bluuebunny/crossref_metadata_2025 huggingface dataset:
CRE mice exhibit hyperactive and impulsive behavior affecting their learning and retention performances
Authors: Desor Frédéric , El Hajj Aseel , Herzine Ameziane , Djelti Fathia , Bombail Vincent , Denis Isabelle , Oster Thierry , Malaplate Catherine , Lanhers Marie-Claire , Yen Frances T. , Claudepierre Thomas
Published: February 2024

CRE recombinase is a protein that recognizes and mediates site-specific recombination between loxP site sequences. TheCre/loxPrecombination system has become a useful tool for genetic manipulation. Spatial regulation of recombination can be achieved by using cell type-specific promoters that drive expression of CRE in the tissue of interest. The temporal regulation can be obtained with CreER recombinase, which consists of Cre fused to mutated hormone-binding domain of the estrogen receptor (ER). In the more improved versions of the construct, the CRE-mediated gene regulation can be controlled both spatially and temporally, by combining tissue-specific expression of a CreER recombinase with its tamoxifen-dependent activity. We recently generated and characterized an astrocyte specific mutant of the lipolysis-stimulated lipoprotein receptorlsrgene by crossing Glast ERT2 mice with floxedlsrmice (El Hajj et al., 2022). During the behavioral analysis of generated mice, we identified specific hyperactive traits in the Glast ERT2 mice (CRE mice) that prevented them from being used as a control group. Here we further assessed the hyperactive trait of those CRE mice using a battery of behavioral tests. We showed that CRE mice exhibited hyperactive behavior combined with attention-deficit, sleep disturbance and impulsivity that affect their learning and memorization performances. These mice may therefore serve as a model to study attention deficit / hyperactivity disorder. Our work also pointed out the need for proper behavioral analysis of control groups in transgenic animal generation to avoid misinterpretation and misattribution of behavioral traits.
Parameter Estimation in Brain Dynamics Models from Resting-State fMRI Data using Physics-Informed Neural Networks
Authors: Sotero Roberto C. , Sanchez-Bornot Jose M. , Shaharabi-Farahani Iman
Published: February 2024

Conventional modeling of the Blood-Oxygen-Level-Dependent (BOLD) signal in resting-state functional Magnetic Resonance Imaging (rsfMRI) struggle with parameter estimation due to the complexity of brain dynamics. This study introduces a novel brain dynamics model (BDM) that directly captures BOLD signal variations through differential equations. Unlike dynamic causal models or neural mass models, we integrate hemodynamic responses into the signal dynamics, considering both direct and network-mediated neuronal activity effects. We utilize Physics-Informed Neural Networks (PINNs) to estimate the parameters of this BDM, leveraging their ability to embed physical laws into the learning process. This approach simplifies computational demands and increases robustness against data noise, providing a comprehensive tool for analyzing rsfMRI data. Leveraging the functional connectivity matrices scaled by the estimated parameters, we apply a state-of-the-art community detection method to elucidate the network structure. Our analysis reveals significant differences in the participation coefficients of specific brain regions when comparing neurotypical individuals to those with Autism Spectrum Disorder (ASD), with distinct patterns observed between male and female cohorts. These differences are consistent with regions implicated in previous studies, reinforcing the role of these areas in ASD. By integrating PINNs with advanced network analysis, we demonstrate a robust approach for dissecting the complex neural signatures of ASD, providing a promising direction for future research in neuroimaging and the broader field of computational neuroscience.
A Real-time Multi-Subject Three Dimensional Pose Tracking System for Analyzing Social Behaviors of Non-human Primates
Authors: Cheng Chaoqun , Huang Zijian , Zhang Ruiming , Huang Guozheng , Wang Han , Tang Likai , Wang Xiaoqin
Published: February 2024

The ability to track positions and poses (body parts) of multiple monkeys in a 3D space in real time is highly desired by non-human primate (NHP) researchers in behavioral and systems neuroscience because it allows both analyzing social behaviors among multiple NHPs and performing close-loop experiments (e.g., delivering sensory or optogenetics stimulation during a particular behavior). While a number of animal pose tracking systems have been reported, nearly all published work lacks the real-time analysis capacity. Existing methods for tracking freely moving animals have been developed primarily for rodents which typically move on a 2D space. In contrast, NHPs roam in a 3D space and move at a much faster speed than rodents. We have designed a real-time 3D pose tracking system (MarmoPose) based on deep learning to capture and quantify social behaviors in natural environment of a highly social NHP species, the common marmosets (Callithrix jacchus) which has risen to be an important NHP model in neuroscience research in recent years. This system has minimum hardware requirement and can accurately track the 3D poses (16 body locations) of multiple marmosets freely roaming in their homecage. It employs a marmoset skeleton model to optimize the 3D poses and estimate invisible body locations. Furthermore, it achieves high inference speed and provides an online processing module for real-time closed-loop experimental control based on the 3D poses of marmosets. While this system is optimized for marmosets, it can also be adapted for other large animal species in a typical housing environment with minimal modifications.
Force, angle, and velocity parameters of finger movements are reflected in corticospinal excitability
Authors: Brandt Ida Marie , Lundbye-Jensen Jesper , Grunbaum Thor , Christensen Mark Schram
Published: February 2024

