Normal Impact Research Articles

Lagrangian carotid strain imaging indices normalized to blood pressure for vulnerable plaque.

Ultrasound Lagrangian carotid strain imaging (LCSI) utilizes physiological deformation caused by arterial pressure variations to generate strain tensor maps of the vessel walls and plaques. LCSI has been criticized for the lack of normalization of magnitude-based strain indices to physiological stimuli, namely blood pressure. We evaluated the impact of normalization of magnitude-based strain indices to blood pressure measured immediately after the acquisition of radiofrequency (RF) data loops for LCSI. A complete clinical ultrasound examination along with RF data loops for LCSI was performed on 50 patients (30 males and 20 females) who presented with >60% carotid stenosis and were scheduled for carotid endarterectomy. Cognition was assessed using the 60-minute neuropsychological test protocol. For axial strains correlation of maximum accumulated strain indices (MASI), cognition scores were -0.46 for non-normalized and -0.45, -0.49, -0.37, and -0.48 for systolic, diastolic, pulse pressure, and mean arterial pressure normalized data, respectively. The corresponding area under the curve (AUC) values for classifiers designed using maximum likelihood estimation of a binormal distribution with a median-split of the executive function cognition scores were 0.73, 0.70, 0.71, 0.70, and 0.71, respectively. No significant differences in the AUC estimates were obtained between normalized and non-normalized magnitude-based strain indices.

Ballistic impact of steel fiber-metal laminates and plates

PurposeThe purpose of this paper is to investigate the ballistic impact response of square clamped fiber-metal laminates and monolithic plates consisting of different metal alloys using the ANSYS LS-DYNA explicit nonlinear analysis software. The panels are subjected to central normal high velocity ballistic impact by a cylindrical projectile.Design/methodology/approachUsing validated finite element models, the influence of the constituent metal alloy on the ballistic resistance of the fiber-metal laminates and the monolithic plates is studied. Six steel alloys are examined, namely, 304 stainless steel, 1010, 1080, 4340, A36 steel and DP 590 dual phase steel. A comparison with the response of GLAss REinforced plates is also implemented.FindingsIt is found that the ballistic limits of the panels can be substantially affected by the constituent alloy. The stainless steel based panels offer the highest ballistic resistance followed by the A36 steel based panels which in turn have higher ballistic resistance than the 2024-T3 aluminum based panels. The A36 steel based panels have higher ballistic limit than the 1010 steel based panels which in turn have higher ballistic limit than the 1080 steel based panels. The behavior of characteristic impact variables such as the impact load, the absorbed impact energy and the projectile’s displacement during the ballistic impact phenomenon is analyzed.Originality/valueThe ballistic resistance of the aforementioned steel fiber-metal laminates has not been studied previously. This study contributes to the scientific knowledge concerning the impact response of steel-based fiber-metal laminates and to the construction of impact resistant structures.

Investigating the impact of data normalization on classification performance

Data normalization is one of the pre-processing approaches where the data is either scaled or transformed to make an equal contribution of each feature. The success of machine learning algorithms depends upon the quality of the data to obtain a generalized predictive model of the classification problem. The importance of data normalization for improving data quality and subsequently the performance of machine learning algorithms has been presented in many studies. But, the work lacks for the feature selection and feature weighting approaches, a current research trend in machine learning for improving performance. Therefore, this study aims to investigate the impact of fourteen data normalization methods on classification performance considering full feature set, feature selection, and feature weighting. In this paper, we also present a modified Ant Lion optimization that search feature subsets and the best feature weights along with the parameter of Nearest Neighbor Classifier. Experiments are performed on 21 publicly available real and synthetic datasets, and results are analyzed based on the accuracy, the percentage of feature reduced and runtime. It has been observed from the results that no single method outperforms others. Therefore, we have suggested a set of the best and the worst methods combining the normalization procedure and empirical analysis of results. The better performers are z-Score and Pareto Scaling for the full feature set and feature selection, and tanh and its variant for feature weighting. The worst performers are Mean Centered, Variable Stability Scaling and Median and Median Absolute Deviation methods along with un-normalized data.

