration changes and early warning of student registration changes by technical means is an important part of university registration management. At present, relevant research is mostly based on mathematical statistical analysis methods such as students′ current credit evaluation or course score averages and seldom uses data mining and other technical methods for in‐depth research. In this paper, we propose a mutated fuzzy neural network (MFNN) based prediction model for student registration changes in colleges and universities, which can provide supplementary reference decisions for school registration management for school teaching managers. In this paper, we first construct the corresponding prediction model of academic registration variation, define the relevant parameters, and model the optimization problem and propose the objective optimization function. Second, the proposed model is optimized by adding principal component analysis (PCA) to the original model to improve the efficiency of model training and the correct prediction rate. It is verified that the proposed model can effectively predict individual students′ academic registration changes with a prediction accuracy of nearly 92.91%.