Identifying which movement parameters are reflected in the corticospinal excitability (CSE) will improve our understanding human motor control. Change in CSE measured with transcranial magnetic stimulation (TMS)-induced motor evoked potentials (MEPs) can probe the content of the signal from primary motor cortex (M1) through the corticospinal pathway and spinal motoneurons to the muscle. Here we used MEPs to investigate which movement- related parameters are reflected in CSE in 33 healthy adults. In three separate tasks, we evaluated which movement parameter(s), force, angle, and velocity, are reflected in the MEP amplitude during movement preparation and movement execution. Bayesian model comparison in a forward feature selection framework identified force and velocity measures as reflected in the MEP amplitude during movement preparation, and force, angle, and velocity measures as reflected in the MEP amplitude during movement execution. Importantly, we included measures of electromyography (EMG) in the forward feature selection, and the parameter measures are included only if they add explanatory power of MEP amplitude in addition to the EMG. These findings show that when taking EMG measures into account, all three movement parameters force, angle, and velocity are reflected in CSE. These findings propose a flexible and task-dependent form of signaling in the motor system that allows parameter-specific modulation of CSE to accurately control finger movements.
Dysregulation of macrophage lipid metabolism underlies intracellular bacterial neuroinvasion
Authors: Sha Zhou , Yang Kun , Fu Shoupeng , Tong Xiaoyong , Yang Hui , Fang Huiling , He Qianqian , Li Ning , Shu Xinyu , Liu Qi , Du Yongliang , Fu Beibei , Xiong Yan , Guo Dong , Liu Jin , Li Qian , Zeng Hao , Zhang Xiaokai , Yao Rui , Zhang Xushuo , Guo Wenjin , Mao Xuhu , Long Mian , Lin Xiaoyuan , Zou Quanming , Wu Haibo
Published: February 2024

Acute infection of the central nervous system is one of the deadliest diseases, but the mechanisms by which intracellular bacteria infiltrate the brain remain poorly understood. Phagocytic cells are usually recognized as the battlefield on which war is waged against intracellular bacteria; however, little is known about how the intracellular bacteria take advantage of infected phagocytes to access the brain. In this study, we find that a novel CD36+Fabp4+Pparg+macrophage subpopulation (CD36+macrophage) participates in penetration of the brain by intracellular bacteria without disruption of the brain-blood barrier. Biomechanical analysis reveals that abundant protrusions and adhesion molecules on CD36+macrophages confer significant resistance to the mechanical stress of blood flow, thereby providing more opportunities for these macrophages to adhere to the vascular endothelial surface. Through metabolomics analysis, we find that macrophage lipid metabolism is dysregulated during bacterial neuroinvasion, and that β-hydroxybutyrate promotes the formation and survival of CD36+macrophages. Importantly, ketogenesis exacerbates symptoms during bacterial neuroinvasion, which could be alleviated by supplementing with physiological level of glucose. Taken together, our findings uncover a pathway by which intracellular bacteria hijack macrophages to invade the brain, suggesting that lipid metabolism might play a role in the prevention or resolution of bacterial neuroinvasion.

Graphic Abstract
Bicyclic pyrrolidine inhibitors ofToxoplasma gondiiphenylalanine t-RNA synthetase with antiparasitic potencyin vitroand brain exposure
Authors: Ence Chloe C. , Uddin Taher , Borrel Julien , Mittal Payal , Xie Han , Zoller Jochen , Sharma Amit , Comer Eamon , Schreiber Stuart L. , Melillo Bruno , Sibley L. David , Chatterjee Arnab K.
Published: February 2024

Previous studies have shown that bicyclic azetidines are potent and selective inhibitors of apicomplexan phenylalanine tRNA synthetase (PheRS), leading to parasite growth inhibitionin vitroandin vivo, including in models ofToxoplasmainfection. Despite these useful properties, additional optimization is required for the development of efficacious treatments of toxoplasmosis from this inhibitor series, in particular to achieve sufficient exposure in the brain. Here, we describe a series of PheRS inhibitors built on a new bicyclic pyrrolidine core scaffold designed to retain the exit-vector geometry of the isomeric bicyclic azetidine core scaffold while offering avenues to sample diverse chemical space. Relative to the parent series, bicyclic pyrrolidines retain reasonable potency and target selectivity for parasite PheRS vs. host. Further structure-activity relationship studies revealed that the introduction of aliphatic groups improved potency, ADME and PK properties, including brain exposure. The identification of this new scaffold provides potential opportunities to extend the analog series to further improve selectivity and potency and ultimately deliver a novel, efficacious treatment of toxoplasmosis.

