Staggering Effects Research Articles

Predicting 28Si projectile fragmentation cross sections with Bayesian neural network method

Abstract This study utilizes the Bayesian neural network (BNN) method in machine learning to learn and predict the cross-section data of 28Si projectile fragmentation for different targets at different energies, and to quantify the uncertainty. The detailed modeling process of BNN is presented, and its prediction results are compared with Cummings, Nilsen, EPAX2, EPAX3, and FRACS models, as well as experimental measurement values. The results reveal that the BNN method achieves the smallest root-mean-square error (RMSE) and the highest agreement with the experimental values compared to other models. Only the BNN method and FRACS model show a significant odd-even staggering effect, but BNN method is more closer to the experimental value. Furthermore, the BNN method is the only model capable of reproducing data features with low cross-section values at Z = 9, and the average ratio of the BNN's predicted to experimental values is close to 1.0. These results demonstrate that the BNN method can accurately reproduce and predict the fragment production cross sections of the 28Si projectile fragmentation, as well as its ability to capture key data characteristics.

Effect of Confinement Level and Staggering on Seismic Performance of Lap-Spliced GFRP-Reinforced Concrete Columns

Effect of Confinement Level and Staggering on Seismic Performance of Lap-Spliced GFRP-Reinforced Concrete Columns

NUMERICAL INVESTIGATIONS OF THERMO-FLUIDIC CHARACTERISTICS IN INNOVATIVE PARALLEL PLATE-FIN HEAT SINK DESIGN SUBJECTED TO PARALLEL FLOW: EXPLORING THE STAGGERING EFFECT

NUMERICAL INVESTIGATIONS OF THERMO-FLUIDIC CHARACTERISTICS IN INNOVATIVE PARALLEL PLATE-FIN HEAT SINK DESIGN SUBJECTED TO PARALLEL FLOW: EXPLORING THE STAGGERING EFFECT

Self-Consistent Calculation of Nuclear Charge Radii in K Isotopes

Fully self-consistent study of the charge radii in Ca region is exemplified by the calculation in the long chains of K isotopes. The neutron-deficient and neutron-rich nuclei with pairing in both neutron and proton sectors, as well as the (semi-) magic nuclei around the closed neutron shells at N = 20, 28, 32 are treated within the Energy Density Functional (EDF) approach with the Fayans functional DF3-a. The performance of the DF3-a is analysed in describing the odd-even staggering effects found both in previous and in more recent CERN-ISOLDE experiments for 36–52K isotopes.

Numerical Analysis on The Effects of Stagger, Thickness, and Curvature on The Propulsion of Tandem Airfoil

The study of the aerodynamics of flapping airfoils is crucial to understand the flight of natural flyers and its potential applications in developing micro air vehicles and wind/water turbine blades. There has been much research on the aerodynamics of flapping wings recently, but there is only a little research relating to the tandem airfoil. Therefore, this study is conducted to determine the aerodynamic characteristics of the tandem airfoil at Re = 100000, typical of insect flight. The tandem airfoil is plunging and pitching harmonically. This study numerically analyzes the effects of stagger, thickness, and curvature on tandem airfoil propulsion. The effects of stagger are studied using NACA 0012, while the effects of thickness are analyzed on NACA 0012, 0015, 0020 and 0030. The simulations to study the effects of curvature are conducted using NACA 0030. The optimum distance of the stagger is X/c = 2.5, but the propulsive efficiency of tandem NACA 0012 is still smaller than two single NACA 0012 airfoils. For the most optimum thickness at 30% of the chord length, the propulsive efficiency of tandem NACA 0030 is higher than two single NACA 0030 airfoils. Meanwhile, the most optimum curvature is 0% because the increase in curvature of the airfoil reduces propulsive efficiency.

The impact of gender on differences in the diagnosis of peripheral arterial disease: the staggering effects of social determinants seen highest in women

Peripheral arterial disease (PAD) is a clinical manifestation of atherosclerosis, affecting primarily the peripheral vasculature in the lower extremities. In its terminal form, PAD can result in critical limb ischemia with subsequent amputation if inappropriately managed. As the prevalence of PAD continues to rise in the United States, disparities in its incidence and treatment have become a major focus point of cardiovascular research. However, most research efforts thus far have focused on the presentation and treatment of PAD in men. Given that women appear to be just as affected by PAD as men, more emphasis is needed on understanding the disparities and challenges affecting women with PAD. This paper aims to identify disparities in the treatment of PAD between males and females, with a closer look at gender disparities between Hispanic and non-Hispanic patients.
 
