bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimization of Patient Health Management Mechanism Under Intelligent Medical Information System
Authors: Zheng Lifang , Liu Weixia , Chen Hangying
Published: May 2022

The establishment of a scientific and complete intelligent medical information analysis application model is of great significance to promote the application of intelligent medical information. Aiming at the deficiencies of Artificial Fish School Algorithm (AFSA) in iterative convergence
speed, low optimization accuracy, and Particle Swarm Optimization (PSO) algorithm easily falling into local extremes, this paper combines AFSA and PSO algorithms. We use the fast local convergence ability of the PSO algorithm to overcome the shortcomings of the AFSA algorithm’s low solution
accuracy and slow convergence speed. In the classification stage, we try to apply machine learning technology to classify the labeled feature vectors, evaluate and analyze the performance of these two machine learning algorithms in intelligent medical diagnosis auxiliary applications, and
use today’s popular deep learning classification methods (i.e., intelligently optimized text classification model) and machine learning classification method to compare the classification effect, evaluate and analyze the applicability of the classification model in the auxiliary application
of intelligent medical diagnosis. The experimental results show that the accuracy rate of applying the machine learning method to the judgment of the type of disease reaches more than 90%, which is fully in line with the disease judgment of the patient.
Automated Diagnosis of Breast Cancer from Mammogram Using Wavelet, Curvelet Features, and Convolutional Neural Network
Authors: Karthic R. S. , Aravind Britto K. R.
Published: May 2022

Breast cancer is the utmost generally occurring cancer in women and the second most communal cancer. The ground truth standard used in real-time clinical application for the diagnosis is a mammogram. A novel approach is projected in this paper for the automated diagnosis of breast cancer
from mammogram images composed from the MIAS data set using curvelet/wavelet transform-based features and a convolutional neural network. The following sequences of operations are involved, namely pre-processing, application of curvelet/wavelet transform, statistical and gray level co-occurrence
matrix-based features extracted from curvelet/wavelet coefficients followed by a selection of highly discriminative features by statistical p-test. Initially, pre-trained models VGG16 and VGG19 are used for classification, and Deep convolutional neural network architecture is constructed for
which feature matrix is given as input. Pretrained models are used for classification using the concept of transfer learning. The constructed architecture hyperparameters are adjusted, and the highest classification precision of 93% is achieved. The obtained results outperform the state of
art methods available in the state of art.
Execution Analysis of Clarity Locale Segmentation for Condition Recognition Utilizing Genetic Algorithm Method
Authors: Saranya S. , Sudha S.
Published: May 2022

The collection of fluid at the back of the fetal neck, known as nuchal translucency (NT), is linked to chromosomal abnormalities and early heart failure in the first trimester of pregnancy. Using the Co-Active Adaptive Neuro Fuzzy Inference System (CANFIS) classification algorithm,
this research presents an effective way for recognising and localising the NT region in fetus images in which noise removed. Then, pattern features are extracted Initially, the noises in fetus images are detected and eliminated using directional filtering technique and then Gabor transform
from the magnitude of Gabor transformed fetus image and then they are optimized using Genetic Algorithm (GA) approach. The extracted GLCM, ELBP and LTP features are integrated into feature vector for further classifications. The size of constructed feature vector is high and leads to high
computation time for the classification process. These optimized feature set is classified using CANFIS. Finally, the graph cut segmentation method is used for segmenting the NT region. This proposed method is practically used in many health care centers in rural areas.
Speed Efficient Fast Fourier Transform for Signal Processing of Nucleotides to Detect Diabetic Retinopathy Using Machine Learning
Authors: Saravanakumar C. , Usha Bhanu N.
Published: May 2022

Diabetic Retinopathy (DR) is a complicated disease of diabetes, which specifically affects the retina. The human-intensive analysis mechanism of DR infected retina are likely to diagnose wrongly compared to computer-intensive diagnosis systems. In this paper, in order to aid the computer
based approach for the diagnosis of DR, a model based on machine learning algorithm is proposed. The nucleotides of the human retina are processed with the help of signal processing methodologies. A speed efficient Fast Fourier transform is proposed to work out the FFT of huge amount of samples
with higher pace. The improvement in speed is achieved in 98% of the samples. The prediction parameters, derived from these samples are utilized to classify the healthy retina sequence and an infected retina. In this study, Fine Tree, KNN Fine, Weighted KNN, Ensemble Bagged Trees and Ensemble
Subspace KNN classifiers are employed to build the models. The simulated results using MATLAB software show that the accuracy is 98% which is better than image processing based methods which were used earlier. The performance parameters such as sensitivity and specificity are determined for
each model. The faithfulness of the model is studied by deriving the ROC Curve.
Optimized Ensemble Machine Learning-Based Diabetic Retinopathy Grading Using Multiple Region of Interest Analysis and Bayesian Approach
Authors: Nancy W. , Celine Kavida A.
Published: May 2022

