bluuebunny/crossref_metadata_2025_split huggingface dataset:
Focused polarization ellipse field singularities: interaction of spin-orbital angular momentum and the formation of optical Möbius strips
Authors: Pal Sushanta Kumar , Somers Lavi , Singh Rakesh Kumar , Senthilkumaran P , Arie Ady 
Published: March 2023

Abstract
We study here the intensity distribution and formation of optical polarization Möbius strips by tightly focusing of C-point singularity beams. These beams are characterized by a central circular polarization point (C-point) surrounded by a spatially varying elliptic polarization. Under tight focusing conditions, the different polarization components of the beam interfere and exhibit clear difference between left-handed and right handed input beams. The transverse polarization distribution at the focal plane is similar to the input distribution for left-handed lemon beam, but exhibits 180° rotation for right handed lemon beam. Moreover, the longitudinal polarization component exhibits spiral phase distribution, owing to spin-orbit angular momentum conversion at the focal plane, with opposite winding directions for the left-handed and right-handed input beams. We show that the shape of the resulting Möbius strip is determined by the helicity of the C-point and by the polarization singularity index, which is the contour integral of polarization ellipse angle around the singularity. It is found that inverting the helicity leads to 180° rotation in the focal plane intensity distribution, accompanied by handedness inversion for the polarization ellipses. The number of separatrices in the input polarization distribution is equivalent to the number of twist points of the Möbius strip in the focal plane, as well as to the number of intensity zeros in the z-component of the focused field. These phenomena are observed for beams with a bright C-point, but also for dark C-point, in which the electric field is zero at the center of the beam.
Dimensional crossover in driving-rate induced criticality on the hysteresis-loop of disordered ferromagnetic systems
Authors: Spasojević Djordje , Mijatović Svetislav , Janićević Sanja 
Published: March 2023

Abstract
We study the effect of finite driving rate on the nonequilibrium hysteresis-loop criticality with the systems’ nonequilateral geometry constraints allowing the dimensional crossover from three-dimensional to two-dimensional disordered ferromagnetic systems . For each system’s thickness, the disorder is fixed above the critical line for adiabatic driving, such that the emergent critical behaviors are solely attributed to the increased driving rates of the external field.We demonstrate it by computing the pertaining magnetizations and coercive fields, changes in avalanche distributions and shapes, and correlation functions of spin-flip events where the pace of the field increments are varied in a broad range. Our results reveal that the driving field rate profoundly affects system evolution attaining three distinct regimes of the induced criticality at the proper thickness-dependent rate values. In particular, these regimes are characterized by the occurrence of non-spanning avalanches (slow driving), the first appearance of spanning avalanches (intermediate regime), and being overwhelmed by system-spanning avalanches (fast driving regime) for a given thickness. Our results will bring some critical insights to the theoretical and experimental studies on the field-driven nonequilateral systems both for conceptual reasons and the versatility of their applications..
A sluggish random walk with subdiffusive spread
Authors: Zodage Aniket , Allen Rosalind J , Evans Martin R , Majumdar Satya N 
Published: March 2023

Abstract
We study a one-dimensional sluggish random walk with space-dependent transition probabilities between nearest-neighbour lattice sites. Motivated by trap models of slow dynamics, we consider a model in which the trap depth increases logarithmically with distance from the origin. This leads to a random walk which has symmetric transition probabilities that decrease with distance

|

k

|

from the origin as

1

/

|

k

|

for large

|

k

|

. We show that the typical position after time t scales as

t

1

/

3

with a nontrivial scaling function for the position distribution which has a trough (a cusp singularity) at the origin. Therefore an effective central bias away from the origin emerges even though the transition probabilities are symmetric. We also compute the survival probability of the walker in the presence of a sink at the origin and show that it decays as

t

−
1

/

3

at late times. Furthermore we compute the distribution of the maximum position, M(t), to the right of the origin up to time t, and show that it has a nontrivial scaling function. Finally we provide a generalisation of this model where the transition probabilities decay as