 Keywords: Peripheral arterial disease, women, Hispanics, disparities

Green HRM - A Novel Approach to the Sustainability of the Health Care Sector

This research investigates the link between environment’s factor and green human resources management (HRM) practices in the Odisha health care organization, including recruiting and selection, training and development, green incentives. A questionnaire survey that was sent to health care organizations in Odisha between March and May 2022 is used to test the study hypotheses. The findings indicate a modest adoption of green human resource management in Odisha hospitals; recruiting and selection showed the highest association, while training and development showed the lowest. Additionally, a statistically significant correlation between the three HRM practises and environmental performance was discovered. To lessen the staggering effects of uncontrolled aspects in the study, such as legislative, cultural, and economic settings, we made the design choice to concentrate on a specific sector. This research, which is said to be the first of its kind in Odisha, explores the role that human resources play in hospitals and other healthcare facilities in delivering environmental performance. It supports the body of literature on environmental preservation and green human resource management, which is underdeveloped in developing nations like (Odisha), India. Keywords-Organizational performance; Green HRM; Performance appraisal; training and development.

The α-particle clustering and half-lives of the newly discovered 207,208Th decay chains within relativistic-Hartree-Bogoliubov approach

The structural and decay properties of the ground state of recently discovered neutron-deficient 207Th and remeasured 208Th isotopes Yang et al. (2022) [26] is examined using the Relativistic-Hartree-Bogoliubov (RHB) formalism using the DD-ME2 parameter set within the preformed cluster-decay model (PCM). The relativistic medium-dependant R3Y so-called DD-R3Y NN potentials are for the first time used to obtain the nucleus-nucleus potential as input into the PCM. The penetration probability is calculated using the WKB approximation, and the preformation probability (Pα) is estimated using our newly derived formula, which is based on parameters well known to influence the α -particle radioactivity. A close correlation is observed between the α-preformation factor and the crucial role of the pairing correlation in the α-decay process. Furthermore, the Pα values for the even-even nuclei are generally found to be of higher magnitude than those for the odd-A nuclei. Our results further affirm that the odd-even staggering effect on the Qα values and its accompanying effects on other observables such as the charge radii and the decay half-lives, which can be largely attributed to the pairing correlation and Pauli blocking of the unpaired valence nucleons.

Nuclear charge radii in Bayesian neural networks revisited

In this work, a refined Bayesian neural network (BNN) based approach with six inputs including the proton number, mass number, and engineered features associated with the pairing effect, shell effect, isospin effect, and “abnormal” shape staggering effect of 181,183,185Hg, is proposed to accurately describe nuclear charge radii. The new approach is able to well describe the charge radii of atomic nuclei with A≥40 and Z≥20. The standard root-mean-square deviation is 0.014 fm for both the training and validation data. In particular, the predicted charge radii of proton-rich and neutron-rich calcium isotopes are found in good agreement with data. We further demonstrate the reliability of the BNN approach by investigating the variations of the root-mean-square deviations with extrapolation distances, mass numbers, and isospin asymmetries.

Simple deep-learning approach for α -decay half-life studies

To exploit the potential of deep learning (DL) in $\ensuremath{\alpha}$-decay studies, we refocus on the essence of DL, which is a nonlinear input-output mapping with a hierarchical learning process. Here, instead of using the residual between experimental data and the calculation, the idea of training DL directly by experimental $\ensuremath{\alpha}$-decay half-life is used. The Levenberg-Marquardt backpropagation algorithm is utilized for fixing free parameters of the mapping. A $\mathcal{K}$-fold cross-validation method is introduced to avoid overfitting and improve the generalization performance of DL, as well as to determine hyperparameters effectively. We find that DL results with both three-dimensional ${Z,A,{Q}_{\ensuremath{\alpha}}}$ and four-dimensional ${Z,A,{Q}_{\ensuremath{\alpha}},l}$ input vectors achieve an impressive accuracy that matches or even exceeds the traditional models. Especially, DL realizes an efficient extraction of the pertinent shell and odd-even staggering effects of half-life solely from the characteristics of ${Q}_{\ensuremath{\alpha}}$ values. On the other hand, the universal decay law (UDL) describes the classical relationship between ${Z,A,{Q}_{\ensuremath{\alpha}}}$ and a-decay half-life, which is homologous with DL. Heuristically, we add the contributions of the angular momentum and blocking effect of unpaired nucleons in the UDL and develop an improved UDL formula.