Diabetic Retinopathy (DR) is a critical abnormality in the retina mainly caused by diabetes. The early diagnosis of DR is essential to avoid painless blindness. The conventional DR diagnosis is manual and requires skilled Ophthalmologists. The Ophthalmologist’s analyses are subjective
to inconsistency and record maintenance issues. Hence, there is a need for other DR diagnosis methods. In this paper, we proposed an AdaBoost algorithm-based ensemble classification approach to classify DR grades. The major objective of the proposed approach is an enhancement of DR classification
performance by using optimized features and ensemble machine learning techniques. The proposed method classifies different grades of DR using the Meyer wavelet and retinal vessel-based features extracted from multiple regions of interest of the retina. To improve the predictive accuracy, we
used a Bayesian algorithm to optimize the hyper-parameters of the proposed ensemble classifier. The proposed DR grading model was constructed and evaluated by using the MESSIDOR fundus image dataset. In evaluation experiment, the classification outcome of the proposed approach was evaluated
by the confusion matrix and receiver operating characteristic (ROC) based metrics. The evaluation experiments show that the proposed approach attained 99.2% precision, 98.2% recall, 99% accuracy, and 0.99 AUC. The experimental findings also indicate that the proposed approach’s classification
outcome is significantly better than that of state of art DR classification methods.
Detection of Diabetic Retinopathy Using Discrete Wavelet Transform with Discrete Meyer in Retinal Images
Authors: Ramani G. , Menakadevi T.
Published: May 2022

One of the major complicated issues for extensive term diabetic aspirant is diabetic retinopathy (DR) which is an eye retinal syndrome, leads to blindness. The presence of exudates detects the disease, which can be prevented in the early stages by regular screening. Exudates can be
automatically detected through inspecting digital retinal image. To detect the exudates for diagnosis the author proposed an algorithm called K-means Kernel support vector machine Radial basis function (KKR) approach, by the following main stages: extracting vessel and removal of optic
disc followed by pre-processing, exudates detection and post processing. Wavelet dependent edge enhancement is used for dark portion separation of exudates in the retinal image by optically designed Wideband bandpass filter. Wavelet toolbox of MATLAB 2018a is used in this KKR algorithm. Statistical
and structural texture features can be obtained using K-means segmentation process by integrating Local Binary Pattern (LBP) with Region Of Interest (ROI). Some features are selected and used Neural Network along with Radial Basis Function (RBF) to classify further. The KKR algorithm
uses 80 fundus images from DIARETDB1 database and parameters are analyzed such as specificity, sensitivity and accuracy. The results obtained from proposed KKR algorithm have specificity of 81.57%, sensitivity of 87.56% and accuracy of 97.94% respectively.
Diagnostic Application and Systematic Evaluation of Image Registration Software in External Radiotherapy
Authors: Zhou Han , Li Jing , Li AoMei , Qiu XiangNan , Shen ZeTian , Ge Yun
Published: May 2022

Purpose: Analyze the clinical application of MIM maestro in cancer radiotherapy and evaluate the advantage of the software compare to the clinical applied tools. Materials and Methods: Potentially relevant studies published were identified through a pubmed and web of science
search using words “MIM Maestro,” “Atlas,” “image registration,” “dose accumulation,” “irradiation.” Combinations of words were also searched as were bibliographies of downloaded papers in order to avoid missing relevant publications.
Results: In many patients with cancer radiotherapy, multiple types of images are demanded, MIM Maestro is a multi-modality image information processing system for radiotherapy. Contour atlas and image registration among dose accumulation and individual fractions is beneficial for radiotherapy.
Overall 34 papers were enrolled for analysis. The MIM appears to provide excellent clinical applications such as the function of contour altas, image fusion and registration, dose accumulation in radiotherapy compared to the other software. Conclusions: The regular optimization of radiotherapy
technology and the development of image technology, improve the clinical efficiency. The current paper give a systematic review of MIM Maestro multi-modality image processing software.
Unbowed, unbent, unbroken? Examining the validity of the responsibility to protect
Authors: Scherzinger Johannes
Published: May 2022

How has the sentiment around the “responsibility to protect” (R2P) changed over time? Scholars have debated far and wide whether the political norm enjoys widespread discursive acceptance or is on the brink of decline. This article contends that we can use sentiment analysis as an important indicator for norm validity. My analysis provides three crucial insights. First, despite the well-known fear of some scholars, R2P is still frequently invoked in Security Council deliberations on issues of international peace and security. Second, overall levels of affirmative language have remained remarkably stable over time. This finding indicates that R2P is far from being obliterated. Out of 130 states, 4 international organizations (IOs), and 2 non-governmental organizations (NGOs) invoking the norm, 65% maintain a positive net-sentiment. Third, zooming into Libya as a case illustration of a critical juncture, we see some minor tonal shifts from some pivotal member states. Adding the fact that interest constellations within the Permanent Five are heterogeneous concerning the third pillar of R2P, future military interventions, sanctioned under the norm, seem unlikely.
The moral and emotional world of police informants
Authors: Loftus Bethan , Bacon Matthew , Skinns Layla
Published: May 2022