Normal Impact Test of a Spherical Rockfall

Rockfall hazard is becoming increasingly fierce due to the higher intensity of human activities in recent years, but research on the impact process has almost come to a standstill, and there is no available method to solve the impact characteristic parameters of the falling rock. The free-fall drop of a spherical rockfall on three different granular layers was examined, and the acceleration value of the falling rock with time was assessed with a three degree of freedom linear accelerometer. Then, the velocity of the rockfall and penetration depth were successively obtained by computing the integral and double integral of the acceleration over time. The time-history curves of the acceleration and velocity of the rockfall and the curve of the acceleration with the penetration depth show that the time-history curve of the rockfall velocity can be characterized by a logistic function. The acceleration time-history curve has the characteristics of a unimodal pulse, and the acceleration curve with the penetration depth is similar in shape to an inverted “U”. The cushioning effect of the sand is the best and that of the gravel layer is the worst in these three different granular layers.

Dynamic stress intensity factors for multiple parallel cracks in an infinite domain under the passage of a normal incident impact or blast P-wave

A numerical technique based upon the symmetric-Galerkin boundary element method (SGBEM) for 2-D elastodynamics in the Laplace-space frequency domain and the principle of superposition of loads was introduced in this work to provide new numerical results for the dynamic stress intensity factors (DSIFs) for multiple parallel cracks in an infinite domain under the passage of an incident impact or blast P-wave normal to the crack faces. Seven test examples were presented and, compared to some DSIF results available in the literature, our Laplace-SGBEM results are able to clearly show the impact of wave scattering on the DSIFs. The results also depict a behavior known as the damped-like oscillation of the DSIFs about their corresponding static value which is caused by the interaction between scattered waves and the crack surfaces. The new results are expected to serve as benchmarks for future techniques to measure their own performance.

Numerical investigation of local heat transfer characteristics of an oblique droplet impacting a wetted wall

In this study, the flow dynamics and heat transfer process of a single droplet obliquely impacting a wall covered by a thin liquid film are investigated numerically based on the volume of fluid method, with the impact angle ranging from 0° to 45°. The results show that the flow and heat transfer for the oblique impact of a droplet show asymmetric pattern and differ significantly from those for a normal impact. The asymmetric heat transfer pattern for oblique impact of a droplet primarily lied in the asymmetric influenced area caused by asymmetric crown jets spreading on the bilateral sides and asymmetric heat transfer oscillation in the valley region caused by asymmetric recirculation. These asymmetries originate indirectly from the asymmetric droplet impaction energy transfer to the bilateral liquid film induced by the oblique impact angle. In addition, parametric studies suggest that the asymmetry of the heat transfer distribution becomes more significant for a larger oblique impact angle, higher Weber number, or smaller dimensionless film thickness.

The role of stroma and epithelial cells in primary Sjögren's syndrome.

Primary SS (pSS) is a chronic autoimmune condition characterized by infiltration of the exocrine glands and systemic B cell hyperactivation. This glandular infiltration is associated with loss of glandular function, with pSS patients primarily presenting with severe dryness of the eyes and mouth. Within the affected glands, the infiltrating lymphocytes are organized in tertiary lymphoid structures. Tertiary lymphoid structures subvert normal tissue architecture and impact on organ function, by promoting the activation and maintenance of autoreactive lymphocytes. This review summarizes the current knowledge about the role of stromal cells (including endothelium, epithelium, nerves and fibroblasts) in the pathogenesis of pSS, in particular the interactions taking place between stromal cells and infiltrating lymphocytes. We will provide evidences pointing towards the driving role of stromal cells in the orchestration of the local inflammatory milieu, thus highlighting the need for therapies aimed at targeting this compartment alongside classical immunosuppression in pSS.

Commentary on “Thinking differently? Autism and quality of life”

PurposeThe purpose of this paper is to describe the possible impact of normalisation on the perceptions of quality of life (QoL) and the impact of this association on the research to date. This commentary reflects on the implications of limiting QoL research to autistic people who are perceived to be “more able”.Design/methodology/approachThis commentary discusses the implications of undertaking QoL research in the field of autism.FindingsThis commentary argues for further consideration of the autistic voice in QoL research. Researcher epistemology and life experience, including experience of autistic people, is examined in terms of how QoL might be perceived and attributed. Further participatory research in the field of quality of life of autistic people, including those with a learning disability and engagement with a variety of autistic people, is called for.Originality/valueThis commentary suggests that the existing definitions of QoL, founded on principles of normalisation, may not be completely applicable to autistic people, and that new ways of both defining and measuring QoL might be needed.