1

/

|

k

|

α

with α > 0.
Remote linkage of record-breaking U.S. Tornado outbreaks to the tropical cyclone in western North Pacific in December 2021
Authors: Jiang Ning , Liu Boqi , Zhu Congwen , Chen Yanying 
Published: March 2023

Abstract
The frequency of tornadoes usually peaks during spring to summer rather than winter in climatology. However, the United States (U.S.) experienced more than 200 tornadoes in December 2021, which broke the historical record and caused 87 fatalities. Historically, the frequency of tornadoes in December tends to increase under El Niño conditions. Our results show that the monthly large-scale weather regime conducive to these record-breaking tornado outbreaks under a La Niña condition is closely associated with Typhoon Nyatoh in the western North Pacific. As the tropical cyclone (TC) recurved into the mid-latitudes, its interaction with the extratropical flows has caused distortions in the Asian jet stream and the dramatic development of anomalous anticyclone west of the dateline, which in turn strongly regulated the response of the monthly atmospheric teleconnection to La Niña forcing. Accurate forecasts of the monthly mean circulation for December 2021 first appeared in the European Center for Medium-Range Weather Forecasts sub-seasonal to seasonal forecasts from 29 November, with a forecast skill closely related to that of Typhoon Nyatoh. Given most studies on the warm seasons with frequent tornadoes, the present results advance our understanding of the TC effect on the monthly atmospheric response to El Niño-Southern Oscillation forcing and its linkage to the tornado occurrence during boreal winter.
The generalized Giambelli formula and polynomial KP and CKP tau-functions
Authors: Kac Victor , van de Leur Johan 
Published: March 2023

Abstract
The first part of the paper is devoted to two descriptions of all polynomial tau-functions of the Kadomtsev-Petviashvili (KP) hierarchy: by a generalized Jacobi-Trudi formula, and a generalized Giambelli formula. We use the latter formula in the second part to obtain all polynomial tau-functions of the CKP hierarchy and its n-reductions. In particular, for

n
=
3

we find all polynomial tau-functions of the Kaup-Kupershmidt hierarchy.
Supercurrent and electromotive force generations by the Berry connection from many-body wave functions
Authors: Koizumi Hiroyasu 
Published: March 2023

Abstract
The velocity field composed of the electromagnetic field vector potential and the Berry connection from many-body wave functions explains supercurrent generation, Faraday’s law for the electromotive force (EMF) generation, and other EMF generations whose origins are not electromagnetism. An example calculation for the EMF from the Berry connection is performed using a model for the cuprate superconductivity.
Implementing quantum Fourier transform using three qubits
Authors: Yachi Mouhcine , Hab-arrih Radouan , Jellal Ahmed 
Published: March 2023

Abstract
Using the circulant symmetry of a Hamiltonian describing three qubits, we realize the quantum Fourier transform. This symmetry allows us to construct a set of eigenvectors independently on the magnitude of physical parameters involved in the Hamiltonian and as a result the entanglement will be maintained. The realization will be leaned on trapped ions and the gate implementation requires an adiabatic transition from each spin product state to Fourier modes. The fidelity was numerically calculated and the results show important values. Finally, we discuss the acceleration of the gate by using the counter-driving field.
A closure for the master equation starting from the dynamic cavity method
Authors: Aurell Erik , Machado Perez David , Mulet Roberto 
Published: March 2023

Abstract
We consider classical spin systems evolving in continuous time with interactions given by a locally tree-like graph. Several approximate analysis methods have earlier been reported based on the idea of Belief Propagation / cavity method. We introduce a new such method which can be derived in a more systematic manner using the theory of Random Point Processes. Within this approach, the master equation governing the system’s dynamics is closed via a set of differential equations for the auxiliary cavity probabilities. The numerical results improve on the earlier versions of the closure on several important classes of problems. We re-visit here the cases of the Ising ferromagnet and the Viana–Bray spin-glass model.
Constraining Weil–Petersson volumes by universal random matrix correlations in low-dimensional quantum gravity
Authors: Weber Torsten , Haneder Fabian , Richter Klaus , Urbina Juan Diego 
Published: March 2023