Lay abstract

The inhibition of protein synthesis in parasites has emerged as an attractive strategy to target parasitic diseases such as malaria, cryptosporidiosis, and toxoplasmosis. In this study, we report a new series of small molecules that inhibit the enzyme responsible for loading the amino acid phenylalanine onto its cognate tRNA in the parasite speciesToxoplasma, directly upstream of protein synthesis. We show that small molecules in this new series inhibitToxoplasmaparasite growth at low concentrations, and that, orally administered to mice, these molecules achieve high concentrations in the brain, which hold promise for the treatment of forms of toxoplasmosis that result from parasitic brain infection.
Quantifying the Relative Importance of Genetics and Environment on the Comorbidity between Mental- and Cardiometabolic Disorders: A Comprehensive Analysis of National Register Data from 17 million Scandinavians
Authors: Meijsen Joeri , Hu Kejia , Krebs Morten Dybdahl , Athanasiadis Georgios , Washbrook Sarah , Zetterberg Richard , e Silva Raquel Nogueira Avelar , Shorter John R. , Gådin Jesper R. , Bergstedt Jacob , Howard David M. , Ye Weimin ,   The iPSYCH Consortium, Lu Yi , Valdimarsdóttir Unnur A. , Ingason Andrés , Mikkelsen Dorte Helenius , Plana-Ripoll Oleguer , McGrath John J. , Micali Nadia , Andreassen Ole A. , Werge Thomas M. , Fang Fang , Buil Alfonso
Published: February 2024

Mental disorders (MDs) are leading causes of disability and premature death worldwide, partly due to high comorbidity with cardiometabolic disorders (CMDs). Reasons for this comorbidity are still poorly understood. We leverage nation-wide health records and complete genealogies of Denmark and Sweden (n=17 million) to reveal the genetic and environmental contributions underlying the observed comorbidity between six MDs and 14 CMDs. Genetic factors contributed about 50% to the comorbidity of schizophrenia, affective disorders, and autism spectrum disorder with CMDs, whereas the comorbidity of attention-deficit/hyperactivity disorder and anorexia with CMDs was mainly or fully driven by environmental factors. These findings provide causal insight to guide clinical and scientific initiatives directed at achieving mechanistic understanding as well as preventing and alleviating the consequences of these disorders.
The microbiome interacts with the circadian clock and dietary composition to regulate metabolite cycling in the gut
Authors: Zhang Yueliang , Li Yongjun , Noya Sara B. , Sehgal Amita
Published: February 2024

The gut microbiome plays a key role in the maintenance of host metabolic homeostasis and health. Most metabolic processes cycle with a 24 hour rhythm, but the extent to which the microbiome influences metabolite cycling under different conditions, such as variations in dietary composition, is largely unknown. In this study, we utilized high temporal resolution metabolite profiling of theDrosophilagut to investigate the role of the microbiome in metabolite cycling. Although the microbiome was previously shown to dampen transcript cycling in the gut, we find that in contrast it increases the number of oscillating metabolites. Interestingly, effects of microbiome loss on metabolite cycling are reduced in a time restricted feeding (TF) paradigm. Conversely, promotion of cycling by TF is reduced in microbiome-containing flies, suggesting that TF compensates for deficits in the microbiome to some extent. In a clock mutant background, loss of the microbiome increases cycling of some classes of metabolites but profoundly affects phase of all of them, indicating the host clock modulates effects of the microbiome on cycling and maintains phase in the face of microbial changes. Lastly, a high protein diet increases microbiome-dependent metabolite cycling but a high sugar diet suppresses such cycling while altering phase. Indeed, we observe that amino acid metabolism is the metabolic pathway most affected by changes in the gut microbiome, the circadian clock and timed feeding. Collectively, our observations highlight a key role of the gut microbiome in contributing to host metabolite cycling, and reveal a complex interaction with internal and external factors.
Momentum mismatch driven bound states in the continuum and ellipsometric phase singularities
Authors: Wu Feng , Qi Xin , Qin Meibao , Luo Ma , Long Yang , Wu Jiaju , Sun Yong , Jiang Haitao , Liu Tingting , Xiao Shuyuan , Chen Hong
Published: February 2024

In this paper, we elucidate the formation of bound states in the continuum (BICs) in compound grating waveguide structures from the perspective of momentum mismatch. As the complex lattice reduces to a simple lattice, the excitable guided resonance turns into an unexcitable BIC due to momentum mismatch. Herein, we refer to this state as momentum mismatch driven BIC. Interestingly, as the incidence changes from normal to oblique, the single momentum mismatch driven BIC splits into dual momentum mismatch driven BICs due to the nonzero tangential momentum of the incident light. Distinct from conventional symmetry-protected and accidental BICs, momentum mismatch driven BICs lie in sections of photonic bands. Consequently, factors of momentum mismatch driven quasi-BICs exhibit angular robustness far beyond conventional symmetry-protected and accidental quasi-BICs. Empowered by the momentum mismatch driven BIC, a pair of ellipsometric phase singularities emerge. Enabled by the drastic ellipsometric phase change, ultrasensitive refractive index sensing can be achieved. These results not only provide unique insights into the relation between momentum, BICs, and ellipsometric phase, but also offer a recipe for developing high-performance phase-based optical devices, such as ultrasensitive sensors, wave plates, and spatial light modulators.