A comparison of pre-impact gas cushioning and Wagner theory for liquid-solid impacts

The normal impact of a symmetric rigid body with an initially quiescent liquid half-space is considered using both Wagner theory and a model of viscous gas pre-impact cushioning. The predictions of these two theories are compared for a range of different body shapes. Both theories assume that the impactor has small deadrise angle. Novel solutions of the Wagner normal impact problem for a symmetric body with a power-law shape are presented, which generalize the well-known results for a parabola and a wedge. For gas cushioned pre-impacts, it is shown that a pocket of gas is entrained even for body shapes with a cusp at the body minimum. A scaling law is developed that relates the dimensions of the trapped gas pocket to the slope of the body. For pre-impact gas cushioning, surface tension is shown to smooth the liquid free-surface and delay the instant of touchdown for a smooth parabolic body, while for a wedge, increasing surface tension initially delays touchdown, before hastening touchdown as the importance of surface tension is increased further. For a flat-bottomed wedge, gas entrainment is again predicted in the gas-cushioning model although the location of initial touchdown, either on the transition between the wedge and the flat bottom or along the side of the wedge, now depends upon the parameters of the body shape.

Clustering-Based Approach for Clustering Journals in Computer Science

In the present scientific world, most of the authors of scientific literature are seeking effective ways to share their research findings with large peer groups. But finding a high-quality journal to publish paper is a huge challenge. Most of the journals present today are predatory and less-quality. The main aim of this study is to help the researchers in identifying the quality level of computer science journals by introducing a data mining model based on six journal quality metrics (Journal Impact Factor, SCImago Journal Rank, Eigenfactor, H-index, Source Normalized Impact per Paper, and Article Influence). Further, another objective is to identify the best metrics to measure the quality of journals out of the six attributes. A sample dataset of 200 journals was used and journals were clustered into five clusters using K-means clustering algorithm. When finding the best quality metrics, Pearson's and Spearman's correlation coefficients were calculated. A more accurate clustering model with an accuracy of 0.9171 was developed considering only suitable attributes.

Evaluating the Impact of Intensity Normalization on MR Image Synthesis.

Image synthesis learns a transformation from the intensity features of an input image to yield a different tissue contrast of the output image. This process has been shown to have application in many medical image analysis tasks including imputation, registration, and segmentation. To carry out synthesis, the intensities of the input images are typically scaled-i.e., normalized-both in training to learn the transformation and in testing when applying the transformation, but it is not presently known what type of input scaling is optimal. In this paper, we consider seven different intensity normalization algorithms and three different synthesis methods to evaluate the impact of normalization. Our experiments demonstrate that intensity normalization as a preprocessing step improves the synthesis results across all investigated synthesis algorithms. Furthermore, we show evidence that suggests intensity normalization is vital for successful deep learning-based MR image synthesis.

Impact tribocharging of soft elastic spheres

The transfer of charge between a solid sphere and a metal plate during an oblique collision has been studied, using larger, more compliant elastic spheres than in previous studies. This relatively slow collision with large maximum strain allowed the normal and tangential impact forces to be measured directly, and the cumulative rolling and sliding contact areas to be deduced using a dynamic model. A rich variety of charging behaviour was observed for different collision regimes, and suggests very different charge transfer mechanisms for sliding, non-sliding, heavy and light contact. The charge transfer to initially-negative and initially-positive spheres was also strikingly different. Although the reasons for this could not be definitively determined, several hypotheses are discussed in detail, including mechano-ion transfer, bulk material transfer, and the effect of the spatial distribution of the initial charge on the statistical distribution of charge transfer events.