AbstractBased on the discovery of the duality between Jackiw–Teitelboim quantum gravity and a double-scaled matrix ensemble by Saad, Shenker and Stanford in 2019, we show how consistency between the two theories in the universal random matrix theory (RMT) limit imposes a set of constraints on the volumes of moduli spaces of Riemannian manifolds. These volumes are given in terms of polynomial functions, the Weil–Petersson (WP) volumes, solving a celebrated nonlinear recursion formula that is notoriously difficult to analyse. Since our results implylinearrelations between the coefficients of the WP volumes, they therefore provide both a stringent test for their symbolic calculation and a possible way of simplifying their construction. In this way, we propose a long-term program to improve the understanding of mathematically hard aspects concerning moduli spaces of hyperbolic manifolds by using universal RMT results as input.
Comparison of methods for turbulence Doppler frequency shift calculation in Doppler reflectometer
Authors: ZHONG Xiaoming , ZOU Xiaolan , ZHOU Chu , LIU Adi , ZHUANG Ge , FENG Xi , ZHANG Jin , JI Jiaxu , FAN Hongrui , LIU Shen , WANG Shifan , GAO Liutian , SHI Wenxiang , LAN Tao , LI Hong , XIE Jinlin , MAO Wenzhe , LIU Zixi , LIU Wandong 
Published: March 2023

Abstract
The Doppler reflectometer (DR), a powerful diagnostic for the plasma perpendicular velocity (u
⊥) and turbulence measurement, has been widely used in various fusion devices. Many efforts have been put into extracting the Doppler shift from the DR signal. There are several commonly used methods for Doppler shift extraction, such as the phase derivative, the center of gravity, and symmetric fitting (SFIT). However, the strong zero-order reflection component around 0 kHz may interfere with the calculation of the Doppler shift. To avoid the influence of the zero-frequency peak, the asymmetric fitting (AFIT) method was designed to calculate the Doppler shift. Nevertheless, the AFIT method may lead to an unacceptable error when the Doppler shift is relatively small compared to the half width at half maximum (HWHM). Therefore, an improved method, which can remove the zero-frequency peak and fit the remaining Doppler peak with a Gaussian function, is devised to extract the Doppler shift. This method can still work reliably whether the HWHM is larger than the Doppler shift or not.
Effects of anode material on the evolution of anode plasma and characteristics of intense electron beam diode
Authors: HUA Ye , WU Ping , WAN Hong , BAI Shuxin , GONG Jinyu , ZHU Meng , BAI Xianchen , ZHANG Guangshuai 
Published: March 2023

Abstract
In this paper, three kinds of materials including graphite, titanium (Ti) and molybdenum (Mo) are used as anodes to figure out the influence factors of anode material on the characteristics of the intense electron beam diode. The results show that the characteristics of diode are mainly determined by the cathode plasma motion under a 15 mm diode gap, in which the typical electron beam parameters are 280 kV, 3.5 kA. When the diode gap is reduced to 5 mm, the voltage of the electron beam reduces to about 200 kV, and its current increases to more than 8.2 kA. It is calculated that the surface temperatures of Ti and Mo anodes are higher than their melting points. The diode plasma luminescence images show that Ti and Mo anodes produce plasmas soon after the bombardment of electron beams. Ti and Mo lines are respectively found in the plasma composition of Ti and Mo anode diodes. Surface melting traces are also observed on Ti and Mo anodes by comparing the micromorphologies before and after bombardment of the electron beam. These results suggest that the time of anode plasma generation is closely related to the anode material. Compared with graphite, metal Ti and Mo anodes are more likely to produce large amounts of plasma due to their more significant temperature rise effect. According to the moment that anode plasma begins to generate, the average expansion velocities of cathode and anode plasma are estimated by fitting the improved space-charge limited flow model. This reveals that generation and motion of the anode plasma significantly affect the characteristics of intense electron beam diode.
Bounded/periodic solutions for a class of scalar delay differential equations
Authors: Ai Shangbing 
Published: March 2023