The global pattern of implementing proactive policing to address crime and insecurity continues to drive undercover techniques, including the deployment of police informants. Our aim in this article is to reflect upon research on informants policing, setting out a more comprehensive agenda that appreciates the moral significance and power dynamics at play. Our starting point is that this practice embodies immense moral and emotional tension, both for the police officer and the informant. However, these deeper aspects have been largely underestimated by scholars. Research can garner new insights by conceptualizing the tactic in terms of vulnerability, morality and emotional labour.
Simulation process and data flow for a large system dynamics model
Authors: Bush Brian , Stright Dana , Huggins Jay , Newes Emily
Published: May 2022

This paper documents the workflow and supporting technologies that a large system dynamics model, the biomass scenario model, employs to streamline the data preparation, simulation, quality control, and analysis process at the National Renewable Energy Laboratory. The workflow centers on automation of routine aspects of the flow of data between data stores, simulations, and visualizations. It enforces quality checks on data, reproducibility of computations, and traceability of results, while maintaining complete archives of modeling and analysis artifacts. The resulting frictionless simulation/analysis environment supports large-scale sensitivity analysis, interactive creation of ensembles of simulations, and rapid visualization-based exploration of simulation results.
A multi-criteria decision analysis of implanted biomedical device antenna: electro-thermal simulation, design, and data analysis
Authors: Sloos Tim , Rustand Brent , Liu Xinhe , Keegan Connor , Sourki Reza , Milani Abbas S
Published: May 2022

In this article, three elemental (dipole, loop, and meander) designs of an implanted biomedical device (IBD) antenna are studied to provide an enhanced understanding of fundamental (material and geometry) factors which would contribute to the regulation of a steady vital sign, with minimal effect on the surrounding tissue during monitoring and treatment. Dipole and Loop antennas are known to offer similar advantages in that they are both balanced antennas, while the Meander antenna is likely to offer better radiation resistance. The investigation was carried out through the design of experiments and finite element modeling of the temperature field due to the AC level applied (10 or 100mA), under the geometry of each given antenna type and three material options (Titanium, Cobalt Chromium, and Macor). Finally, a multi-criteria decision-making process is applied to select the optimal design under maximum field temperature, thermal conductivity, electrical conductivity, density, and specific heat attributes. The findings suggested that the Meander design made of Titanium would allow for a maximized overall performance with minimal thermal and radiation effects.
Combining PDEVS and Modelica for describing agent-based models
Authors: Sanz Victorino , Urquia Alfonso
Published: May 2022

Modelica is a general-purpose modeling language mainly designed to facilitate the development, reusability and exchange of models. It represents the state-of-the-art in equation-based modeling of continuous-time systems. Modelica libraries facilitate the description of multi-formalism and multi-domain models. However, the description of agent-based models (ABMs) in Modelica is not currently supported, mainly due to the characteristics of the language and its simulation algorithm. The combination of ABMs with continuous-time equations provides a powerful tool for describing and analyzing complex systems. An approach for describing ABMs using the Modelica language is presented in this manuscript, with the objective of facilitating the combination of ABMs with the rest of Modelica functionality. Agent behavior is described using a process-oriented modeling approach. Agents are described as individual entities that move across a flowchart diagram, that represents the processes that agents undergo. Processes are formally described using the Parallel DEVS formalism, extended to describe the interface with other Modelica models. The environment where agents interact is described as a cellular automaton. This approach has been implemented in a free Modelica library, named ABMLib. Three case studies are discussed to illustrate the modeling functionality of the library and its combination with other models: a basic traffic model, a sheep–wolves predator–prey model and a consumer market model.
Numerically robust co-simulation using transmission line modeling and the Functional Mock-up Interface
Authors: Braun Robert , Fritzson Dag
Published: May 2022

Modeling and simulation are important tools for efficient product development. There is a growing need for collaboration, interdisciplinary simulation, and re-usability of simulation models. This usually requires simulation tools to be coupled together for co-simulation. However, the usefulness of co-simulation is often limited by poor performance and numerical instability. Achieving stability is especially hard for stiff mechanical couplings. A suitable method is to use transmission line modeling (TLM), which separates submodels using physically motivated time delays. The most established standard for tool coupling today is the Functional Mock-up Interface (FMI). Two example models in one dimension and three dimensions are used to demonstrate how the next version of FMI for co-simulation can be used in conjunction with TLM. The stability properties of TLM are also proven by numerical analysis. Results show that numerical stability can be ensured without compromising on performance. With the current FMI standard, this requires tailor-made models and custom solutions for the interpolation of input variables. Without using custom solutions, variables must be exchanged using sampled communication and extrapolation. In this case, stability properties can be improved by reducing communication step size. However, it is shown that stability cannot be achieved even when using unacceptably small communication steps. This motivates the need for the next version of FMI to include an intermediate update mode, where variables can be interchanged in between communication points. It is suggested that the FMI standard should be extended with optional callback functions for providing intermediate output variables and requesting intermediate input variables.
From the streets to the town halls: Municipalist platforms in the post-Yugoslav space
Authors: Milan Chiara
Published: May 2022