Published by the American Physical Society
2024
Scalar field restricted Boltzmann machine as an ultraviolet regulator
Authors: Aarts Gert , Lucini Biagio , Park Chanju
Published: February 2024

Restricted Boltzmann machines (RBMs) are well-known tools used in machine learning to learn probability distribution functions from data. We analyze RBMs with scalar fields on the nodes from the perspective of lattice field theory. Starting with the simplest case of Gaussian fields, we show that the RBM acts as an ultraviolet regulator, with the cutoff determined by either the number of hidden nodes or a model mass parameter. We verify these ideas in the scalar field case, where the target distribution is known, and explore implications for cases where it is not known using the MNIST dataset. We also demonstrate that infrared modes are learnt quickest.

Published by the American Physical Society
2024
Standard model Higgs inflation supplemented by minimal dark matter
Authors: Kawai Shinsuke , Okada Nobuchika , Shafi Qaisar
Published: February 2024

Renormalization group analysis with the present measurements of the top quark mass mt=172.69±0.30  GeV [1] indicates that the Standard Model (SM) Higgs potential becomes unstable at energy scales ∼1010  GeV. This may be interpreted as hinting at new particles at high energy. The minimal extension of the SM that can avoid this instability while leaving the SM Higgs as the sole scalar particle of the theory is obtained by adding suitable fermions to the SM. These fermions are good dark matter candidates and the model is known as the minimal dark matter model. We revisit the inflationary scenario based on the minimal dark matter model, taking into account updated parameter constraints and recent understanding of reheating dynamics. We explore the model with different values of the right-handed neutrino mass and find that the cosmological prediction is insensitive to such details. We obtained a spectral index of the cosmic microwave background ns=0.9672 and a tensor-to-scalar ratio r=0.0031 as a robust prediction of this scenario.

Published by the American Physical Society
2024
Effective field theory of particle mixing
Authors: Cao Shuyang , Boyanovsky Daniel
Published: February 2024

We introduce an effective field theory to study mixing of two fields induced by their couplings to a common decay channel in a medium. The extension of the method of Lee, Oehme, and Yang, the cornerstone of analysis of CP violation in flavored mesons, to include the mixing of particles with different masses provides a guide to and benchmark for the effective field theory. The analysis reveals subtle caveats in the description of mixing in terms of the widely used non-Hermitian effective Hamiltonian, more acute in the nondegenerate case. The effective field theory describes the dynamics of field mixing where the common intermediate states populate a bath in thermal equilibrium, as an . We obtain the effective action up to second order in the couplings, where indirect mixing is a consequence of off-diagonal self-energy components. We find that if only one of the mixing fields features an initial expectation value, indirect mixing induces an expectation value of the other field. The equal time two point correlation functions exhibit an asymptotic approach to a stationary thermal state, and the emergence of long-lived coherence which displays quantum beats as a consequence of interference of quasinormal modes in the medium. The amplitudes of the quantum beats are resonantly enhanced in the nearly degenerate case with potential observational consequences.

Published by the American Physical Society
2024
Detection of astrophysical neutrinos at prospective locations of dark matter detectors
Authors: Zhuang Yi , Strigari Louis E. , Jin Lei , Sinha Samiran
Published: February 2024

We study the prospects for detection of solar, atmospheric neutrino, and diffuse supernova neutrino background (DSNB) fluxes at future large-scale dark matter detectors through both electron and nuclear recoils. We specifically examine how the detection prospects change for several prospective detector locations [Sanford Underground Research Facility (SURF), SNOlab, Gran Sasso, China Jinping Underground Laboratory (CJPL), and Kamioka] and improve upon the statistical methodologies used in previous studies. Because of its ability to measure lower neutrino energies than other locations, we find that the best prospects for the atmospheric neutrino flux are at the SURF location, while the prospects are weakest at CJPL because it is restricted to higher neutrino energies. On the contrary, the prospects for the DSNB are best at CJPL, due largely to the reduced atmospheric neutrino background at this location. Including full detector resolution and efficiency models, the CNO component of the solar flux is detectable via the electron recoil channel with exposures of ∼103 ton-yr for all locations. These results highlight the benefits for employing two detector locations, one at high and one at low latitude.

Published by the American Physical Society
2024
Gravitation wave signal from asteroid mass primordial black hole dark matter
Authors: Ghosh Diptimoy , Mishra Arvind Kumar
Published: February 2024

Primordial black holes (PBHs) in the mass range ∼1017–1023  g are currently unconstrained, and can constitute the full dark matter (DM) density of the universe. Motivated by this, in the current work, we aim to relate the existence of PBHs in the said mass range to the production of observable gravitational waves (GWs) in the upcoming GW detectors. We follow a relatively model-independent approach assuming that the PBHs took birth in a radiation dominated era from enhanced primordial curvature perturbation at small scales produced by inflation. We show that the constraints from cosmic microwave background and BAO data allow for the possibility of PBHs being the whole of DM density of the universe. Finally, we derive the GW spectrum induced by the enhanced curvature perturbations and show that they are detectable in the future GW detectors like eLISA, LISA, BBO, and DECIGO.