In this paper we use upper and lower solutions, the monotone iterative method, and the Schauder fixed point theorem to establish a new result on the existence of bounded/periodic solutions over

R

\mathbb R

for a class of scalar delay differential equations of the form

d
u

d
t

=
f
(
t
,
u
(
t
)
,
u
(
t
−

r
1

)
,
⋯
,
u
(
t
−

r
m

)
)

\begin{equation*} \frac {du}{dt}=f(t,u(t), u(t-r_1), \cdots , u(t-r_m)) \end{equation*}

with constant delays, where

f
f

satisfies a one-sided Lipschitz condition on the state variables

u
(
t
)

u(t)

,

u
(
t
−

r
1

)

u(t-r_1)

, …,

u
(
t
−

r
m

)

u(t-r_m)

. Applications of this result to some population models are given.
The Optimal Use of Fines and Imprisonment Revisited
Authors: D'Antoni Massimo , Friehe Tim , Tabbach Avraham 
Published: March 2023

Abstract
We study the optimal use of fines and imprisonment when wealth varies across individuals and may be observable or not. When wealth is observable, the optimal total sanction includes the maximum fine and either zero or maximum imprisonment. Imprisonment often complements the fine, therefore the total sanction increases with wealth. However, with unobservable wealth, total sanctions must weakly decrease with wealth to satisfy incentive compatibility constraints. The total sanction for low-wealth individuals may include maximum imprisonment, while high-wealth individuals may face no imprisonment and often less than maximum fines. The inability to observe wealth aligns policy prescriptions with actual enforcement policy and lowers social welfare.
Systematically missing data in causally interpretable meta-analysis
Authors: Steingrimsson Jon A , Barker David H , Bie Ruofan , Dahabreh Issa J 
Published: March 2023

Summary
Causally interpretable meta-analysis combines information from a collection of randomized controlled trials to estimate treatment effects in a target population in which experimentation may not be possible but from which covariate information can be obtained. In such analyses, a key practical challenge is the presence of systematically missing data when some trials have collected data on one or more baseline covariates, but other trials have not, such that the covariate information is missing for all participants in the latter. In this article, we provide identification results for potential (counterfactual) outcome means and average treatment effects in the target population when covariate data are systematically missing from some of the trials in the meta-analysis. We propose three estimators for the average treatment effect in the target population, examine their asymptotic properties, and show that they have good finite-sample performance in simulation studies. We use the estimators to analyze data from two large lung cancer screening trials and target population data from the National Health and Nutrition Examination Survey (NHANES). To accommodate the complex survey design of the NHANES, we modify the methods to incorporate survey sampling weights and allow for clustering.
Functional network reconfiguration supporting memory-guided attention
Authors: Isenburg Kylie , Morin Thomas M , Rosen Maya L , Somers David C , Stern Chantal E 
Published: March 2023

Abstract
Studies have identified several brain regions whose activations facilitate attentional deployment via long-term memories. We analyzed task-based functional connectivity at the network and node-specific level to characterize large-scale communication between brain regions underlying long-term memory guided attention. We predicted default mode, cognitive control, and dorsal attention subnetworks would contribute differentially to long-term memory guided attention, such that network-level connectivity would shift based on attentional demands, requiring contribution of memory-specific nodes within default mode and cognitive control subnetworks. We expected that these nodes would increase connectivity with one another and with dorsal attention subnetworks during long-term memory guided attention. Additionally, we hypothesized connectivity between cognitive control and dorsal attention subnetworks facilitating external attentional demands. Our results identified both network-based and node-specific interactions that facilitate different components of LTM-guided attention, suggesting a crucial role across the posterior precuneus and restrosplenial cortex, acting independently from the divisions of default mode and cognitive control subnetworks. We found a gradient of precuneus connectivity, with dorsal precuneus connecting to cognitive control and dorsal attention regions, and ventral precuneus connecting across all subnetworks. Additionally, retrosplenial cortex showed increased connectivity across subnetworks. We suggest that connectivity from dorsal posterior midline regions is critical for the integration of external information with internal memory that facilitates long-term memory guided attention.
Generalization of cognitive maps across space and time
Authors: Sherrill Katherine R , Molitor Robert J , Karagoz Ata B , Atyam Manasa , Mack Michael L , Preston Alison R 
Published: March 2023