Aeroelastic modeling and analysis of wings in proximity

This study investigates the effects of aerodynamic interaction on the aeroelastic characteristics of wings in proximity which is considered to be aerodynamically more efficient than the single wing case. The structural model of the wing is based on the first-order shear deformation theory and analyzed by the finite element method. The flow surrounding the wings is governed by potential theory and the aerodynamic loads are computed using the unsteady vortex lattice method. The aeroelastic simulation framework is established by integrating the structural and aerodynamic models within the flexible multibody dynamic program to solve the aeroelastic equations of motion in the time domain. Cantilever wings in proximity, arranged in biplane configuration, with different geometric parameters such as gap, sweep angle, dihedral angle, and stagger are considered in the analysis. The numerical results show that the smaller gap between the wings magnifies the aerodynamic interaction effect and decreases the onset of flutter speed. Sweeping the wing backward further reduces the flutter boundaries of the biplane model mainly due to changes in the wing's structural modal whereas the effect of dihedral angles is understated. The effect of stagger is more evident for a smaller gap and mostly leads to an increase in the flutter boundary. The aeroelastic responses are independent of initial disturbance and show a natural tendency to oscillate with a phase difference. This investigation warrants the importance of considering biplane wings as a single system for a gap lower than wing chord length as well as the significance of other geometric parameters in the aeroelastic calculation.

Addressing Women’s Needs with Human Immunodeficiency Virus (HIV) and Enhancing the Visibility of Pharmacists in the Public Health Arena

Human Immunodeficiency Virus (HIV) continues to have a staggering effect on women’s lives in the United States (U.S.). Women Living With HIV (WLWH) face many challenges, such as mental health disorders, compared to their male counterparts. These diagnoses make women more disproportionally affected, and meaningful healthcare interventions must address these conditions. This review has three foci: WLWH in the U.S., their access to care and staying in care once antiretroviral treatment has been initiated, coping with mental health, and the role of the U.S. pharmacists in access to the treatment. Pharmacists are the most easily accessible healthcare profession in the U.S. For example, 93% of American customers live within 5 miles of a community pharmacy. Pharmacists are the last healthcare provider with whom the patient interacts before a medication is dispensed; thus, they are in an ideal position to intervene. Engaging pharmacists to provide care for patients with chronic disease states such as HIV has resulted in positive outcomes. Although there are global and U.S. studies that emphasize the role of pharmacists in directing care for persons living with HIV, there is a lack of studies conducted about the role of pharmacists in managing mental health. Future research must address WLWH and mental health conditions to develop targeted interventions from an interdisciplinary team perspective.

Diagnosis of COVID-19 based on chest X-ray images using pre-trained deep convolutional neural networks

The novel coronavirus (COVID-19) that emerged and transmitted from China (Wuhan City) had a staggering effect on public health and the world economy. The early diagnosis of COVID-19 has become more important for its treatment and for controlling its spread due to its highly transmissible nature. In addition, the restricted supply of test kits calls for an alternative system for diagnosis. Since radiological images of chest of patients with COVID-19 show abnormalities, it is possible to diagnose COVID-19 utilizing chest X-ray images. Therefore, by applying deep convolution neural network (CNN), we have presented a diagnosis of COVID-19 based on chest X-ray images in this paper. For the diagnosis of COVID-19, an exhaustive comparative performance analysis of 16 state-of-the-art models is presented. Moreover, each model is trained with three approaches: transfer learning, fine tuning and scratch learning. The experiments were conducted on the dataset that comprises of 127 images of COVID-19, 500 images of Pneumonia and 500 images of normal cases. We have performed the experiments in two scenarios: binary classification (COVID-19 vs. Normal) and multiclass classification (COVID-19 vs. Pneumonia vs. Normal). Further, we have applied cost-sensitive learning technique to handle the class imbalance issue. In this study, InceptionResNetV2 model with fine-tuning approach achieved highest classification accuracy of 99.20% in binary classification and Xception model achieved classification accuracy of 89.33% in multiclass classification among all considered models. To validate our approach, we have presented the performance of our model on three other datasets and achieved adequate classification accuracy. Hence, the promising results demonstrate that the fine-tuning of deep CNN models is an effective way for diagnosis of COVID-19 and therefore, it can be deployed in diagnostic centers to assist radiologist after its validation with more prominent datasets.