Published by the American Physical Society
2024
Approximate higher-form symmetries, topological defects, and dynamical phase transitions
Authors: Armas Jay , Jain Akash
Published: February 2024

Higher-form symmetries are a valuable tool for classifying topological phases of matter. However, emergent higher-form symmetries in interacting many-body systems are typically not exact due to the presence of topological defects. In this paper, we develop a systematic framework for building effective theories with approximate higher-form symmetries. We focus on a continuous U(1) q-form symmetry and study phases with various patterns of spontaneous and explicit symmetry breaking. We uncover a web of dualities between such phases and highlight their role in describing the presence of dynamical higher-form topological defects. In order to study the out-of-equilibrium dynamics of these phases of matter, we formulate respective hydrodynamic theories and study the spectra of excitations exhibiting higher-form charge relaxation and Goldstone relaxation effects. We show that our framework is able to describe various phase transitions due to proliferation of vortices or defects. This includes the melting transition in smectic crystals, the plasma phase transition from polarized gases to magnetohydrodynamics, the spin-ice transition, the superfluid to neutral fluid transition, and the Meissner effect in superconductors, among many others.

Published by the American Physical Society
2024
Using Weyl operators to study Mermin’s inequalities in quantum field theory
Authors: De Fabritiis P. , Guedes F. M. , Guimaraes M. S. , Roditi I. , Sorella S. P.
Published: February 2024

Mermin’s inequalities are investigated in a quantum field theory framework by using von Neumann algebras built with Weyl operators. We devise a general construction based on the Tomita-Takesaki modular theory and use it to compute the vacuum expectation value of the Mermin operator, analyzing the parameter space and explicitly exhibiting a violation of Mermin’s inequalities. Therefore, relying on the power of modular operators, we are able to demonstrate that Mermin’s inequalities are violated when examined within the vacuum state of a scalar field theory.

Published by the American Physical Society
2024
Shedding light on charmonium
Authors: Wang Zhiguo , Li Meijian , Li Yang , Vary James P.
Published: February 2024

We investigate E1 radiative transitions within charmonium in a relativistic approach based on light-front QCD. In quantum field theory, two sets of processes are pure E1: χc0→J/ψγ (ψ→χc0γ) and hc→ηcγ (ηc′→hcγ), both involving the P-wave charmonia. We compute the E1 radiative decay widths as well as the corresponding transition form factors of various processes including those involving 2P states. These observables provide an access to the microscopic structures of the P-wave charmonium. We show that our parameter-free predictions are in excellent agreement with the experimental measurements as well as lattice simulations whenever available.

Published by the American Physical Society
2024
Demonstrating Bayesian quantum phase estimation with quantum error detection
Authors: Yamamoto Kentaro , Duffield Samuel , Kikuchi Yuta , Muñoz Ramo David
Published: February 2024

Quantum phase estimation (QPE) serves as a building block of many different quantum algorithms and finds important applications in computational chemistry problems. Despite the rapid development of quantum hardware, experimental demonstration of QPE for chemistry problems remains challenging due to its large circuit depth and the lack of quantum resources to protect the hardware from noise with fully fault-tolerant protocols. In the present work, we take a step towards fault-tolerant quantum computing by demonstrating a QPE algorithm on a Quantinuum trapped-ion computer. We employ a Bayesian approach to QPE and introduce a routine for optimal parameter selection, which we combine with a [[n+2,n,2]] quantum error detection code carefully tailored to the hardware capabilities. As a simple quantum chemistry example, we take a hydrogen molecule represented by a two-qubit Hamiltonian and estimate its ground state energy using our QPE protocol. In the experiment, we use the quantum circuits containing as many as 920 physical two-qubit gates to estimate the ground state energy within 6×10−3 hartree of the exact value.

Published by the American Physical Society
2024
Correlation Spectroscopy with Multiqubit-Enhanced Phase Estimation
Authors: Hainzer H. , Kiesenhofer D. , Ollikainen T. , Bock M. , Kranzl F. , Joshi M. K. , Yoeli G. , Blatt R. , Gefen T. , Roos C. F.
Published: February 2024

Ramsey interferometry is a widely used tool for precisely measuring transition frequencies between two energy levels of a quantum system, with applications in time keeping, precision spectroscopy, quantum optics, and quantum information. Often, the coherence time of the quantum system surpasses the one of the oscillator probing the system, thereby limiting the interrogation time and associated spectral resolution. Correlation spectroscopy overcomes this limitation by probing two quantum systems with the same noisy oscillator for a measurement of their transition frequency difference; this technique has enabled very precise comparisons of atomic clocks. Here, we extend correlation spectroscopy to the case of multiple quantum systems undergoing strong correlated dephasing. We model Ramsey correlation spectroscopy with N particles as a multiparameter phase estimation problem and demonstrate that multiparticle correlations can assist in reducing the measurement uncertainties even in the absence of entanglement. We derive precision limits and optimal sensing techniques for this problem and compare the performance of probe states and measurement with and without entanglement. Using one- and two-dimensional ion Coulomb crystals with up to 91 qubits, we experimentally demonstrate the advantage of measuring multiparticle correlations for reducing phase uncertainties and apply correlation spectroscopy to measure ion-ion distances, transition frequency shifts, laser-ion detunings, and path-length fluctuations. Our method can be straightforwardly implemented in experimental setups with globally coherent qubit control and qubit-resolved single-shot readout and is, thus, applicable to other physical systems such as neutral atoms in tweezer arrays.