Abstract
Prominent theories posit that associative memory structures, known as cognitive maps, support flexible generalization of knowledge across cognitive domains. Here, we evince a representational account of cognitive map flexibility by quantifying how spatial knowledge formed one day was used predictively in a temporal sequence task 24 hours later, biasing both behavior and neural response. Participants learned novel object locations in distinct virtual environments. After learning, hippocampus and ventromedial prefrontal cortex (vmPFC) represented a cognitive map, wherein neural patterns became more similar for same-environment objects and more discriminable for different-environment objects. Twenty-four hours later, participants rated their preference for objects from spatial learning; objects were presented in sequential triplets from either the same or different environments. We found that preference response times were slower when participants transitioned between same- and different-environment triplets. Furthermore, hippocampal spatial map coherence tracked behavioral slowing at the implicit sequence transitions. At transitions, predictive reinstatement of virtual environments decreased in anterior parahippocampal cortex. In the absence of such predictive reinstatement after sequence transitions, hippocampus and vmPFC responses increased, accompanied by hippocampal-vmPFC functional decoupling that predicted individuals’ behavioral slowing after a transition. Collectively, these findings reveal how expectations derived from spatial experience generalize to support temporal prediction.
Identifying autism spectrum disorder using edge-centric functional connectivity
Authors: Sun Ang , Wang Jiaojian , Zhang Junran 
Published: March 2023

Abstract
Brain network analysis is an effective method to seek abnormalities in functional interactions for brain disorders such as autism spectrum disorder (ASD). Traditional studies of brain networks focus on the node-centric functional connectivity (nFC), ignoring interactions of edges to miss much information that facilitates diagnostic decisions. In this study, we present a protocol based on an edge-centric functional connectivity (eFC) approach, which significantly improves classification performance by utilizing the co-fluctuations information between the edges of brain regions compared with nFC to build the classification mode for ASD using the multi-site dataset Autism Brain Imaging Data Exchange I (ABIDE I). Our model results show that even using the traditional machine-learning classifier support vector machine (SVM) on the challenging ABIDE I dataset, relatively high performance is achieved: 96.41% of accuracy, 98.30% of sensitivity, and 94.25% of specificity. These promising results suggest that the eFC can be used to build a reliable machine-learning framework to diagnose mental disorders such as ASD and promote identifications of stable and effective biomarkers. This study provides an essential complementary perspective for understanding the neural mechanisms of ASD and may facilitate future investigations on early diagnosis of neuropsychiatric disorders.
COVID-19 and food insecurity in Africa: A review of the emerging empirical evidence
Authors: Jr. Tabe-Ojong Martin Paul , Nshakira-Rukundo Emmanuel , Haile Gebrekidan Bisrat 
Published: March 2023

Abstract
The coronavirus disease (COVID-19) risks rolling back many of the efforts and global successes recorded in reducing poverty and food insecurity. We undertake a systematic search and review of the growing microeconomic literature on the association between COVID-19 and food insecurity in Africa, discussing its implications for food policy and research. Furthermore, we review the various coping strategies households employ to build resilience to COVID-19. The evidence indicates that COVID-19 is associated with an increase in food insecurity both ex-ante and ex-durante. Given the covariate nature of COVID-19 and associated control mechanisms, current evidence is short of providing clear causal learning. We provide some potential interesting areas where future efforts can be geared to improve learning on the relationship between COVID-19, food insecurity, and building resilience to shocks.