In the last decade, urban social movements that emerged in the Yugoslav successor states decided to form political platforms to enter the institutional arena, often after years of mobilisation for the right to the city. Their aim was to seize power at the local level, trying to provide an answer to the crisis of representative democracy and to oppose the process of centralisation of power. These platforms ran for elections in Zagreb (Croatia) and Belgrade (Serbia), to reclaim local autonomy on societal, environmental, economic and political matters. Based on ethnographic work, document analysis and a series of in-depth interviews with activists, this article explores the trajectories of two platforms, ‘Zagreb Is Ours’ ( Zagreb je naš) in Zagreb, Croatia, and ‘We Won’t Let Belgrade D(r)own’ ( Ne davimo Beograd) in Belgrade, Serbia. It analyses the factors accounting for the choice of urban activists to embrace new municipalist ideas as strategic ideological and political positioning of their electoral platforms, arguing that the reasons are twofold: the embeddedness into regional and transnational activist networks, which facilitated the process of diffusion of new municipalist ideas across Europe and locally, and the resonance of new municipalism with socialist Yugoslavia’s decentralised system of self-management and direct democracy, an historical experience that the platforms’ initiators partially reappraised.
Nonsingular fast terminal sliding mode control based on neural network with adaptive robust term for robotic manipulators with actuators
Authors: Lu Ningyu , Ma Li , Hua Xiaoqing
Published: May 2022

For accurate trajectory tracking of robotic manipulators with actuators, a novel nonsingular fast terminal sliding mode control (NFTSMC) strategy based on radial basis function neural network (RBFNN) is put forward and investigated in this paper. Because of the existence of nonsingular fast terminal sliding mode (NFTSM) manifold, the controller possesses high precision and fast convergence. Considering that it is difficult to obtain accurate model parameters owing to modeling errors or external disturbances, RBFNN is used to approximate the nonlinear uncertainties due to its simple structure and great generalization ability. A new adaptive law is designed to adjust RBFNN. In order to compensate the estimation errors and suppress other unstable factors, a robust term is introduced. A new adaptive law is developed to flexibly adjust the robust term. Then, Lyapunov theory is applied to prove the system stability and finite-time convergence. Finally, a small-sized industrial robotic manipulator Epson LS3-401S with its first two joints is taken as the simulation plant, and several simulations between the proposed controller and the other two controllers are performed. External disturbances and other two conditions are considered to simulate the real environment, and the corresponding results verify the effectiveness and superiority of the proposed controller.
A Multi-Scale Suitability Analysis of Home-Improvement Retail-Store Site Selection for Ontario, Canada
Authors: Robinson Derek T. , Caradima Bogdan
Published: May 2022

A multi-scale suitability analysis using big data (4.7 million suitability scores) is presented across a large spatial extent (1.076 million km2) to identify potential locations for new home-improvement retail stores. Suitability scores were generated for individual property parcels using criteria weights derived from surveyed retail-industry experts. To increase capacity for site selection, distributions of suitability scores were generated at census dissemination areas (populations 500-700; n = 19,963) and census metropolitan and agglomeration areas (core populations >10,000; n = 43). Analogues among metropolitan and agglomeration areas were generated and spatial clustering was used to identify groups of highly-suitable parcels within urban areas. Lastly, individual parcels can be interrogated for overall suitability or individual criteria scores. Our approach combines retail methods typically used in isolation (e.g. location quotient, Huff’s model, network analysis) and demonstrates how a simple survey can be used to weight criteria. Results show that survey respondents were in general agreement and that top-line revenues were more critical to perceived location success than development and operational costs. Analysis of suitability scores found analogues and clusters of census metropolitan areas that coincide with store sales as well as clusters of highly suitable parcels predominantly located around major highways. In addition to identifying challenges and solutions to the presented research, we also describe future research directions that extend the presented static analysis to include processes like store closure and openings, competition, and land use change through the use of agent-based modelling.
A New Skin for the Wounds of History: Fanon’s Affective Sociogeny and Ricœur’s Carnal Hermeneutics
Authors: Faust J. Reese
Published: May 2022