A new method for the study of parabolic impact of foam-core sandwich panels

Lightweight sandwich panels with composite facesheets and foam core have high impact energy absorption capability and are widely employed in multifunctional applications such as aircraft and marine structures. The dynamic behaviour of sandwich panels is typically studied for impact loading at normal angle of incidence but the structures are more frequently loaded at some oblique angle or with a complex tri-dimensional trajectory in real engineering situations. The damage area and damage modes for these trajectories are significantly different and it is not sufficient to study only normal impacts. There are well established experimental protocols for normal or oblique impact tests using devices like the drop tower, but impacts with complex trajectory are difficult to characterise experimentally. In this paper, a Gough-Stewart platform with six degrees of freedom has been modified to develop an original tri-dimensional impact device called Hexapod. The trajectory is defined to an impactor attached to the seventh jack of the Hexapod to study the response of sandwich plates to impact loading with complex trajectories. The applicability of the newly developed device is demonstrated by studying parabolic impact with different trajectories on sandwich plates with Kevlar facesheets and Rohacell foam core. The time history of vertical and horizontal components of force is measured using tri-axial load cell and strain history is obtained from Digital Image Correlation of a high speed camera images. The results of the parabolic impact show the importance of shear behaviour of the foam in the progression of damage in the sandwich panels. Additionally, the response of the sandwich panels to parabolic impact was simulated numerically using explicit finite element code LS-DYNA. The results of the FE model are compared with experimental data in terms of the force history and strain contours.

DOCOSAHEXAENOIC ACID (DHA) FOR THE TREATMENT OF PEDIATRIC SPORT-RELATED CONCUSSION: RESULTS OF A FEASIBILITY TRIAL

Introduction: The rate of sport-related concussion (SRC) has increased steadily over the past two decades in the pediatric population. Docosahexaenoic acid (DHA), an Omega-3 fatty acid important for brain development in children, may aid in recovery following SRC. The purpose of this study was to determine the feasibility, outcomes, and safety of DHA as early treatment for SRC in pediatrics. Methods: A double-blind, randomized, placebo-controlled feasibility trial was conducted. Inclusion criteria were ages 14-18 and SRC within 4 days of enrollment. Exclusion criteria included taking DHA, radiographic evidence of TBI, participation in motorized sports, or previous concussion within past 6 months. Following diagnosis of concussion and initiation of standard treatment, subjects were randomized in a 1:1 fashion to DHA or a placebo and were instructed to take 2 capsules twice daily for 12 weeks. DHA capsules contained a total of 2000 mg of DHA/day and PLACEBO capsules contained corn and soy oil. Both were flavored with masking agents. Subjects were followed prospectively. Standard clinical assessments, SCAT-3 symptoms, ImPACT scores, BESS scores, adverse effects, and drug compliance was collected at enrollment, 1-week, 2-weeks, 4-weeks and 12-weeks. Demographics, day of injury symptoms, injury characteristics, and sport played were also collected. Subjects who demonstrated normal neurocognitive testing, complete symptom resolution and were cleared to begin a return to play (RTP) progression prior to the 4-week follow-up visit were permitted to forgo additional study visits, but requested to return for the 12-week visit. Groups were compared using Mann-Whitney tests for continuous variables and chi-square tests for categorical variables. Results: 40 subjects were enrolled; 20 in the DHA group (mean age: 16.02 years; 65% male) and 20 in the PLACEBO group (mean age: 15.97 years; 70% male). No significant differences in demographics, sport, symptoms, ImPACT scores, or BESS scores at enrollment were noted between groups. 25 (62.5%) subjects completed the 12-week visit. Overall drug compliance was 61.57% in the DHA group compared to 66.34% in the PLACEBO group (p=0.727). Subjects in the DHA group were symptom-free 4 days earlier than the PLACEBO group (16.1 vs. 20.9 days, p=0.082), demonstrated normal ImPACT neurocognitive testing (12.2 vs. 16.8 days, p=0.382), and were cleared to begin a RTP progression (21.4 vs. 23.4 days, p=0.115) sooner than those in the PLACEBO group. Two adverse effects were noted in the DHA group. One event was determined to be unrelated to the study. The second event was drug-related eructation and considered minor. No adverse effects were reported in the PLACEBO group. Conclusion: This study demonstrated that use of high-dose DHA for treatment of SRC in pediatrics is feasible and safe. DHA may allow for a faster symptom-free state and for an earlier return to play, but a large-scale trial is needed.