Published by the American Physical Society
2024
Variational sparse diffusion and its application in mesh processing
Authors: Xue Yongjiang , Wang Wei , Song Qingzeng
Published: February 2024

Purpose

The primary objective of this study is to tackle the enduring challenge of preserving feature integrity during the manipulation of geometric data in computer graphics. Our work aims to introduce and validate a variational sparse diffusion model that enhances the capability to maintain the definition of sharp features within meshes throughout complex processing tasks such as segmentation and repair.

Design/methodology/approach

We developed a variational sparse diffusion model that integrates a high-order L1 regularization framework with Dirichlet boundary constraints, specifically designed to preserve edge definition. This model employs an innovative vertex updating strategy that optimizes the quality of mesh repairs. We leverage the augmented Lagrangian method to address the computational challenges inherent in this approach, enabling effective management of the trade-off between diffusion strength and feature preservation. Our methodology involves a detailed analysis of segmentation and repair processes, focusing on maintaining the acuity of features on triangulated surfaces.

Findings

Our findings indicate that the proposed variational sparse diffusion model significantly outperforms traditional smooth diffusion methods in preserving sharp features during mesh processing. The model ensures the delineation of clear boundaries in mesh segmentation and achieves high-fidelity restoration of deteriorated meshes in repair tasks. The innovative vertex updating strategy within the model contributes to enhanced mesh quality post-repair. Empirical evaluations demonstrate that our approach maintains the integrity of original, sharp features more effectively, especially in complex geometries with intricate detail.

Originality/value

The originality of this research lies in the novel application of a high-order L1 regularization framework to the field of mesh processing, a method not conventionally applied in this context. The value of our work is in providing a robust solution to the problem of feature degradation during the mesh manipulation process. Our model’s unique vertex updating strategy and the use of the augmented Lagrangian method for optimization are distinctive contributions that enhance the state-of-the-art in geometry processing. The empirical success of our model in preserving features during mesh segmentation and repair presents an advancement in computer graphics, offering practical benefits to both academic research and industry applications.
Tito’s Goa: deciding the growth strategy for India?
Authors: Mehdi Mokhalles Mohammad , Kumar Nitesh , Srivastava Manish , Akoijam Sunildro L.S. , Sarma Tridib Ranjan
Published: February 2024

Learning outcomes

The case study aims to provide students with an understanding of the challenges a business faces when operating in India. In conclusion of this study, students should be able to know why franchising is such a common way of delivering services to end users, describe the “place” decisions of physical channels, and be familiar with the strategic and tactical location considerations and devise a growth strategy to expand the business.

Case overview/synopsis

Situated at Tito’s Lane in North Goa, Tito’s was the discotheque founded by Tito Henry D’Souza in 1971. The company offered restaurant, concert space and nightclub services to music and party lovers from diverse locations. Ricardo D’Souza and David D’Souza (both brothers) spearheaded the business. Ricardo understood the growth of markets and the factors driving the growth in India. The key factors driving the Tito’s and pub, bar, café and lounge business in India were rising disposable incomes among Indians, nightlife parties by young individuals and preference for quality food and alcoholic beverages among the customers. By seeing the opportunities in 2022, Ricardo considered expanding its business across India. How should Ricardo move to expand its business and offerings? What strategies should they devise for the growth of the business?

Complexity academic level

This case study is designed for use in undergraduate programs like Bachelor of Business Administration. It is ideal for strategy and services marketing. Theoretical frameworks like the Ansoff matrix are suitable for analyzing the case study to understand the growth of the business.

Supplementary materials

Teaching notes are available for educators only.

Subject code

CSS 8: Marketing.
Adjoined ISPH method and artificial intelligence for thermal radiation on double diffusion inside a porous L-shaped cavity with fins
Authors: Elshehabey Hillal M. , Çolak Andaç Batur , Aly Abdelraheem
Published: February 2024

Purpose

The purpose of this study is to adapt the incompressible smoothed particle hydrodynamics (ISPH) method with artificial intelligence to manage the physical problem of double diffusion inside a porous L-shaped cavity including two fins.

Design/methodology/approach

The ISPH method solves the nondimensional governing equations of a physical model. The ISPH simulations are attained at different Frank–Kamenetskii number, Darcy number, coupled Soret/Dufour numbers, coupled Cattaneo–Christov heat/mass fluxes, thermal radiation parameter and nanoparticle parameter. An artificial neural network (ANN) is developed using a total of 243 data sets. The data set is optimized as 171 of the data sets were used for training the model, 36 for validation and 36 for the testing phase. The network model was trained using the Levenberg–Marquardt training algorithm.