This article argues that, despite their distance across the colonial divide, a creolizing reading of Frantz Fanon and Paul Ricœur can yield valuable insights into decoloniality. Tracing their shared philosophical concerns with embodied phenomenology, social ontology and recognition, I argue that their respective accounts of sociogeny and hermeneutics can be productively read together as describing a shared end of mutual recognition untainted by racism or coloniality – a ‘new skin’ for humanity, as Fanon describes it. More specifically, Fanon contributes to Ricœur an understanding of how divergences in social location can be overcome through liberatory action that posits a new logic of sociality; likewise, Ricœur provides Fanon with an account of how liberatory horizons are produced through this praxis, based on the imaginative connection between ideology and utopia. This article concludes by arguing that these congruent methodological and normative concerns can be read together to concretize – and potentially actualize – the utopic end of liberatory struggle in mutual recognition through fashioning this new skin.
Parents’ and older siblings’ socialization of younger siblings’ empathy: a sample case in China
Authors: Su-Russell Chang , Russell Luke T.
Published: May 2022

In 2016, China officially ended its One-Child policy and started allowing urban married couples to have up to two children. Beginning in 2021, Chinese policy officially began encouraging couples to have up to three children in response to low birth rates and increasing needs for workers and care providers in an aging country. Siblinghood in China has thus begun to re-emerge as a social phenomenon among urban Chinese. Given the important role sibling relationships have in the development of empathy, this relaxation and policy shift provides a unique context in which to investigate family dynamics among two-child families where there is a large age gap between children. Guided by family systems theory, the current study examined family level factors that help socialize younger sibling’s empathy in mainland China by testing direct associations between autonomy supportive parenting, marital quality, coparenting, and secondborn children’ (ages 3–5) empathy in mainland China. Direct and indirect associations with secondborn children’s empathy via older sibling’s relationship quality with their younger sibling were also tested. Results revealed coparent conflict and positive sibling relationship were directly associated with younger sibling’s empathy; further, marital quality and coparent support were indirectly associated with younger sibling’s empathy via positive sibling relationship. Parents, educators, and practitioners may consider addressing family level factors as an avenue for promoting younger sibling’s empathy development.
Sequential contact-based adaptive grasping for robotic hands
Authors: Pollayil George Jose , Pollayil Mathew Jose , Catalano Manuel Giuseppe , Bicchi Antonio , Grioli Giorgio
Published: May 2022

This paper proposes a novel type of grasping strategy that draws inspiration from the role of touch and the importance of wrist motions in human grasping. The proposed algorithm, which we call Sequential Contact-based Adaptive Grasping, can be used to reactively modify a given grasp plan according to contacts arising between the hand and the object. This technique, based on a systematic constraint categorization and an iterative task inversion procedure, is shown to lead to synchronized motions of the fingers and the wrist, as it can be observed in humans, and to increase grasp success rate by substantially mitigating the relevant problems of object slippage during hand closure and of uncertainties caused by the environment and by the perception system. After describing the grasping problem in its quasi-static aspects, the algorithm is derived and discussed with some simple simulations. The proposed method is general as it can be applied to different kinds of robotic hands. It refines a priori defined grasp plans and significantly reduces their accuracy requirements by relying only on a forward kinematic model and elementary contact information. The efficacy of our approach is confirmed by experimental results of tests performed on a collaborative robot manipulator equipped with a state-of-the-art underactuated soft hand.
Moving beyond the impasse in geographies of ‘alternative’ food networks
Authors: Misleh Denise
Published: May 2022

Despite theoretical developments in conceptualising alterity, what counts as ‘alternative’ in unconventional systems of food provision remains contested. This paper argues that the literature has reached an impasse. I argue that overly ‘alternative’ readings conceptualise Alternative Food Networks (AFNs) as a more embedded form of economic exchange, while neoliberal readings represent them as a case of marketisation. This paper systematically reviews AFNs literature and contends that a deeper engagement with Polanyian geographies enables a more nuanced approach to evaluating alternatives and their socio-political significance. Analytically and normatively, ‘alternatives’ need not be radically ‘other’, nor seen as having been co-opted by the neoliberal order.
Flame retardancy of biodegradable polylactic acid with piperazine pyrophosphate and melamine cyanurate as flame retardant
Authors: Chen Hongxu , Xia Wei , Wang Nan , Liu Yang , Fan Penghui , Wang Song , Li Sanxi , Liu Jie , Tang Tao , Zhang Ailing , Ding Zhan , Wu Weidong , Chen Qi
Published: May 2022

A flame-retardant polylactic acid composite added with piperazine pyrophosphate and melamine cyanurate was developed. Piperazine pyrophosphate and melamine cyanurate showed synergistic effect in the polylactic acid composites. When the weight ratio of piperazine pyrophosphate to melamine cyanurate was 4:1 and the loading of the piperazine pyrophosphate/melamine cyanurate flame retardant was 15 wt.%, the prepared polylactic acid composites passed V-0 rating in the UL-94 test and achieved the high limit oxygen index value of 34.9%. The cone calorimeter test result confirmed that the addition of piperazine pyrophosphate/melamine cyanurate flame retardant reduced the total heat release value of polylactic acid. The effect of polylactic acid biodegradation on the flame retardancy of polylactic acid composite was further discussed. The biodegraded polylactic acid, which was exposed to the air for 8 months, showed high flame retardancy and even passed V-0 rating in the UL-94 test without the addition of piperazine pyrophosphate/melamine cyanurate flame retardant, which proved that biodegradation could affect the flame retardancy of polylactic acid.
Post-Assault Health Care for Sexual Assault Survivors During COVID-19: A Mixed Methods Analysis of Service Rates in a Predominately African American Community
Authors: Campbell Rebecca , Javorka McKenzie , Engleton Jasmine , Goodman-Williams Rachael , Gregory Katie
Published: May 2022