A data science-based framework to categorize academic journals

Academic journals play a significant role in the dissemination of new research insights and knowledge among scientists. The number of such journals has recently increased significantly. Scientists prefer to publish their scholarly work at reputed venues. Speed of publication is also an import factor considered by many while selecting a publication venue. To evaluate a journal’s quality, few of the key indicators include impact factor, Source Normalized Impact per Paper (SNIP), and Hirsch index (h-index). Journals’ ranking is an indication of their impact and quality with respect to other venues in a specific discipline. Various measures can be utilized for ranking, like, field specific statistics, intra discipline ranking, or a combination of both. Earlier, the journals’ ranking was done through a manual process by providing an institutional list created by academic leaders. Factors like politicization, biases, and personal interests were the key issues with such categorization. Later, the process evolved to a database system based on impact factor, SNIP (Source Normalized Impact per Paper), h-index, or any combination of these. All this demanded an external source of categorizing academic journals. This work presents a data science-based framework that evaluates journals based on their key bibliometric indicators and presents an automated approach to categorize them. For this, the current proposal is restricted to the journals published in the computer science domain. The journal’s features considered in the proposed framework include: publisher, impact factor, website, CiteScore, SJR (SCImago Journal & Country Rank), SNIP, h-index, country, age, cited half-life, immediacy factor/index, Eigenfactor score, article influence score, open access, percentile, citations, acceptance rate, peer review, and the number of articles published yearly. A dataset is collected for 660 journals consisting of these 19 features. The dataset is preprocessed to fill-in the missing values and perform scaling. Three feature selection techniques, namely, Mutual Information (MI), minimum Redundancy Maximum Relevance (mRMR), and Statistical Dependency (SD) are used to rank the aforementioned features. The dataset is then vertically divided into three sets, all features, top nine features, and bottom ten features. Later, two clustering techniques, namely, k-means and k-medoids are employed to find the optimum number of coherent groups in the dataset. Based on a rigorous evaluation, four groups of journals are identified. It is followed by training two classifiers, i.e., k-NN (Nearest Neighbor) and Artificial Neural Network (ANN) to predict the category of an unknown journal. Where, the ANN shows an average accuracy of 82.85%. A descriptive analysis of the clusters formed is also presented to gain insights about the four journal categories. The proposed framework provides an opportunity to independently categorize academic journals based on data science methods using multiple significant bibliometric indicators.

How might sovereign bond yields in Asia Pacific react to US monetary normalisation under turbulent market conditions?

ABSTRACTThis paper examines the potential impact of US monetary normalisation on sovereign bond yields in Asia Pacific. We apply the quantile vector autoregressive model with principal component analysis to the assessment of tail risk of sovereign debt, which may not be detectable using traditional OLS-based analysis. Our empirical evidence suggests that US Treasury bond yields can have a significant impact on sovereign bond yields in the region, an important channel through which monetary normalisation by the Fed can affect Asia-Pacific economies. Increases in sovereign bond yields will not only compromise the ability of the sovereigns in the region to service their debt but also translate into higher costs of borrowing for the rest of economy. The results show how much the outsized impact could potentially be if US monetary normalisation somehow turns out to be much more disorderly than expected.

Impact factor correlations with Scimago Journal Rank, Source Normalized Impact per Paper, Eigenfactor Score, and the CiteScore in Radiology, Nuclear Medicine & Medical Imaging journals.