Findings

The resulting simulations show how thermal radiation declines the temperature distribution and changes the contour of a heat capacity ratio. The temperature distribution is improved, and the velocity field is decreased by 36.77% when the coupled heat Cattaneo–Christov heat/mass fluxes are increased from 0 to 0.8. The temperature distribution is supported, and the concentration distribution is declined by an increase in Soret–Dufour numbers. A rise in Soret–Dufour numbers corresponds to a decreasing velocity field. The Frank–Kamenetskii number is useful for enhancing the velocity field and temperature distribution. A reduction in Darcy number causes a high porous struggle, which reduces nanofluid velocity and improves temperature and concentration distribution. An increase in nanoparticle concentration causes a high fluid suspension viscosity, which reduces the suspension’s velocity. With the help of the ANN, the obtained model accurately predicts the values of the Nusselt and Sherwood numbers.

Originality/value

A novel integration between the ISPH method and the ANN is adapted to handle the heat and mass transfer within a new L-shaped geometry with fins in the presence of several physical effects.
A robot motion skills method with explicit environmental constraints
Authors: Huang Yonghua , Li Tuanjie , Ning Yuming , Zhang Yan
Published: February 2024

Purpose

This paper aims to solve the problem of the inability to apply learning methods for robot motion skills based on dynamic movement primitives (DMPs) in tasks with explicit environmental constraints, while ensuring the reliability of the robot system.

Design/methodology/approach

The authors propose a novel DMP that takes into account environmental constraints to enhance the generality of the robot motion skill learning method. First, based on the real-time state of the robot and environmental constraints, the task space is divided into different regions and different control strategies are used in each region. Second, to ensure the effectiveness of the generalized skills (trajectories), the control barrier function is extended to DMP to enforce constraint conditions. Finally, a skill modeling and learning algorithm flow is proposed that takes into account environmental constraints within DMPs.

Findings

By designing numerical simulation and prototype demonstration experiments to study skill learning and generalization under constrained environments. The experimental results demonstrate that the proposed method is capable of generating motion skills that satisfy environmental constraints. It ensures that robots remain in a safe position throughout the execution of generation skills, thereby avoiding any adverse impact on the surrounding environment.

Originality/value

This paper explores further applications of generalized motion skill learning methods on robots, enhancing the efficiency of robot operations in constrained environments, particularly in non-point-constrained environments. The improved methods are applicable to different types of robots.
Considering leadership pedagogy in creative arts education
Authors: Walzer Daniel
Published: February 2024

Purpose

In the following theoretical article, the author generates a theory of Leadership Pedagogy and its connection to Creative Arts Education.

Design/methodology/approach

The article analyzes Leadership Theory across three pillars: Socio-relational, Cognitive and Creative, and how these areas underscore thoughtful and caring pedagogy and inclusive teaching in undergraduate education.

Findings

Drawing on the Scholarship of Teaching and Learning (SoTL), the article advocates for a flexible, multifaceted approach to curricular design rooted in theoretical pluralism, prioritizing interdisciplinary methods to bridge theory and practice in Creative Arts Education.

Originality/value

The article concludes with implications for future research and collaboration connecting Leadership Studies and the Arts.
The effect of discount discrepancy on purchase intention: the moderation of justification
Authors: Zuniga Huertas Melby Karina , Ferreira Lepre Thais Rubia , Torres Urdan André
Published: February 2024

Purpose

This paper aims to clarify the effect of discount discrepancy (DD) on consumers’ purchase intention (PI). The authors propose, test and provide evidence and explanations about the moderation of justification in the relation between consumers’ perceived DD and PI.

Design/methodology/approach

The authors conducted three experimental studies with a 2 × 2 factorial design, focusing on consumers’ processing of price discounts. Participants were informed that this study aimed to gather opinions on fashion, clothing and retail sales promotions. They accessed the questionnaire via Qualtrics. Each participant took part in only one study. The experimental conditions were manipulated through scenarios.

Findings

Study 1 tested and supported the moderation of justification on the effect of DD on PI. Study 2 tested and supported the moderation of the type of justification for the effect of DD on PI. Study 3 confirmed the findings in Study 2 and revealed the more effective type of justification.

Research limitations/implications

The authors focused on a typically hedonic product category (fashion clothing). Further research should include a wider variety of goods and services, which could lead to different explanations or generalizations.

Practical implications

Sales promotions must refrain from generating DD between the initial price discount and the subsequent smaller discounts. Practitioners must evaluate the gains of an initial, more considerable percentage discount to attract consumers to the store and sell them other products versus the cost of losing sales because of DD. Management should recognize the importance of giving the correct justification for perceived DD, aligning the firm’s justification with the consumer’s motivation to buy the product.

Social implications

The authors offer subsidies for effective consumer protection policies.