This study examined how the COVID-19 pandemic affected sexual assault healthcare services in a predominately African American U.S. city. In mixed methods research design, we used quantitative interrupted time series modeling to evaluate changes in service rates for three core post-assault healthcare services—medical forensic exams (MFEs), medical advocacy MFE accompaniment, and counseling—from January 2019 through June 2021. We also conducted qualitative interviews with 12 sexual assault advocates to understand how their clients were impacted by COVID and how their agency adapted services to respond to the needs of their community. Both the quantitative and qualitative data revealed marked disruptions in service provision. The number of MFEs, medical advocacy accompaniments, and counseling sessions significantly decreased during the pandemic’s initial surge, and survivors feared seeking hospital-based health care due to concerns that they might contract COVID-19 in hospital emergency departments. The number of MFEs performed by program staff did not return to pre-pandemic levels during this study’s observation period, but the number of medical advocacy accompaniments and counseling sessions did significantly rebound. Counseling services eventually exceeded pre-pandemic levels as agency staff supported clients with both assault- and COVID-related trauma and loss. These results underscore the need for community-based sexual assault healthcare services, so that if public health emergencies limit the availability, accessibility, and safety of hospital emergency department care, sexual assault survivors have other settings for obtaining post-assault health care.
Work placement learning and student employability: Do student satisfaction, commitment and achievement matter?
Authors: Otache Innocent , Edopkolor James Edomwonyi
Published: May 2022

While the extant literature generally suggests a positive relationship between work placement learning (WPL) and student employability, the mechanisms underlying this relationship remain unclear and under-researched. Against this background, this study draws on insights from experiential learning and self-determination theories to explore the mediating effects of student satisfaction, commitment and achievement on the relationship between WPL and student employability. The study adopted a quantitative approach, gathering data from 294 students in two public higher education institutions (HEIs) in Nigeria using a structured questionnaire. A serial mediation analysis was performed to test the study hypotheses. The results show that WPL is positively associated with student satisfaction, commitment, achievement and employability. The results also indicate that student satisfaction, commitment and achievement have strong positive impacts on student employability. Further analysis reveals that student satisfaction, commitment and achievement individually and sequentially mediate the relationship between WPL and student employability. This research demonstrates that student satisfaction, commitment and achievement help to maximize the positive impact of WPL on employability. The findings offer policy and practical implications for HEIs, policymakers, students and industry.
Mechanical properties of polymer matrix/glass fiber composites containing metal/hybrid nanoparticles-an overview
Authors: Chrispin Laila Aiswarya , Narayanan Mythili , Bhadrakumar Sindhu Devika , AlbyRoy Anju
Published: May 2022

Glass fiber reinforced composite has gained attention from various engineering fields because of its enhanced properties. This paper reviewed the mechanical characteristics, such as tensile strength, flexural strength, hardness number, impact strength, wear percentage, etc., of the composites from different experimental studies performed by various researchers over time; by varying with the weight percentage of different metal and non-metal nanoparticles. The main observation was that the mechanical properties remained optimal at a certain quantity of nanoparticles was added beyond which these characteristics began to decrease. When more than one type of nanoparticle is dispersed, or micro rubber particles are added with a specific type of nanoparticle, the properties are more pronounced than when only a single type of particle is used.
A comprehensive investigation of RANS and LES turbulence models for diesel spray modeling via experimental diesel schlieren imaging
Authors: Rostampour Arman , Shojaeefard Mohammad Hassan , Molaeimanesh Gholam Reza
Published: May 2022

Spray simulation is the basis of many engine simulations and directly impacts the quality of other simulations. Various models have been proposed to simulate spraying and the breakup and evaporation of fuel particles. The Kelvin–Helmholtz/Rayleigh–Taylor (KH-RT) model is one of the most common of these models. In this study, while analyzing the sensitivity of the KH-RT model constants on spray simulation, the effect of the LES and RANS turbulence model on spray penetration length and shape of the diesel spray contour is investigated. This study shows that both LES and RANS turbulence models along with the KH-RT model predict the spray penetration length with appropriate accuracy. While the RANS model, due to its averaging nature, does not accurately simulate the shape of the spray contour, which has very soft edges. Finally, the best method for simulating diesel spray and the proposed constants of the KH-RT model is presented.
Thermomechanical loading and cut-out effect on static and dynamic responses of multilayered structure with TD properties
Authors: Dewangan Hukum Chand , Sharma Nitin , Panda Subrata Kumar
Published: May 2022