In the last decade, several journal's editors decided to publish alternative bibliometric indices parallel to the impact factor (IF): Scimago Journal Rank (SJR), Source Normalized Impact per Paper (SNIP), Eigenfactor Score (ES) and CiteScore™ (CiteScore); however, there is scarce information about the correlations among them. In this study, we aimed to evaluate the associations between this bibliometrics in the Radiology, Nuclear Medicine & Medical Imaging category of the Web of Knowledge. We hypothesized the IF did not show the best correlation with other metrics. Retrospective study. We used bibliometrics recorded from the 2017 publicly available versions of the Journal Citation Reports (JCR), SJR ( www.scimagojr.com ), SNIP ( www.journalindicators.com ), and CiteScore ( www.scopus.com ); we also included the Total Cites. We measured the correlations using the Spearman correlation coefficients (RS) for all combinations of the bivariate pair, performed pairwise comparisons of the RS values, and calculated the coefficients of determination. We also tested the statistical significance of the difference between r coefficients between groups. All analyses were conducted with the JMP Pro software. The stronger bivariate correlations were represented by the ES↔Total Cites RS = 0.968, p < 0.001, R2 = 0.937; and the CiteScore↔SJR RS = 0.911, p < 0.001, R2 = 0.829. From 105 possible combinations of pairwise comparisons, 38 depicted a p value > 0.050 which would suggest interchangeability among bivariate correlations. Our findings support our hypothesis that the IF does not show the best correlation between other metrics. Radiologists, interventional radiologist, or nuclear medicine doctors should have a clear understanding of the associations among the journal's bibliometrics for their decision-making during the manuscript submission phase.

The morphology of the deposited particles after a wet agglomerate normal surface impact

Through discrete element modeling, we investigate the breakage, deposition and attachment of wet dust agglomerates during normal surface impacts. The morphology and structure of the deposited dirt layer is studied through statistical analysis of the height profiles. It is found that the deposited layer is influenced by both the structural properties of the primary agglomerates and the impact conditions. The roughness of the deposited dirt layer shows a positive correlation to impact velocity and a negative correlation to the agglomerate moisture content. Within the pendular liquid regime the structural strength of the agglomerates shows a strong correlation to the moisture content while at higher moisture content the correlation becomes weaker. It is also observed that for a given impact velocity agglomerates of various sizes show similar deposition patterns. To unify the results for different agglomerate sizes, a dimensionless surface density is introduced.

Size- and Temperature-Dependent Collision and Deposition Model for Micron-Sized Sand Particles

Sand ingestion and deposition in gas turbine engine components can lead to several operational hazards. This paper discusses a physics-based model for modeling the impact, deposition, and sticking of sand particles to surfaces. The collision model includes both normal and tangential components of impact. The normal collision model divides the impact process into three stages, the elastic stage, the elastic–plastic stage, and full plastic stage, and the recovery process is assumed to be fully elastic. The adhesion loss in the recovery stage is described using Timoshenko's model and Tsai's model, and shows that the two models are consistent under certain conditions. Plastic deformation losses of surface asperities are also considered for particle–wall collisions. The normal impact model is supplemented by an impulse-based tangential model, which includes both sliding and rolling frictions. Sand properties are characterized by size and temperature dependencies. The predicted coefficient of restitution (COR) of micron-sized sand particles is in very good agreement with experimental data at room temperature and at higher temperatures from 1073 K to 1340 K. The predicted COR decreases rapidly at temperatures above 1340 K. There is a strong interplay between the size-dependent properties of micron sand particles and the temperature dependency of yield stress on the collision and deposition characteristics. This is the first physics-based high temperature model including translation and rotation of micron-sized sand particles with sliding and rolling modes in the gas turbine literature.

Table Tennis Ball Impacting Racket Polymeric Coatings: Experiments and Modeling of Key Performance Metrics

The performance of a table tennis racket is often associated with subjective or quantitative criteria such as the adhesion, the control and the speed. Overall, the so-called performance aims at characterizing the impact with the ball. Ultimately, the polymeric layers glued onto the wooden blade play a key role, as evidenced in a previous work where the normal linear (no spin) impact of a ball onto polymeric layers was experimentally and numerically investigated. In this work, more realistic loading conditions leading to varying the incident angle and spin of the ball, were explored. While the sole linear restitution coefficient was determined in the anterior normal impact study, new physical metrics were identified to describe fully the trajectory of the reflected ball after impact. A companion 3D finite elements model was developed where the polymeric time-dependent dissipative compliant behavior measured with dynamic mechanical analysis and compression tests was accounted for. The confrontations with the experimental data highlighted the key role of the polymer intrinsic properties along with the friction coefficient between the ball and the polymer external layer.