Originality/value

By studying the influence of justification on the effect of DD on PI, the authors propose a mechanism that would reduce the negative effect of DD on consumers’ PI.
Study on the mechanism underlying Trichosanthis peel injection‐induced improvements in myocardial fibrosis markers in patients with chronic heart failure
Authors: He Yue , Gu Xinsheng , Yang Zhou , Wang Hao , Liu Ping
Published: February 2024

In this research, we aimed to observe the changes in myocardial fibrosis indices in patients with chronic heart failure before and after treatment and to evaluate the anti‐chronic heart failure and ventricular remodelling effects of Trichosanthis peel (TP) injection. This study was a single‐center, open, single‐blind, randomized controlled study with an optimal efficacy design. Patients were consecutively and randomly divided into two groups, with 36 patients in the TP injection group and 36 patients in the conventional treatment group. ELISA was used to measure changes in myocardial fibrosis indices before and after discharge, including transforming growth factor β (TGF‐β), serum hyaluronic acid (HA), type I procollagen (PCI), laminin (LN) and type III procollagen (PCIII). There was no significant difference between the two groups in clinical data or baseline level of myocardial fibrosis before treatment. After treatment, compared with the conventional treatment group, the myocardial fibrosis index was significantly decreased following TP injection. Our findings indicate that TP injection combined with conventional medicine can attenuate myocardial fibrosis by reducing angiotensin II, aldosterone, TGFβ, HA, PCI, metallomatrix proteinase 2, connective tissue growth factor and LN and promote ventricular remodelling in patients with chronic heart failure.
Distinct bacterial succession and functional response to alginate in the South, Equatorial, and North Pacific Ocean
Authors: Balmonte John Paul , Giebel Helge‐Ansgar , Arnosti Carol , Simon Meinhard , Wietz Matthias
Published: February 2024

The availability of alginate, an abundant macroalgal polysaccharide, induces compositional and functional responses among marine microbes, but these dynamics have not been characterized across the Pacific Ocean. We investigated alginate‐induced compositional and functional shifts (e.g., heterotrophic production, glucose turnover, hydrolytic enzyme activities) of microbial communities in the South Subtropical, Equatorial, and Polar Frontal North Pacific in mesocosms. We observed that shifts in response to alginate were site‐specific. In the South Subtropical Pacific, prokaryotic cell counts, glucose turnover, and peptidase activities changed the most with alginate addition, along with the enrichment of the widest range of particle‐associated taxa (161 amplicon sequence variants; ASVs) belonging to Alteromonadaceae, Rhodobacteraceae, Phormidiaceae, and Pseudoalteromonadaceae. Some of these taxa were detected at other sites but only enriched in the South Pacific. In the Equatorial Pacific, glucose turnover and heterotrophic prokaryotic production increased most rapidly; a single Alteromonas taxon dominated (60% of the community) but remained low (<2%) elsewhere. In the North Pacific, the particle‐associated community response to alginate was gradual, with a more limited range of alginate‐enriched taxa (82 ASVs). Thus, alginate‐related ecological and biogeochemical shifts depend on a combination of factors that include the ability to utilize alginate, environmental conditions, and microbial interactions.
Understanding institutional layers and modes of change for energy transitions: Analysis of Norway's electricity sector reforms
Authors: Ekanem Minika , Noble Bram F. , Poelzer Greg , Hernes Hans‐Kristian
Published: February 2024

Institutions have significant implications for whether and how energy systems restructure, evolve, and successfully transition. Yet, literature analyzing energy sector reforms often approach transitions from economic or technical perspectives, with much less attention to the underlying roles and influences of institutions. This paper explores the roles and influence of institutions on the speed, direction, timing, and sequence of energy transitions. A conceptual framework integrating the hierarchy of institutions with an historical institutionalist approach is developed and applied to explore transitions in Norway's electricity sector as a case study. Results show that conversion followed by layering emerge as the dominant modes of institutional change in Norway's electricity sector reform, illustrating the importance of alignment between institutions in creating the conditions for large‐scale energy transitions and the importance of boundaries to maintain alignment between levels of institutions. Governments can minimize potential gaps between transition intentions and outcomes through effective conversion and layering of institutional arrangements, but layering challenges emerge when institutional change introduces new actors or energy arenas to existing policy paradigms.
Silver nanoparticles as colorimetric probe for selective determination of Hg2+ from milk samples with ultrasound‐assisted extraction protocol
Authors: Nikam Pranali , Seth Raman , Sharma Rajan
Published: February 2024

The present investigation demonstrates a simple, sensitive and selective colorimetric probe for the detection of Hg2+ in milk samples employing redox interaction of Hg2+ ions with citrate‐stabilised silver nanoparticles, inducing colour change from yellow to colourless. Milk samples were pretreated by ultrasound assistance in acidic media. The detection limit (LOD) was 6.17 ppb using UV–Visible spectrophotometer with linear correlation (R2 = 0.9901) at 10–2000 ppb solution of Hg2+ ions. Developed probe was highly selective to Hg2+ over different interfering metal ions and can be effectively employed to identify Hg2+ in milk samples.