The influences of cut-out on the static and dynamic deflection of the multilayered composites under thermomechanical are predicted numerically. In this regard, a mathematical model is prepared using the third-order kinematics associated with the isoparametric finite element steps. Moreover, the solution accuracy of the derived model has been tested frequently by solving a series of examples (obtained from MATLAB code) similar to the published one. In addition, the model verification is extended further by comparing the numerical results with the in-house experimental data recorded under the static and dynamic loading conditions. The equivalent single-layer theoretical model (prepared for the cut-out abided laminated structure) exactness is maintained by considering the variation of in-plane displacement as cubic. In contrast, the state space variable along with the thickness is constant. Additionally, the experimental comparisons are made considering the influences of different cut-out geometry, temperature increment, and loading intensities. The effects of cut-out and the laminated structural geometrical parameters that affect the final design consideration due to the thermomechanical loading as well as the temperature-dependent properties are computed using the derived model, and the outcomes are discussed in detail.
Research on gear mesh stiffness of helical gear based on combining contact line analysis method
Authors: Yan Hai , Wen Lihua , Yin Shaoping , Cao Hao , Chang Lehao
Published: May 2022

A new analytical model of mesh stiffness of helical gears is proposed using a combination of contact line analysis with slice method, which can well predict the dimensionless time-varying mesh stiffness. Based on the derived formula, the influence of gear basic parameters on mesh stiffness fluctuation coefficient is studied. The simulation shows that the influence of the overlap ratio on the mesh stiffness fluctuation coefficient is greater than that of the transverse contact ratio. By designing reasonable helix angle and tooth width, the overlap ratio is close to an integer, and then the mesh stiffness fluctuation coefficient can obtain a local minimum value, which is an effective way to reduce the vibration and noise of gear system.
Influence of coefficient of friction between punch-blank interface on formability of friction stir welded aluminum tailor welded blanks – An experimental and finite element simulation investigations
Authors: Battina N Malleswararao , Chirala Hari Krishna , Inala Ramu , Kummitha Obula Reddy , Veeravalli Lakshmi Narayana , Pericherla Srinivasa Raju
Published: May 2022

The influence of the coefficient of friction between punch-blank interface on the formability of friction stir welded aluminum tailor welded blanks was studied. Experimental and finite element investigations were performed to evaluate the formability with four different lubricants like dry lubricant, graphite in water, graphite in machine oil, and Teflon sheet (TS). During simulation, the boundary condition of the punch-blank interface was assigned as a frictional contact and the assigned value is the coefficient of friction value of the respective lubricant. To carry out the simulation, the entire blank was divided into three zones. It has been found that the coefficient of friction between punch-blank interfaces has a significant influence on formability. In the four lubrication conditions, the dry lubrication applied blank exhibited the lowest formability properties, and the TS applied blank exhibited superior formability properties in all aspects such as punch load-carrying capacity, limiting dome height, forming limit diagrams, and strain distribution profiles (experimentation and simulation). The experimental and simulation have a good agreement in all strain conditions. The standard deviation between the experimental and simulation results is ±10%.
Effect of WC particles on the mechanical behavior and machinability of aluminum matrix composites
Authors: Kara Memduh , Coskun Tolga , Gunoz Alper
Published: May 2022

Aluminum-based metal matrix composites are extensively used in applications in many industrial fields, especially in the aviation and automotive industry. The usage rate is increasing day by day. Therefore, it is very important to improve the mechanical properties of the composite structure. For this purpose, in this study, 3, 5, and 7 wt.% tungsten carbide (WC) reinforced aluminum matrix composite material was produced by stir casting method. The mechanical properties (tensile strength, hardness, wear) of the produced composite materials and their effect on machinability were investigated. The machinability process was performed in constant cutting speed, constant cutting depth, three different feed rates (0.05, 0.1, and 0.2 mm·rev−1), and dry environmental conditions. Wear tests were performed on dry sliding conditions, under 25 N load, covering different distances (150, 300, 450, and 600 m). In addition, the microstructure of the composite samples was analyzed using optical microscopy and scanning electron microscope. The phases in the composite material were determined using the X-ray diffraction technique. As a result of the experiments, with the addition of WC particles, the mechanical properties of the materials such as tensile strength, hardness, and wear resistance have increased and the machinability capability has decreased.
A finite strain chemo-poro-mechanical framework for the chemically stimulated permeation of fluid in polymer gels
Authors: Shi Yuhao , Wallmersperger Thomas
Published: May 2022