Effect of Stagger on Low-Speed Performance of Busemann Biplane Airfoil

In this study, the low-speed performances of the Busemann biplane were clarified, focusing on the relative contributions of the upper and lower elements to the total aerodynamic characteristics of the biplane. Also, the effects of the staggered biplane, which changes the horizontal distance between two wings in a biplane configuration, were investigated by balance measurements and numerical simulations. The flow velocity was 15 m/s, and the Reynolds number based on the airfoil chord length was 2.1 × 105. In the tests of the integrated biplane wing, the attack angles of the wing elements were varied by a balance system and turntable, which were set in the wind tunnel sidewall. The results show that the lower element generated most of the lift and drag of the Busemann biplane (or the baseline biplane model with no stagger) at high angles of attack. At angles above 20 deg, the contribution of the lower element to total aerodynamic characteristics is almost constant, with 95% of the total lift and 88% of the total drag. The total lift and drag of the baseline model were smaller than the sum of the individual elements that were treated as a single configuration. The increments of lift and drag due to the stagger effects were confirmed, especially at high angles of attack. When the stagger value increases, the high-pressure area near the leading edge of the lower surface of the upper element also increases, which increases the lift and drag of the up-per element. This is the main reason for the increments of total lift and drag of the biplane model. The stagger effects also prevented the leading-edge separation of the lower element in the biplane configuration and increased the lift slopes of the biplane model.

Odd-even staggering and shell effects of charge radii for nuclei with even Z from 36 to 38 and from 52 to 62

A unified theoretical model reproducing charge radii of known atomic nuclei plays an essential role in making extrapolations for unknown nuclei. Recently developed new ansatz which phenomenologically takes into account the neutron-proton short-range correlations ($np$-SRCs) can describe the discontinuity properties and odd-even staggering (OES) effect of charge radii along isotopic chains remarkably well. In this work, we further review the modified root-mean-square (rms) charge radii formula in the framework of relativistic mean field (RMF) theory. The charge radii are calculated along various isotopic chains that include the nuclei featuring the $N=50$ and 82 magic shells. Our results suggest that RMF with and without considering a correction term give an almost similar trend of nuclear size for some isotopic chains with open proton shell, especially the abrupt increases across the strong neutron closed shells and the OES behaviors. This reflects that the $np$-SRCs have almost no influence for some nuclei due to the strong coupling between different levels around Fermi surface. The weakening OES behavior of nuclear charge radii is observed generally at completely filled neutron shells and this may be proposed as a signature of magic indicator.

COVID-19, microbiopolitics and species precarity in the anthropocene

ABSTRACT The turn towards deep entanglement precipitated by the Anthropocene has seen a rise in probiotic approaches towards microorganisms that highlight human-microbe relationalities. However, COVID-19 complicates this relationality not least considering its staggering effects on human society which have reinforced notions of solidarity and common crisis, as evidenced in the various biopolitical measures or the ‘outbreak narrative’. In this regard, Heather Paxson’s formulation of microbiopolitics as the construction and evaluation of categories of microorganisms serves as a useful model to ask what kind of microbiopolitics the coronavirus pandemic makes possible and what these strategies imply for collaborative human-microbe relations or multispecies flourishing. The microbiopolitics that marks the pandemic as new mutations and strains of viruses are being identified and a future of zoonotic diseases is anticipated shows this microbial relationality as already present. However, to make sense of entanglement in the pandemic is to recognize microbiopolitics as socio-politically contingent and undercut by anthropocentric anxieties for our own well-being but also as a species precarity. This species precarity for humans shows that the pandemic is differentially experienced as a self while negotiating its relations with non-human others. It is what demands of us that we develop strategies for living along with the virus or other microbes for the foreseeable future.

Extended deformable tension-shear model for graphene layered materials with non-uniform staggering

Current theoretical works on the mechanical behaviors of graphene layered materials are usually limited to the regular staggering. But, more practical staggering modes haven't been paid enough attention. In this work, we extend the deformable tension-shear (DTS) model to non-uniform staggering through two different methods, i.e. eigenvalue method and isolated break method. Then, different staggering modes such as the regular staggering with offset, stair-wise staggering, and non-uniform staggering are studied under the framework of the extended DTS model. An effective shear load transfer length lc=Dh0/G is defined, where D is the in-plane tension stiffness of graphene, h0 is the interlayer distance, G is the interlayer shear modulus. It is found the ratio of minimum in-plane adjacent break distance to the effective shear load transfer length Δmin/lc plays an important role in determining the mechanical behaviors of graphene layered materials. For example, when Δmin<0.5lc the intralayer force distribution in platelet is linear which is the uniform shear strain solution of nacre-like structure, while when Δmin>8lc, the intralayer force has a long plateau away from the break and the plateau value is also the same at different platelets. Therefore, the in-plane interaction of adjacent breaks can be ignored for large size of graphene sheet, based on which the in-plane isolated break solution is derived. Then, the interlayer force concentration factor (IFCF) is analytically obtained for arbitrary N graphene layers with r aligned breaks. Further analysis indicates the in-plane isolated break solution gives the upper bound of IFCF for the uniform stair-wise staggering but may underestimate the IFCF for random staggering. The results presented herein comprehensively explore the staggering effect on mechanical behaviors of graphene layered materials which may guide the design of high-performance nacre-like materials.