Polyelectrolyte polymer gels can significantly increase or decrease their volume by an external stimulus. The reason for this ability is the multiphasic structure of the gel. In the present work, a chemo-electro-poromechanical model is presented, which is supposed to map the swelling behavior of chemically stimulated polymer gels. The presented model was implemented in COMSOL Multiphysics®, and the swelling behavior of an acrylamide gel was simulated afterward. The mechanical parameters were obtained from experimental data using a least square optimization while the other material parameters were calibrated to the experimentally determined swelling behavior.
Augmented Virtuality Systems as a Tool for Improving Numeracy Decision-Making Among Children
Authors: Yuviler-Gavish N , Treiger Z , Horesh E , Shamilov E
Published: May 2022

Young children depend on the non-symbolic representation of numbers for their numeracy understanding and decision-making. The objective of the current research was to examine whether the use of an augmented virtuality (AV) system to represent numbers as physical objects, compared to representing them only visually on a computer screen, will improve children’s numeracy decision-making. The question was evaluated by comparing children’s decisions to buy more profitable versus non-profitable products, as well as their total profit, when the coins and the coin machine are real (AV system group) compared to their decisions when using a system in which the coins and the coin machine are virtual (virtual system group). Two between-participants groups of children aged 6–8 participated in this study, with 30 children in each group. The results demonstrated that in the AV system group, the children invested more proportionately in the profitable versus non-profitable products, while in the virtual system group, the opposite occurred. As a result of their better decision-making, the total profits of the AV system group were higher than those of the virtual system group. The current findings are an interesting addition to the existing literature on the contribution of virtual reality and augmented reality systems in improving mathematical learning.
We love to hate George Soros: A cross-platform analysis of the Globalism conspiracy theory campaign in Brazil
Authors: Santini Rose Marie , Salles Débora , Barros Carlos Eduardo
Published: May 2022

The proliferation of conspiracy theories surrounding George Soros and the ‘Globalist invasion’ had been concentrated primarily in Eastern Europe, Russia and the United States. However, since Jair Bolsonaro’s presidential victory in Brazil, Soros has become a target of the far-right in the country. On Soros’ 90th Birthday in August 2020, the right-wing group ‘Movement for Conservative Brazil’ (Movimento Brasil Conservador – MBC) launched a campaign called ‘International Day Against George Soros’, aiming to attack the billionaire’s reputation. The purpose of this paper is to investigate how this campaign worked across online platforms as a strategy to popularize the Globalism conspiracy theory in the biggest Latin American country. We aim (1) to map the dynamics of disinformation dissemination across chat apps using hyperlink analysis; and (2) to interpret conspiratorial narratives about George Soros shared on chat apps during the month of his 90th birthday. We collected messages mentioning the anti-Soros campaign in WhatsApp and Telegram public groups and channels to extract hyperlinks and domains. These websites were manually categorized in an effort to analyze which conspiracy theories about George Soros are being disseminated on chat apps in Brazil. Our results suggest an increasing cross-platform dissemination of narratives attacking Soros. This case study illustrates how the rise of a transnationally networked political right has been accompanied by an emerging alternative digital communication infrastructure through which conspiracy theories circulate.
Safe care for premature babies at home: Parenting and stimulating development
Authors: Pancieri Letícia , Silva Rosane M M , Wernet Monika , Fonseca Luciana M M , Hameed Shaffa , Mello Debora F
Published: May 2022

Parental daily care and adequate stimuli are extremely important for development and safety of premature babies at home. This study aimed to analyze safe home care for babies born under 32 weeks from parents’ perspectives, with a view to a longitudinal promotion of baby development. A qualitative study, based on philosophical hermeneutic approach proposed by Hans-Georg Gadamer, in which dialogue as a principle provides understanding and fusion of experiences and knowledge. Semi-structured interviews were conducted with 18 parents of premature babies under 1 year of age. Thematic analysis proposed by Braun and Clarke was applied using an inductive approach. Elements related to safe care were identified: home arrival, safe home care: preserving baby health and development, support for safe home care, and development of parental care to promote baby safety. These elements can provide a basis for safe home care that needs to be reinforced longitudinally to increase particularities of baby protection, avoid accidents and illnesses, and improve appropriate developmental stimuli and positive parenting.
Risky business? Parenting children of deployed Danish soldiers
Authors: Heiselberg Maj Hedegaard
Published: May 2022

This article focuses on children’s reactions to military deployment from the perspective of their parents. Based on ethnographic fieldwork among Danish soldiers, their female partners and young children over the course of military deployment, the article illustrates how parents’ attempts to access whether their children will suffer from the long-term absence of their father influence parenting practices and experiences of military deployment. Inspired by anthropological perspectives on parenthood, the article argues that the pressure on parents to be ‘involved’ in the upbringing and care of their children is magnified in the Danish case of soldiers and their partners because of cultural understandings of the military as well as ideals of gender equality and sameness. With the purpose of preventing future harm on their children, the article further argues, soldiers and their partners mobilise strategies to limit the uncertainty experienced in relation to deployment. Such strategies include preparing children for deployment, routinising everyday activities and making the absence of their father comprehensible.