Evaluating the Impacts of Smallholder Farmer’s Participation in Modern Agricultural Value Chain Tactics for Facilitating Poverty Alleviation—A Case Study of Kiwifruit Industry in Shaanxi, China

Market-based initiatives like agriculture value chain (AVC) are becoming progressively pervasive to support smallholder rural farmers and assist them in entering larger market interventions and providing a pathway of enhancing their socioeconomic well-being. Moreover, it may also foster staggering effects towards the post-era poverty alleviation in rural areas and possessed a significant theoretical and practical influence for modern agricultural development. The prime objective of the study is to explore the effects of smallholder farmers’ participation in the agricultural value chain for availing rural development and poverty alleviation. Specifically, we have crafted the assessment employing pre-production (improved fertilizers usage), in-production (modern preservation technology), and post-production (supply chain) participation and interventions of smallholder farmers. The empirical data has been collected from a micro survey dataset of 623 kiwifruit farmers from July to September in Shaanxi, China. We have employed propensity score matching (PSM), probit, and OLS models to explore the multidimensional poverty reduction impact and heterogeneity of farmers’ participation in the agricultural value chain. The results show that the total number of poor farmers who have experienced one-dimensional and two-dimensional poverty is relatively high (66.3%). We also find that farmers’ participation in agricultural value chain activities has a significant poverty reduction effect. The multidimensional poverty level of farmers using improved fertilizer, organizational acquisition, and using storage technology (compared with non-participating farmers) decreased by 30.1%, 46.5%, and 25.0%, respectively. The multidimensional poverty reduction degree of male farmers using improved fertilizer and participating in the organizational acquisition is greater than that of women. The multidimensional poverty reduction degree of female farmers using storage and fresh-keeping technology has a greater impact than the males using storage and improved storage technology. Government should widely promote the value chain in the form of pre-harvest, production, and post-harvest technology. The public–private partnership should also be strengthened for availing innovative technologies and infrastructure development.

An Experimental Analysis on the Effects of Stagger on the Aerodynamic Forces of Tandem Wings

This study is inspired by the flapping motion of natural flyers: insects. Many insects have two pairs of wings referred as tandem wings. Literature review indicates that the effects of tandem wing are influenced by parameters such as stagger (the stream-wise distance between the aerodynamic center of the front and the rear airfoil), angle-of-attack and flow velocity. As a first stage, this study focuses on the effects of stagger (St) on the aerodynamic performance of tandem wings. A recent numerical study of stagger on tandem airfoils in turbulent flow (Re = 6000000) concluded that a larger stagger resulted in a decrease in lift force, and an increase in drag force. However, for laminar flow (Re = 2000), increasing the stagger was not found to be detrimental for aerodynamic performance. Another work also revealed that the maximum lift coefficient for a tandem configuration decreased with increasing stagger. The focus of this study is to perform an experimental analysis of tandem two-dimensional (2D) NACA 0012 airfoils. The two airfoils are set at the same angle-of-attack of 0° to 15° with 5° interval and three variations of stagger: 1c, 1.5c and 2c. The experiments are conducted using an open-loop-subsonic wind tunnel at a Reynolds number of 170000. The effects of St on the aerodynamic forces (lift and drag) are analyzed

Spectral Explanation for Statistical Odd-Even Staggering in Few Fermions Systems

Odd-even statistical staggering in a Lipkin-like few fermions model has been recently encountered. Of course, staggering in nuclear binding energies is a well established fact. Similar effects are detected in other finite fermion systems as well, as for example, ultra small metallic grains and metal clusters. We work in this effort with the above-mentioned Lipkin-like, two-level fermion model and show that statistical staggering effects can be detailedly explained by recourse to a straightforward analysis of the associated energy-spectra.